From 0725f5fe2b57daee82e35232bab43949bc6fa528 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 9 Jul 2026 15:31:34 +0700
Subject: [PATCH 001/202] refactor simulation.py

---
 mcdc/main.py               |  4 +-
 mcdc/object_/simulation.py | 87 +++++++++++++++++++++-----------------
 2 files changed, 50 insertions(+), 41 deletions(-)

diff --git a/mcdc/main.py b/mcdc/main.py
index 71db344ae..ead76f36c 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -3,7 +3,7 @@
 # ======================================================================================
 
 
-def run():
+def run(simulationPy):
     """
     Execute the MC/DC simulation.
 
@@ -21,8 +21,6 @@ def run():
     time_total_start = MPI.Wtime()
 
     # Get settings and MPI master status
-    from mcdc.object_.simulation import simulation as simulationPy
-
     settings = simulationPy.settings
     master = MPI.COMM_WORLD.Get_rank() == 0
 
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 48e7e3433..c03064e44 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -30,11 +30,11 @@
 
 ####
 
-from mcdc.object_.base import ObjectSingleton
+from mcdc.object_.base import ObjectBase
 from mcdc.object_.data import DataBase, DataNone
 from mcdc.object_.distribution import DistributionBase, DistributionNone
 from mcdc.object_.gpu_tools import GPUMeta
-from mcdc.object_.mesh import MeshBase, MeshUniform
+from mcdc.object_.mesh import MeshBase
 from mcdc.object_.particle import ParticleBank
 from mcdc.object_.settings import Settings
 from mcdc.object_.universe import Universe, Lattice
@@ -44,7 +44,7 @@
 # ======================================================================================
 
 
-class Simulation(ObjectSingleton):
+class Simulation(ObjectBase):
     # Annotations for Numba mode
     label: str = "simulation"
     non_numba: list[str] = [
@@ -58,19 +58,19 @@ class Simulation(ObjectSingleton):
     # Physics
     data: list[DataBase]
     distributions: list[DistributionBase]
-    materials: list[MaterialBase]
-    elements: list[Element]
+    neutron_reactions: list[NeutronReactionBase]
     electron_reactions: list[ElectronReactionBase]
     nuclides: list[Nuclide]
-    neutron_reactions: list[NeutronReactionBase]
+    elements: list[Element]
+    materials: list[MaterialBase]
     sources: list[Source]
 
     # Geometry
-    cells: list[Cell]
-    lattices: list[Lattice]
-    regions: list[Region]
     surfaces: list[Surface]
+    regions: list[Region]
+    cells: list[Cell]
     universes: list[Universe]
+    lattices: list[Lattice]
     meshes: list[MeshBase]
 
     # Tallies
@@ -92,31 +92,37 @@ class Simulation(ObjectSingleton):
     bank_source: ParticleBank
     bank_future: ParticleBank
 
-    # Simulation parameters
+    # Simulation indices
     idx_work: int
     idx_cycle: int
     idx_census: int
     idx_batch: int
-    dd_idx: int
-    dd_N_local_source: int
-    dd_local_rank: int
+
+    # k-eigenvalue globals
     k_eff: float
     k_cycle: NDArray[float64]
     k_avg: float
     k_sdv: float
+    k_avg_running: float
+    k_sdv_running: float
+    #
     n_avg: float
     n_sdv: float
     n_max: float
+    #
     C_avg: float
     C_sdv: float
     C_max: float
-    k_avg_running: float
-    k_sdv_running: float
-    gyration_radius: NDArray[float64]
-    cycle_active: bool
+    #
     eigenvalue_tally_nuSigmaF: Annotated[NDArray[float64], (1,)]
     eigenvalue_tally_n: Annotated[NDArray[float64], (1,)]
     eigenvalue_tally_C: Annotated[NDArray[float64], (1,)]
+    #
+    gyration_radius: NDArray[float64]
+    #
+    cycle_active: bool
+
+    # MPI parameters
     mpi_size: int
     mpi_rank: int
     mpi_master: bool
@@ -124,6 +130,8 @@ class Simulation(ObjectSingleton):
     mpi_work_size: int
     mpi_work_size_total: int
     mpi_work_iter: Annotated[NDArray[int64], (1,)]
+
+    # Runtimes
     runtime_total: float
     runtime_preparation: float
     runtime_simulation: float
@@ -135,7 +143,7 @@ class Simulation(ObjectSingleton):
     source_seed: int
 
     def __init__(self):
-        super().__init__()
+        super().__init__(register=False)
 
         # ==============================================================================
         # Simulation objects
@@ -144,19 +152,19 @@ def __init__(self):
         # Physics
         self.data = [DataNone()]
         self.distributions = [DistributionNone()]
-        self.materials = []
-        self.elements = []
+        self.neutron_reactions = []
         self.electron_reactions = []
         self.nuclides = []
-        self.neutron_reactions = []
+        self.elements = []
+        self.materials = []
         self.sources = []
 
         # Geometry
-        self.cells = []
-        self.lattices = []
-        self.regions = []
         self.surfaces = []
+        self.regions = []
+        self.cells = []
         self.universes = [Universe("Root Universe", root=True)]
+        self.lattices = []
         self.meshes = []
 
         # Tallies
@@ -182,7 +190,7 @@ def __init__(self):
         self.bank_future = ParticleBank(tag="future")
 
         # ==============================================================================
-        # Simulation parameters
+        # Simulation variables and parameters
         # ==============================================================================
 
         # Simulation indices
@@ -191,29 +199,29 @@ def __init__(self):
         self.idx_census = 0
         self.idx_batch = 0
 
-        # Domain decomposition
-        self.dd_idx = 0
-        self.dd_N_local_source = 0
-        self.dd_local_rank = 0
-
         # Eigenvalue simulation
         self.k_eff = 0.0
         self.k_cycle = np.ones(1)
         self.k_avg = 0.0
         self.k_sdv = 0.0
+        self.k_avg_running = 0.0
+        self.k_sdv_running = 0.0
+        #
         self.n_avg = 0.0  # Neutron density
         self.n_sdv = 0.0
         self.n_max = 0.0
+        #
         self.C_avg = 0.0  # Precursor density
         self.C_sdv = 0.0
         self.C_max = 0.0
-        self.k_avg_running = 0.0
-        self.k_sdv_running = 0.0
-        self.gyration_radius = np.zeros(1)
-        self.cycle_active = False
+        #
         self.eigenvalue_tally_nuSigmaF = np.zeros(1)
         self.eigenvalue_tally_n = np.zeros(1)
         self.eigenvalue_tally_C = np.zeros(1)
+        #
+        self.gyration_radius = np.zeros(1)
+        #
+        self.cycle_active = False
 
         # MPI parameters
         self.mpi_size = MPI.COMM_WORLD.Get_size()
@@ -224,7 +232,7 @@ def __init__(self):
         self.mpi_work_size_total = 0
         self.mpi_work_iter = np.zeros(1, dtype=int64)
 
-        # Runtime records
+        # Runtimes
         self.runtime_total = 0.0
         self.runtime_preparation = 0.0
         self.runtime_simulation = 0.0
@@ -235,8 +243,11 @@ def __init__(self):
         self.gpu_meta = GPUMeta()
         self.source_seed = 0
 
-    def set_root_universe(self, cells=[]):
-        self.universes[0].cells = cells
+    # ==================================================================================
+    # Run simulation
+    # ==================================================================================
 
+    def run(self):
+        from mcdc.main import run
 
-simulation = Simulation()
+        return run(self)

From d5649f66f3800c8e53233fcf63ed2d1acb7886eb Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 9 Jul 2026 20:13:49 +0700
Subject: [PATCH 002/202] refactor simulation.py

---
 mcdc/__init__.py           | 15 +------------
 mcdc/main.py               |  5 ++---
 mcdc/object_/simulation.py | 43 +++++++++++++++++++++++++++-----------
 mcdc/visualize.py          |  5 +++--
 4 files changed, 37 insertions(+), 31 deletions(-)

diff --git a/mcdc/__init__.py b/mcdc/__init__.py
index e3147dd75..2685c44c8 100644
--- a/mcdc/__init__.py
+++ b/mcdc/__init__.py
@@ -9,27 +9,14 @@
 # Simulation building blocks
 # ======================================================================================
 
-# The simulation
-from mcdc.object_.simulation import simulation
-
-# The settings
-settings = simulation.settings
-
-# The objects
 from mcdc.object_.cell import Cell, Universe, Lattice
 from mcdc.object_.material import Material, MaterialMG
 from mcdc.object_.mesh import MeshUniform, MeshStructured
+from mcdc.object_.simulation import Simulation
 from mcdc.object_.source import Source
 from mcdc.object_.surface import Surface
 from mcdc.object_.tally import Tally
 
-# ======================================================================================
-# Runners
-# ======================================================================================
-
-from mcdc.main import run
-from mcdc.visualize import visualize
-
 # ======================================================================================
 # Misc.
 # ======================================================================================
diff --git a/mcdc/main.py b/mcdc/main.py
index ead76f36c..6fa308047 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -42,7 +42,7 @@ def run(simulationPy):
     #       The use of container is necessary to ensure proper mutability and tracking
     #       of the structure when running in different kinds of machines supported by
     #       the Numba-based compilation framework.
-    simulation_container, data = preparation()
+    simulation_container, data = preparation(simulationPy)
     simulation = simulation_container[0]
 
     # Print headers
@@ -116,12 +116,11 @@ def run(simulationPy):
 # ======================================================================================
 
 
-def preparation():
+def preparation(simulationPy):
     import math
 
     from mpi4py import MPI
 
-    from mcdc.object_.simulation import simulation as simulationPy
     from mcdc.object_.material import (
         Material,
         MaterialMG,
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index c03064e44..7a0e2a29e 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -1,14 +1,6 @@
 from __future__ import annotations
 from typing import TYPE_CHECKING, Annotated
 
-from mcdc.object_.technique import (
-    ImplicitCapture,
-    PopulationControl,
-    GlobalWeightRoulette,
-    WeightWindows,
-    WeightedEmission,
-)
-
 if TYPE_CHECKING:
     from mcdc.object_.cell import Cell, Region
     from mcdc.object_.element import Element
@@ -24,6 +16,7 @@
 
 import numpy as np
 
+from collections.abc import Sequence
 from mpi4py import MPI
 from numpy import float64, int64
 from numpy.typing import NDArray
@@ -37,6 +30,14 @@
 from mcdc.object_.mesh import MeshBase
 from mcdc.object_.particle import ParticleBank
 from mcdc.object_.settings import Settings
+from mcdc.object_.technique import (
+    ImplicitCapture,
+    PopulationControl,
+    GlobalWeightRoulette,
+    WeightWindows,
+    WeightedEmission,
+)
+
 from mcdc.object_.universe import Universe, Lattice
 
 # ======================================================================================
@@ -142,7 +143,7 @@ class Simulation(ObjectBase):
     gpu_meta: GPUMeta
     source_seed: int
 
-    def __init__(self):
+    def __init__(self) -> None:
         super().__init__(register=False)
 
         # ==============================================================================
@@ -244,10 +245,28 @@ def __init__(self):
         self.source_seed = 0
 
     # ==================================================================================
-    # Run simulation
+    # Simulation object setters
+    # ==================================================================================
+
+    def set_model(self, cells: Sequence[Cell]) -> None:
+        self.universes[0].cells = list(cells)
+
+    def set_sources(self, sources: Sequence[Source]) -> None:
+        self.sources = list(sources)
+
+    def set_tallies(self, tallies: Sequence[Tally]) -> None:
+        self.tallies = list(tallies)
+
+    # ==================================================================================
+    # Operations
     # ==================================================================================
 
-    def run(self):
+    def visualize_model(self, vis_type, x, y, z, pixels, colors, time, save_as) -> None:
+        from mcdc.visualize import visualize_model
+
+        visualize_model(self, vis_type, x, y, z, pixels, colors, time, save_as)
+
+    def run(self) -> None:
         from mcdc.main import run
 
-        return run(self)
+        run(self)
diff --git a/mcdc/visualize.py b/mcdc/visualize.py
index 25640041a..de98502f7 100644
--- a/mcdc/visualize.py
+++ b/mcdc/visualize.py
@@ -5,7 +5,8 @@
 _visualize_cache = None
 
 
-def visualize(
+def visualize_model(
+    simulationPy,
     vis_type,
     x=0.0,
     y=0.0,
@@ -44,7 +45,7 @@ def visualize(
     # Use cached preparation if available
     global _visualize_cache
     if _visualize_cache is None:
-        _visualize_cache = preparation()
+        _visualize_cache = preparation(simulationPy)
     simulation_container, data = _visualize_cache
     simulation = simulation_container[0]
 

From 69965f70e25e83c3d8d972d1f8247a7944b26e17 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 9 Jul 2026 20:36:27 +0700
Subject: [PATCH 003/202] improve hints

---
 mcdc/object_/mesh.py  | 6 +++---
 mcdc/object_/tally.py | 2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index 6307b6ef0..32b9358ab 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -171,9 +171,9 @@ class MeshStructured(MeshBase):
     def __init__(
         self,
         name: str = "",
-        x: Sequence[float] = [-INF, INF],
-        y: Sequence[float] = [-INF, INF],
-        z: Sequence[float] = [-INF, INF],
+        x: Sequence[float] | NDArray[float64] = np.array([-INF, INF]),
+        y: Sequence[float] | NDArray[float64] = np.array([-INF, INF]),
+        z: Sequence[float] | NDArray[float64] = np.array([-INF, INF]),
     ):
         type_ = MESH_STRUCTURED
         super().__init__(type_, name)
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 225059696..107f95157 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -89,7 +89,7 @@ def __new__(
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
         energy: Sequence[float] | str | NoneType = None,
-        time: Sequence[float] | NoneType = None,
+        time: Sequence[float] | NDArray[float64] | NoneType = None,
         spatial_shape: tuple[int, ...] | NoneType = None,
     ) -> TallySurfaceCrossing | TallyTracklength | TallyCollision:
         # Determine tally estimator type and create the instance based on the provided

From 49dcd7066b7c4d9cdf6d06bf8950869e8b79a44d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 13 Jul 2026 10:03:16 +0700
Subject: [PATCH 004/202] set overall simulation object

---
 mcdc/main.py                     | 202 ++++++++++++++++++++++++++++++-
 mcdc/numba_types.py              |  59 +++++----
 mcdc/object_/base.py             |  15 +--
 mcdc/object_/cell.py             |  55 +++------
 mcdc/object_/data.py             |   6 +-
 mcdc/object_/distribution.py     |   6 +-
 mcdc/object_/material.py         |   8 +-
 mcdc/object_/mesh.py             |   7 +-
 mcdc/object_/neutron_reaction.py |   3 -
 mcdc/object_/nuclide.py          |   5 +-
 mcdc/object_/simulation.py       | 201 ++++++++++++++++++++++++++++--
 mcdc/object_/source.py           |  22 ++--
 mcdc/object_/surface.py          |  30 +++--
 mcdc/object_/tally.py            |  17 +--
 mcdc/object_/universe.py         |  14 +--
 15 files changed, 503 insertions(+), 147 deletions(-)

diff --git a/mcdc/main.py b/mcdc/main.py
index 6fa308047..31864d521 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -1,9 +1,9 @@
 # ======================================================================================
-# Run
+# Run Simulation
 # ======================================================================================
 
 
-def run(simulationPy):
+def run_simulation(simulationPy):
     """
     Execute the MC/DC simulation.
 
@@ -112,11 +112,11 @@ def run(simulationPy):
 
 
 # ======================================================================================
-# Preparation
+# Prepare
 # ======================================================================================
 
 
-def preparation(simulationPy):
+def prepare(simulationPy):
     import math
 
     from mpi4py import MPI
@@ -159,7 +159,199 @@ def preparation(simulationPy):
     # Set nuclear and atomic data for transported particles
     if settings.neutron_transport:
         for nuclide in simulationPy.nuclides:
-            nuclide.set_neutron_data()
+            nuclide.set_neutron_data(simulationPy)
+
+        for material in simulationPy.materials:
+            if isinstance(material, Material):
+                update_fissionable_from_nuclides(material)
+
+    if settings.electron_transport:
+        for element in simulationPy.elements:
+            element.set_electron_data()
+
+    # Set physics mode
+    if len(simulationPy.materials) == 0:
+        # Default physics in dummy mode
+        settings.neutron_multigroup_mode = True
+    else:
+        settings.neutron_multigroup_mode = isinstance(
+            simulationPy.materials[0], MaterialMG
+        )
+
+    # ==================================================================================
+    # Adjust simulation parameters as needed
+    # ==================================================================================
+
+    # Reset time grid size of all tallies if census-based tally is desired
+    if settings.use_census_based_tally:
+        N_bin = settings.census_tally_frequency
+        for tally in simulationPy.tallies:
+            tally._use_census_based_tally(N_bin)
+
+    # Normalize source probability
+    norm = 0.0
+    for source in simulationPy.sources:
+        norm += source.probability
+    for source in simulationPy.sources:
+        source.probability /= norm
+
+    # Create root universe if not defined
+    if len(simulationPy.universes[0].cells) == 0:
+        simulationPy.universes[0].cells = simulationPy.cells
+
+    # Initial guess
+    simulationPy.k_eff = settings.k_init
+
+    # Activate tally scoring for fixed-source
+    if not settings.neutron_eigenvalue_mode:
+        simulationPy.cycle_active = True
+    # All active eigenvalue cycle?
+    elif settings.N_inactive == 0:
+        simulationPy.cycle_active = True
+
+    # ==================================================================================
+    # Set particle bank sizes
+    # ==================================================================================
+
+    # Some sizes
+    N_particle = settings.N_particle
+    N_work = math.ceil(N_particle / MPI.COMM_WORLD.Get_size())
+    N_census = settings.N_census
+
+    # Determine bank size
+    if settings.neutron_eigenvalue_mode or N_census == 1:
+        settings.future_bank_buffer_ratio = 0.0
+    if not settings.neutron_eigenvalue_mode and N_census == 1:
+        settings.census_bank_buffer_ratio = 0.0
+        settings.source_bank_buffer_ratio = 0.0
+    size_active = settings.active_bank_buffer
+    size_census = int((settings.census_bank_buffer_ratio) * N_work)
+    size_source = int((settings.source_bank_buffer_ratio) * N_work)
+    size_future = int((settings.future_bank_buffer_ratio) * N_work)
+
+    # Set bank size
+    simulationPy.bank_active.size[0] = size_active
+    simulationPy.bank_census.size[0] = size_census
+    simulationPy.bank_source.size[0] = size_source
+    simulationPy.bank_future.size[0] = size_future
+
+    # ==================================================================================
+    # Generate Numba-supported "Objects"
+    # ==================================================================================
+
+    from mcdc.code_factory.numba_objects_generator import generate_numba_objects
+    from mcdc.code_factory.literals_generator import make_literals
+
+    make_literals(simulationPy)
+
+    simulation_container, data = generate_numba_objects(simulationPy)
+    simulation = simulation_container[0]
+
+    # Reload mcdc getters and setters
+    import importlib
+    import mcdc.mcdc_get as mcdc_get
+    import mcdc.mcdc_set as mcdc_set
+
+    importlib.reload(mcdc_get)
+    importlib.reload(mcdc_set)
+
+    # ==================================================================================
+    # Adapt functions as needed
+    # ==================================================================================
+
+    # Pick physics model
+    import mcdc.transport.physics as physics
+
+    if settings.neutron_multigroup_mode:
+        physics.neutron.particle_speed = physics.neutron.multigroup.particle_speed
+        physics.neutron.macro_xs = physics.neutron.multigroup.macro_xs
+        physics.neutron.neutron_production_xs = (
+            physics.neutron.multigroup.neutron_production_xs
+        )
+        physics.neutron.collision = physics.neutron.multigroup.collision
+
+    # Pick Python-version RNG if needed
+    import mcdc.config as config
+    import mcdc.transport.rng as rng
+
+    if config.mode == "python":
+        rng.wrapping_add = rng.wrapping_add_python
+        rng.wrapping_mul = rng.wrapping_mul_python
+
+    # TODO: Find out why the following is needed to avoid circular import
+    import mcdc.transport.particle_bank as particle_bank_module
+
+    # ==================================================================================
+    # Source particles from file
+    # ==================================================================================
+    # TODO: Use parallel h5py, may need to compile for speed
+
+    import h5py
+
+    # All ranks, take turn
+    for i in range(simulation["mpi_size"]):
+        if simulation["mpi_rank"] == i:
+            if settings.use_source_file:
+                with h5py.File(settings.source_file_name, "r") as f:
+                    # Get source particle size
+                    N_particle = f["particles_size"][()]
+
+                    # Redistribute work
+                    mpi.distribute_work(N_particle, simulation)
+                    N_local = simulation["mpi_work_size"]
+                    start = simulation["mpi_work_start"]
+                    end = start + N_local
+
+                    # Add particles to source bank
+                    simulation["bank_source"]["particles"][:N_local] = f["particles"][
+                        start:end
+                    ]
+                    simulation["bank_source"]["size"] = N_local
+        MPI.COMM_WORLD.Barrier()
+
+    # ==================================================================================
+    # Finalize
+    # ==================================================================================
+
+    return simulation_container, data
+
+
+# ======================================================================================
+# Compile Simulation
+# ======================================================================================
+
+
+def compile_simulation(simulationPy, compile_ID):
+    # Empty out
+    # Go over cells in the root universe
+
+    from mcdc.object_.material import (
+        Material,
+        MaterialMG,
+        set_elements_from_nuclides,
+        set_nuclides_from_elements,
+        update_fissionable_from_nuclides,
+    )
+
+    # ==================================================================================
+    # Set material data as needed
+    # ==================================================================================
+
+    # Set material compositions based on transported particles
+    for material in simulationPy.materials:
+        if not isinstance(material, Material):
+            continue
+
+        if settings.neutron_transport and len(material.nuclides) == 0:
+            set_nuclides_from_elements(material)
+
+        if settings.electron_transport and len(material.elements) == 0:
+            set_elements_from_nuclides(material)
+
+    # Set nuclear and atomic data for transported particles
+    if settings.neutron_transport:
+        for nuclide in simulationPy.nuclides:
+            nuclide.set_neutron_data(simulationPy)
 
         for material in simulationPy.materials:
             if isinstance(material, Material):
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index 0948870c6..5b5646971 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -778,14 +778,16 @@ def set_simulation(N: dict):
         ('N_tabulated_distribution', int64),
         ('tabulated_energy_angle_distributions', tabulated_energy_angle_distribution, (N['tabulated_energy_angle_distribution'])),
         ('N_tabulated_energy_angle_distribution', int64),
-        ('materials', material, (N['material'])),
-        ('N_material', int64),
-        ('native_materials', native_material, (N['native_material'])),
-        ('N_native_material', int64),
-        ('multigroup_materials', multigroup_material, (N['multigroup_material'])),
-        ('N_multigroup_material', int64),
-        ('elements', element, (N['element'])),
-        ('N_element', int64),
+        ('neutron_reactions', neutron_reaction, (N['neutron_reaction'])),
+        ('N_neutron_reaction', int64),
+        ('neutron_capture_reactions', neutron_capture_reaction, (N['neutron_capture_reaction'])),
+        ('N_neutron_capture_reaction', int64),
+        ('neutron_elastic_scattering_reactions', neutron_elastic_scattering_reaction, (N['neutron_elastic_scattering_reaction'])),
+        ('N_neutron_elastic_scattering_reaction', int64),
+        ('neutron_fission_reactions', neutron_fission_reaction, (N['neutron_fission_reaction'])),
+        ('N_neutron_fission_reaction', int64),
+        ('neutron_inelastic_scattering_reactions', neutron_inelastic_scattering_reaction, (N['neutron_inelastic_scattering_reaction'])),
+        ('N_neutron_inelastic_scattering_reaction', int64),
         ('electron_reactions', electron_reaction, (N['electron_reaction'])),
         ('N_electron_reaction', int64),
         ('electron_bremsstrahlung_reactions', electron_bremsstrahlung_reaction, (N['electron_bremsstrahlung_reaction'])),
@@ -798,26 +800,24 @@ def set_simulation(N: dict):
         ('N_electron_ionization_reaction', int64),
         ('nuclides', nuclide, (N['nuclide'])),
         ('N_nuclide', int64),
-        ('neutron_reactions', neutron_reaction, (N['neutron_reaction'])),
-        ('N_neutron_reaction', int64),
-        ('neutron_capture_reactions', neutron_capture_reaction, (N['neutron_capture_reaction'])),
-        ('N_neutron_capture_reaction', int64),
-        ('neutron_elastic_scattering_reactions', neutron_elastic_scattering_reaction, (N['neutron_elastic_scattering_reaction'])),
-        ('N_neutron_elastic_scattering_reaction', int64),
-        ('neutron_fission_reactions', neutron_fission_reaction, (N['neutron_fission_reaction'])),
-        ('N_neutron_fission_reaction', int64),
-        ('neutron_inelastic_scattering_reactions', neutron_inelastic_scattering_reaction, (N['neutron_inelastic_scattering_reaction'])),
-        ('N_neutron_inelastic_scattering_reaction', int64),
+        ('elements', element, (N['element'])),
+        ('N_element', int64),
+        ('materials', material, (N['material'])),
+        ('N_material', int64),
+        ('native_materials', native_material, (N['native_material'])),
+        ('N_native_material', int64),
+        ('multigroup_materials', multigroup_material, (N['multigroup_material'])),
+        ('N_multigroup_material', int64),
         ('sources', source, (N['source'])),
         ('N_source', int64),
-        ('cells', cell, (N['cell'])),
-        ('N_cell', int64),
-        ('lattices', lattice, (N['lattice'])),
-        ('N_lattice', int64),
         ('surfaces', surface, (N['surface'])),
         ('N_surface', int64),
+        ('cells', cell, (N['cell'])),
+        ('N_cell', int64),
         ('universes', universe, (N['universe'])),
         ('N_universe', int64),
+        ('lattices', lattice, (N['lattice'])),
+        ('N_lattice', int64),
         ('meshes', mesh, (N['mesh'])),
         ('N_mesh', int64),
         ('structured_meshes', structured_mesh, (N['structured_mesh'])),
@@ -843,32 +843,31 @@ def set_simulation(N: dict):
         ('bank_source', bank_source),
         ('bank_census', bank_census),
         ('bank_active', bank_active),
+        ('name', 'U32'),
+        ('compile_ID', int64),
         ('idx_work', int64),
         ('idx_cycle', int64),
         ('idx_census', int64),
         ('idx_batch', int64),
-        ('dd_idx', int64),
-        ('dd_N_local_source', int64),
-        ('dd_local_rank', int64),
         ('k_eff', float64),
         ('k_cycle_offset', int64),
         ('k_cycle_length', int64),
         ('k_avg', float64),
         ('k_sdv', float64),
+        ('k_avg_running', float64),
+        ('k_sdv_running', float64),
         ('n_avg', float64),
         ('n_sdv', float64),
         ('n_max', float64),
         ('C_avg', float64),
         ('C_sdv', float64),
         ('C_max', float64),
-        ('k_avg_running', float64),
-        ('k_sdv_running', float64),
-        ('gyration_radius_offset', int64),
-        ('gyration_radius_length', int64),
-        ('cycle_active', bool),
         ('eigenvalue_tally_nuSigmaF', float64, (1,)),
         ('eigenvalue_tally_n', float64, (1,)),
         ('eigenvalue_tally_C', float64, (1,)),
+        ('gyration_radius_offset', int64),
+        ('gyration_radius_length', int64),
+        ('cycle_active', bool),
         ('mpi_size', int64),
         ('mpi_rank', int64),
         ('mpi_master', bool),
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index 11d87e8ad..3e249ca10 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -6,10 +6,7 @@
 
 
 class ObjectBase:
-    def __init__(self, register):
-        if register and isinstance(self, ObjectNonSingleton):
-            register_object(self)
-
+    def __init__(self):
         if "non_numba" in dir(self):
             self.non_numba += ["non_numba", "label"]
         else:
@@ -24,15 +21,15 @@ def __setattr__(self, key, value):
 
 class ObjectSingleton(ObjectBase):
     def __init__(self):
-        super().__init__(register=False)
+        super().__init__()
 
 
 class ObjectNonSingleton(ObjectBase):
     ID: int
 
-    def __init__(self, register=True):
+    def __init__(self):
         self.ID = -1
-        super().__init__(register)
+        super().__init__()
 
         if "non_numba" in dir(self):
             self.non_numba += ["ID"]
@@ -44,10 +41,10 @@ class ObjectPolymorphic(ObjectNonSingleton):
     child_ID: int
     type: int
 
-    def __init__(self, type_, register=True):
+    def __init__(self, type_):
         self.child_ID = -1
         self.type = type_
-        super().__init__(register)
+        super().__init__()
 
         self.non_numba += ["child_ID"]
 
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 54e0947c9..d28d336ff 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -30,7 +30,6 @@
 )
 from mcdc.object_.base import ObjectNonSingleton
 from mcdc.object_.material import MaterialBase
-from mcdc.object_.simulation import simulation
 from mcdc.object_.tally import TallyCollision, TallyTracklength
 from mcdc.object_.universe import Universe, Lattice
 from mcdc.print_ import print_error
@@ -40,18 +39,6 @@
 # ======================================================================================
 
 
-# Region-making helper that checks if an identical region is already created
-def make_region(type_, A, B):
-    for existing_region in simulation.regions:
-        if (
-            type_ == existing_region.type
-            and A == existing_region.A
-            and B == existing_region.B
-        ):
-            return existing_region
-    return Region(type_, A, B)
-
-
 class Region(ObjectNonSingleton):
     type: str
     A: Surface | Region | NoneType
@@ -66,35 +53,20 @@ def __init__(self, type_, A, B):
 
     @classmethod
     def make_halfspace(cls, surface, sense):
-        region = make_region("halfspace", surface, sense)
+        region = Region("halfspace", surface, sense)
         return region
 
     def __and__(self, other):
-        return make_region("intersection", self, other)
+        return Region("intersection", self, other)
 
     def __or__(self, other):
-        return make_region("union", self, other)
+        return Region("union", self, other)
 
     def __invert__(self):
-        return make_region("complement", self, None)
+        return Region("complement", self, None)
 
     def __repr__(self):
-        text = "Region: "
-        if self.type == "halfspace":
-            if self.B > 0:
-                text += "+s%i" % self.A.ID
-            else:
-                text += "-s%i" % self.A.ID
-        elif self.type == "intersection":
-            text += "r%i & r%i" % (self.A.ID, self.B.ID)
-        elif self.type == "union":
-            text += "r%i | r%i" % (self.A.ID, self.B.ID)
-        elif self.type == "complement":
-            text += "~r%i" % (self.A.ID)
-        elif self.type == "all":
-            text += "all"
-
-        return text
+        return f"Region: {str.capitalize(self.type)}"
 
 
 # ======================================================================================
@@ -157,14 +129,14 @@ def __init__(
         super().__init__()
 
         # Set name
-        if name != "":
-            self.name = name
+        if name == "":
+            self.name = "(Unnamed cell)"
         else:
-            self.name = f"{self.label}_{self.ID}"
+            self.name = name
 
         # Set region
         if region is None:
-            self.region = make_region("all", None, None)
+            self.region = Region("all", None, None)
         else:
             self.region = region
 
@@ -184,15 +156,19 @@ def __init__(
             self.rotation *= PI / 180.0
 
         # Set region Reversed Polished Notation (RPN)
+        # TODO
+        """
         if self.region.type != "all":
             self.region_RPN_tokens = generate_RPN_tokens(self.region)
             self.region_RPN = generate_RPN(self.region_RPN_tokens)
         else:
             self.region_RPN_tokens = []
             self.region_RPN = Boolean(True)
+        """
 
         # List surfaces
-        self.surfaces = list_surfaces(self.region_RPN_tokens)
+        # TODO
+        # self.surfaces = list_surfaces(self.region_RPN_tokens)
 
         # Cell tallies
         self.collision_tallies = []
@@ -222,7 +198,6 @@ def __init__(
     def __repr__(self):
         text = "\n"
         text += f"Cell\n"
-        text += f"  - ID: {self.ID}\n"
         text += f"  - Name: {self.name}\n"
         text += f"  - {self.region}\n"
         if isinstance(self.fill, MaterialBase):
@@ -235,7 +210,7 @@ def __repr__(self):
             text += f"  - Translation: {self.translation}\n"
         if self.fill_rotated:
             text += f"  - Rotation: {self.rotation * 180 / PI}\n"
-        text += f"  - Bounding surfaces: {[x.ID for x in self.surfaces]}\n"
+        # text += f"  - Bounding surfaces: {[x.ID for x in self.surfaces]}\n"
         if len(self.collision_tallies) > 0:
             text += f"  - Collision tallies: {[x.ID for x in self.collision_tallies]}\n"
         if len(self.tracklength_tallies) > 0:
diff --git a/mcdc/object_/data.py b/mcdc/object_/data.py
index 8f513fad7..c8ab82821 100644
--- a/mcdc/object_/data.py
+++ b/mcdc/object_/data.py
@@ -29,8 +29,8 @@ class DataBase(ObjectPolymorphic):
     # Annotations for Numba mode
     label: str = "data"
 
-    def __init__(self, type_, register=True):
-        super().__init__(type_, register)
+    def __init__(self, type_):
+        super().__init__(type_)
 
     def __repr__(self):
         text = "\n"
@@ -61,7 +61,7 @@ class DataNone(DataBase):
 
     def __init__(self):
         type_ = DATA_NONE
-        super().__init__(type_, False)
+        super().__init__(type_)
         self.ID = 0
 
 
diff --git a/mcdc/object_/distribution.py b/mcdc/object_/distribution.py
index 8784e1d2d..f732d2ffe 100644
--- a/mcdc/object_/distribution.py
+++ b/mcdc/object_/distribution.py
@@ -39,8 +39,8 @@ class DistributionBase(ObjectPolymorphic):
     # Annotations for Numba mode
     label: str = "distribution"
 
-    def __init__(self, type_, register=True):
-        super().__init__(type_, register)
+    def __init__(self, type_):
+        super().__init__(type_)
 
     def __repr__(self):
         text = "\n"
@@ -86,7 +86,7 @@ class DistributionNone(DistributionBase):
 
     def __init__(self):
         type_ = DISTRIBUTION_NONE
-        super().__init__(type_, False)
+        super().__init__(type_)
         self.ID = 0
 
 
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index c2b2fbfbe..50dc88e79 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -12,7 +12,6 @@
 from mcdc.object_.base import ObjectPolymorphic
 from mcdc.object_.element import Element
 from mcdc.object_.nuclide import Nuclide
-from mcdc.object_.simulation import simulation
 from mcdc.object_.util import ISOTOPIC_ABUNDANCE
 from mcdc.print_ import print_1d_array, print_error
 
@@ -32,17 +31,16 @@ def __init__(self, type_, name):
         super().__init__(type_)
 
         # Set name
-        if name != "":
-            self.name = name
+        if name == "":
+            self.name = "(Unnamed material)"
         else:
-            self.name = f"{self.label}_{self.child_ID}"
+            self.name = name
 
         self.fissionable = False
 
     def __repr__(self):
         text = "\n"
         text += f"{decode_type(self.type)}\n"
-        text += f"  - ID: {self.ID}\n"
         text += f"  - Name: {self.name}\n"
         text += f"  - Fissionable: {self.fissionable}\n"
         return text
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index 32b9358ab..3eb018eb2 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -29,17 +29,16 @@ def __init__(self, type_, name):
         super().__init__(type_)
 
         # Set name
-        if name != "":
-            self.name = name
+        if name == "":
+            self.name = "(Unnamed mesh)"
         else:
-            self.name = f"{self.label}_{self.child_ID}"
+            self.name = name
 
         self.N_bin = 0
 
     def __repr__(self):
         text = "\n"
         text += f"{decode_type(self.type)}\n"
-        text += f"  - ID: {self.ID}\n"
         text += f"  - Name: {self.name}\n"
         text += f"  - # of bins: {self.N_bin}\n"
         return text
diff --git a/mcdc/object_/neutron_reaction.py b/mcdc/object_/neutron_reaction.py
index 4faac2db3..c7c2d55cf 100644
--- a/mcdc/object_/neutron_reaction.py
+++ b/mcdc/object_/neutron_reaction.py
@@ -10,8 +10,6 @@
     ANGLE_ISOTROPIC,
     ANGLE_ENERGY_CORRELATED,
     ANGLE_DISTRIBUTED,
-    INTERPOLATION_LINEAR,
-    INTERPOLATION_LOG,
     NEUTRON_REACTION_CAPTURE,
     NEUTRON_REACTION_ELASTIC_SCATTERING,
     NEUTRON_REACTION_FISSION,
@@ -31,7 +29,6 @@
     DistributionTabulatedEnergyAngle,
     DistributionNBody,
 )
-from mcdc.object_.simulation import simulation
 from mcdc.print_ import print_1d_array, print_error
 
 # ======================================================================================
diff --git a/mcdc/object_/nuclide.py b/mcdc/object_/nuclide.py
index 80ca3e669..8e798e77c 100644
--- a/mcdc/object_/nuclide.py
+++ b/mcdc/object_/nuclide.py
@@ -18,7 +18,6 @@
     NeutronReactionInelasticScattering,
     set_energy_distribution,
 )
-from mcdc.object_.simulation import simulation
 from mcdc.print_ import print_1d_array, print_error
 
 # ======================================================================================
@@ -74,7 +73,7 @@ def __init__(self, nuclide_name, temperature):
         self.excitation_level = int(file["excitation_level"][()])
         file.close()
 
-    def set_neutron_data(self):
+    def set_neutron_data(self, simulation):
         nuclide_name = self.name
         temperature = self.temperature
 
@@ -161,7 +160,7 @@ def set_neutron_data(self):
         ):
             for MT in MTs[rx_name]:
                 h5_group = file[f"neutron_reactions/{rx_name}/{MT}"]
-                reaction = rx_class.from_h5_group(h5_group)
+                reaction = rx_class.from_h5_group(h5_group, simulation)
                 rx_container.append(reaction)
 
         # ==============================================================================
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 7a0e2a29e..f04bef20e 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -46,6 +46,27 @@
 
 
 class Simulation(ObjectBase):
+    """MC/DC transport simulation.
+
+    A ``Simulation`` represents a complete transport calculation. It combines
+    the physical model, source definitions, simulation settings, tally
+    definitions, and transport techniques required to execute a Monte Carlo
+    simulation.
+
+    A simulation is first constructed using Python objects. Before execution,
+    the model is compiled into an execution-ready representation optimized for
+    MC/DC's transport engine.
+
+    Notes
+    -----
+    The Python object graph is independent of the compiled representation used
+    during transport. Compilation traverses the object graph, assigns internal
+    identifiers, validates the model, and generates the data structures used by
+    the execution backend.
+    """
+
+    _next_compile_ID: int = 1
+
     # Annotations for Numba mode
     label: str = "simulation"
     non_numba: list[str] = [
@@ -54,8 +75,15 @@ class Simulation(ObjectBase):
         "bank_census",
         "bank_source",
         "bank_future",
+        "_next_compile_ID",
+        "compiled",
     ]
 
+    # Basic parameters
+    name: str
+    compile_ID: int
+    compiled: bool
+
     # Physics
     data: list[DataBase]
     distributions: list[DistributionBase]
@@ -143,8 +171,22 @@ class Simulation(ObjectBase):
     gpu_meta: GPUMeta
     source_seed: int
 
-    def __init__(self) -> None:
-        super().__init__(register=False)
+    def __init__(self, name: str = "") -> None:
+        """Create a simulation.
+
+        Parameters
+        ----------
+        name : str, optional
+            User-defined simulation name. If omitted, an unnamed simulation is
+            created.
+        """
+        super().__init__()
+
+        # Set name
+        self.name = name or "(Unnamed simulation)"
+
+        self.compile_ID = 0
+        self.compiled = False
 
         # ==============================================================================
         # Simulation objects
@@ -249,24 +291,169 @@ def __init__(self) -> None:
     # ==================================================================================
 
     def set_model(self, cells: Sequence[Cell]) -> None:
+        """Set the simulation model.
+
+        Parameters
+        ----------
+        cells : Sequence[Cell]
+            Cells that define the root universe of the model.
+
+        Notes
+        -----
+        Only the root cells are stored. Connected geometry and physics objects are
+        discovered automatically during compilation.
+        """
         self.universes[0].cells = list(cells)
+        self.compiled = False
 
     def set_sources(self, sources: Sequence[Source]) -> None:
+        """Set the simulation source definitions.
+
+        Parameters
+        ----------
+        sources : Sequence[Source]
+            Source definitions used to initialize particles.
+
+        Notes
+        -----
+        Connected distributions and supporting objects are collected during
+        compilation.
+        """
         self.sources = list(sources)
+        self.compiled = False
 
     def set_tallies(self, tallies: Sequence[Tally]) -> None:
+        """Set the simulation tally definitions.
+
+        Parameters
+        ----------
+        tallies : Sequence[Tally]
+            Tallies used to score transport quantities.
+
+        Notes
+        -----
+        Connected meshes, filters, and other referenced objects are collected
+        during compilation.
+        """
         self.tallies = list(tallies)
+        self.compiled = False
 
     # ==================================================================================
     # Operations
     # ==================================================================================
 
-    def visualize_model(self, vis_type, x, y, z, pixels, colors, time, save_as) -> None:
+    def compile(self) -> None:
+        """Compile the simulation.
+
+        Compilation validates the simulation, discovers all connected objects,
+        assigns internal identifiers, and generates the execution-ready data
+        structures used by the transport engine.
+
+        Notes
+        -----
+        Compilation does not perform particle transport. It only prepares the
+        simulation for execution or other operations that require the compiled
+        representation.
+        """
+        from mcdc.main import compile_simulation
+
+        compile_ID = type(self)._next_compile_ID
+
+        try:
+            compile_simulation(self, compile_ID)
+        except Exception:
+            self.compiled = False
+            raise
+
+        self.compile_ID = compile_ID
+        type(self)._next_compile_ID += 1
+        self.compiled = True
+
+    def visualize_model(
+        self,
+        vis_plane,
+        x,
+        y,
+        z,
+        pixels,
+        colors,
+        time,
+        save_as,
+    ) -> None:
+        """Visualize the simulation model.
+
+        Generate two-dimensional slices of the simulation geometry at one or more
+        times. If necessary, the simulation is compiled automatically before
+        visualization.
+
+        Parameters
+        ----------
+        vis_plane : {'xy', 'xz', 'yz', 'yx', 'zx', 'zy'}
+            Coordinate plane to visualize.
+
+        x : float or array_like
+            Plane x-coordinate for ``'yz'`` visualization, or x-axis range for
+            ``'xy'`` and ``'xz'`` visualizations.
+
+        y : float or array_like
+            Plane y-coordinate for ``'xz'`` visualization, or y-axis range for
+            ``'xy'`` and ``'yz'`` visualizations.
+
+        z : float or array_like
+            Plane z-coordinate for ``'xy'`` visualization, or z-axis range for
+            ``'xz'`` and ``'yz'`` visualizations.
+
+        pixels : array_like
+            Number of pixels along the two visualization axes.
+
+        colors : array_like
+            Sequence of ``(material, color)`` pairs used to render the model.
+
+        time : float or array_like
+            Time or times at which geometry snapshots are generated.
+
+        save_as : str, optional
+            Output filename. If omitted, the visualization is displayed without
+            saving.
+
+        Notes
+        -----
+        Visualization uses the compiled model representation but does not perform
+        particle transport or modify the compiled simulation state.
+        """
+        if not self.compiled:
+            self.compile()
+
         from mcdc.visualize import visualize_model
 
-        visualize_model(self, vis_type, x, y, z, pixels, colors, time, save_as)
+        visualize_model(self, vis_plane, x, y, z, pixels, colors, time, save_as)
 
     def run(self) -> None:
-        from mcdc.main import run
-
-        run(self)
+        """Execute the transport simulation.
+
+        If necessary, the simulation is compiled automatically before execution.
+
+        Notes
+        -----
+        Compilation is invalidated after execution because transport updates the
+        internal simulation state. If the Python model is modified directly without
+        using the public simulation interface, users are responsible for ensuring
+        the simulation is recompiled before subsequent operations.
+        """
+        from mcdc.main import run_simulation
+
+        if not self.compiled:
+            self.compile()
+
+        try:
+            run_simulation(self)
+        finally:
+            self.compiled = False
+
+    def __repr__(self) -> str:
+        return (
+            f"{self.__class__.__name__}("
+            f"name={self.name!r}, "
+            f"compiled={self.compiled}, "
+            f"compile_ID={self.compile_ID})"
+        )
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 3f29677c4..6570a97ab 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -19,7 +19,6 @@
 )
 from mcdc.object_.base import ObjectNonSingleton
 from mcdc.object_.distribution import DistributionTabulated, DistributionPMF
-from mcdc.object_.simulation import simulation
 from mcdc.object_.util import move_object
 from mcdc.print_ import print_error
 
@@ -230,10 +229,10 @@ def __init__(
         super().__init__()
 
         # Set name
-        if name != "":
-            self.name = name
+        if name == "":
+            self.name = "(Unnamed source)"
         else:
-            self.name = f"{self.label}_{self.ID}"
+            self.name = name
 
         # ==============================================================================
         # Default attributes
@@ -361,7 +360,6 @@ def __init__(
     def __repr__(self):
         text = "\n"
         text += f"Source\n"
-        text += f"  - ID: {self.ID}\n"
         text += f"  - Name: {self.name}\n"
         text += f"  - Particle: {decode_particle_type(self.particle_type)}\n"
         text += f"  - Probability: {self.probability * 100}%\n"
@@ -378,16 +376,12 @@ def __repr__(self):
             text += f"  - Direction [ux, uy, yz]: {self.direction}\n"
         elif self.white_direction:
             text += f"  - Isotropic halfspace: {self.direction}\n"
-        if simulation.materials[0].label == "multigroup_material":
-            if self.mono_energetic:
-                text += f"  - Energy group: {self.energy_group} \n"
-            else:
-                text += f"  - Energy group: {distribution.decode_type(self.energy_group_pmf.type)} [ID: {self.energy_group_pmf.ID}]\n"
+        if self.mono_energetic:
+            text += (
+                f"  - Energy / energy group: {self.energy} eV / {self.energy_group}\n"
+            )
         else:
-            if self.mono_energetic:
-                text += f"  - Energy: {self.energy} eV\n"
-            else:
-                text += f"  - Energy: {distribution.decode_type(self.energy_pdf)} [ID: {self.energy_pdf.ID}]\n"
+            text += f"  - Energy / energy group: PDF / PMF\n"
         if self.discrete_time:
             text += f"  - Time: {self.time} s\n"
         else:
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index ececf78be..09a863763 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -139,10 +139,12 @@ def __init__(self, type_, name, boundary_condition):
 
         # Type and name
         self.type = type_
-        if name != "":
-            self.name = name
+
+        # Set name
+        if name == "":
+            self.name = "(Unnamed surface)"
         else:
-            self.name = f"{self.label}_{self.ID}"
+            self.name = name
 
         # Boundary condition
         if boundary_condition == "none":
@@ -201,7 +203,6 @@ def __repr__(self):
         """
         text = "\n"
         text += f"{decode_type(self.type)}\n"
-        text += f"  - ID: {self.ID}\n"
         text += f"  - Name: {self.name}\n"
         text += f"  - Boundary condition: {decode_BC_type(self.boundary_condition)}\n"
 
@@ -298,7 +299,12 @@ def __repr__(self):
     # ==================================================================================
 
     @classmethod
-    def PlaneX(cls, name: str = "", x: float = 0.0, boundary_condition: str = "none"):
+    def PlaneX(
+        cls,
+        name: str = "",
+        x: float = 0.0,
+        boundary_condition: str = "none",
+    ):
         """
         Create a plane perpendicular to +x at x = constant.
 
@@ -330,7 +336,12 @@ def PlaneX(cls, name: str = "", x: float = 0.0, boundary_condition: str = "none"
         return surface
 
     @classmethod
-    def PlaneY(cls, name: str = "", y: float = 0.0, boundary_condition: str = "none"):
+    def PlaneY(
+        cls,
+        name: str = "",
+        y: float = 0.0,
+        boundary_condition: str = "none",
+    ):
         """
         Create a plane perpendicular to +y at y = constant.
 
@@ -362,7 +373,12 @@ def PlaneY(cls, name: str = "", y: float = 0.0, boundary_condition: str = "none"
         return surface
 
     @classmethod
-    def PlaneZ(cls, name: str = "", z: float = 0.0, boundary_condition: str = "none"):
+    def PlaneZ(
+        cls,
+        name: str = "",
+        z: float = 0.0,
+        boundary_condition: str = "none",
+    ):
         """
         Create a plane perpendicular to +z at z = constant.
 
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 107f95157..8d357a350 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -44,7 +44,6 @@
 )
 from mcdc.object_.mesh import MeshBase, MeshStructured, MeshUniform
 from mcdc.object_.base import ObjectPolymorphic
-from mcdc.object_.simulation import simulation
 from mcdc.print_ import print_1d_array, print_error
 
 
@@ -152,10 +151,10 @@ def __init__(
         spatial_shape: tuple[int, ...] | NoneType = None,
     ):
         # Set name
-        if name != "":
-            self.name = name
+        if name == "":
+            self.name = "(Unnamed tally)"
         else:
-            self.name = f"{self.label}_{self.child_ID}"
+            self.name = name
 
         # Set scores
         self.scores = []
@@ -274,7 +273,6 @@ def _phasespace_filter_text(self):
     def __repr__(self):
         text = "\n"
         text += f"{decode_type(self.type)}\n"
-        text += f"  - ID: {self.ID}\n"
         text += f"  - Name: {self.name}\n"
         return text
 
@@ -498,7 +496,7 @@ def __repr__(self):
         if isinstance(self.cell, Cell):
             text += f"  - Cell filter: {self.cell.name}\n"
         if isinstance(self.mesh, MeshBase):
-            text += f"  - Mesh: {mesh_module.decode_type(self.mesh.type)} (ID {self.mesh.ID})\n"
+            text += f"  - Mesh: {mesh_module.decode_type(self.mesh.type)}\n"
         text += super()._phasespace_filter_text()
         text += f"  - Bin shape [mu, azi, energy, time, score]: {self.bin_shape} \n"
         return text
@@ -600,16 +598,21 @@ def __init__(
             self.mesh_stride_x = N_score * mesh.Nz * mesh.Ny
 
         # Attach to all cells if cell filter is not specified
+        # TODO
+        """
         if cell is None:
             for cell_ in simulation.cells:
                 cell_.tracklength_tallies.append(self)
+        """
 
     def __repr__(self):
+        from mcdc.object_.cell import Cell
+
         text = super().__repr__()
         if isinstance(self.cell, Cell):
             text += f"  - Cell filter: {self.cell.name}\n"
         if isinstance(self.mesh, MeshBase):
-            text += f"  - Mesh: {mesh_module.decode_type(self.mesh.type)} (ID {self.mesh.ID})\n"
+            text += f"  - Mesh: {mesh_module.decode_type(self.mesh.type)}\n"
         text += super()._phasespace_filter_text()
         text += f"  - Bin shape [mu, azi, energy, time, score]: {self.bin_shape} \n"
         return text
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index ad477525b..a14942fe4 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -55,16 +55,16 @@ class Universe(ObjectNonSingleton):
     def __init__(self, name: str = "", cells: list[Cell] = [], root: bool = False):
         # Custom treatment for root universe
         if root:
-            super().__init__(register=False)
+            super().__init__()
             self.ID = 0
         else:
             super().__init__()
 
         # Set name
-        if name != "":
-            self.name = name
+        if name == "":
+            self.name = "(Unnamed universe)"
         else:
-            self.name = f"{self.label}_{self.ID}"
+            self.name = name
 
         self.cells = cells
 
@@ -138,10 +138,10 @@ def __init__(
         super().__init__()
 
         # Set name
-        if name != "":
-            self.name = name
+        if name == "":
+            self.name = "(Unnamed lattice)"
         else:
-            self.name = f"{self.label}_{self.ID}"
+            self.name = name
 
         # Default uniform grids
         self.x0 = -INF

From 1f7f7967fec550d451b9ad3808169d2c14731f37 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 13 Jul 2026 10:53:25 +0700
Subject: [PATCH 005/202] remove objectSingleton

---
 mcdc/object_/base.py      |  5 -----
 mcdc/object_/gpu_tools.py |  4 ++--
 mcdc/object_/particle.py  |  4 ++--
 mcdc/object_/settings.py  |  4 ++--
 mcdc/object_/technique.py | 12 ++++++------
 5 files changed, 12 insertions(+), 17 deletions(-)

diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index 3e249ca10..ecd1327cc 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -19,11 +19,6 @@ def __setattr__(self, key, value):
         super().__setattr__(key, value)
 
 
-class ObjectSingleton(ObjectBase):
-    def __init__(self):
-        super().__init__()
-
-
 class ObjectNonSingleton(ObjectBase):
     ID: int
 
diff --git a/mcdc/object_/gpu_tools.py b/mcdc/object_/gpu_tools.py
index b4d4965a3..f5d077a06 100644
--- a/mcdc/object_/gpu_tools.py
+++ b/mcdc/object_/gpu_tools.py
@@ -3,11 +3,11 @@
 
 ####
 
-from mcdc.object_.base import ObjectSingleton
+from mcdc.object_.base import ObjectBase
 
 
 @dataclass
-class GPUMeta(ObjectSingleton):
+class GPUMeta(ObjectBase):
     # Annotations for Numba mode
     label: str = "gpu_meta"
     #
diff --git a/mcdc/object_/particle.py b/mcdc/object_/particle.py
index 3d9fa43f5..624277b9e 100644
--- a/mcdc/object_/particle.py
+++ b/mcdc/object_/particle.py
@@ -8,7 +8,7 @@
 ####
 
 from mcdc.constant import PARTICLE_NEUTRON
-from mcdc.object_.base import ObjectBase, ObjectSingleton
+from mcdc.object_.base import ObjectBase, ObjectBase
 
 
 @dataclass
@@ -45,7 +45,7 @@ class Particle(ParticleData):
     event: int = -1
 
 
-class ParticleBank(ObjectSingleton):
+class ParticleBank(ObjectBase):
     label: str = "particle_bank"
     non_numba: list[str] = ["particles"]
     particles: list[ParticleData] = []
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index 60a28d896..1d8e66a20 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -9,7 +9,7 @@
 ####
 
 from mcdc.constant import *
-from mcdc.object_.base import ObjectSingleton
+from mcdc.object_.base import ObjectBase
 from mcdc.object_.util import is_sorted
 from mcdc.print_ import print_error
 
@@ -19,7 +19,7 @@
 
 
 @dataclass
-class Settings(ObjectSingleton):
+class Settings(ObjectBase):
     # Annotations for Numba mode
     label: str = "settings"
 
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index 271a2f31d..d26e9dda5 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -1,7 +1,7 @@
 import numpy as np
 
 from mcdc.constant import INF
-from mcdc.object_.base import ObjectSingleton
+from mcdc.object_.base import ObjectBase
 from mcdc.object_.mesh import MeshBase, MeshUniform
 from mcdc.print_ import print_error
 from numpy.typing import NDArray
@@ -12,7 +12,7 @@
 # ======================================================================================
 
 
-class ImplicitCapture(ObjectSingleton):
+class ImplicitCapture(ObjectBase):
     # Annotations for Numba mode
     label: str = "implicit_capture"
     active: bool
@@ -29,7 +29,7 @@ def __call__(self, active: bool = True):
 # ======================================================================================
 
 
-class WeightedEmission(ObjectSingleton):
+class WeightedEmission(ObjectBase):
     # Annotations for Numba mode
     label: str = "weighted_emission"
 
@@ -50,7 +50,7 @@ def __call__(self, active: bool = True, weight_target: float = 1.0):
 # ======================================================================================
 
 
-class GlobalWeightRoulette(ObjectSingleton):
+class GlobalWeightRoulette(ObjectBase):
     # Annotations for Numba mode
     label: str = "global_weight_roulette"
 
@@ -78,7 +78,7 @@ def __call__(self, weight_threshold: float = 0.0, weight_target: float = 1.0):
 # ======================================================================================
 
 
-class WeightWindows(ObjectSingleton):
+class WeightWindows(ObjectBase):
     label: str = "weight_windows"
 
     active: bool
@@ -180,7 +180,7 @@ def __call__(self, weight_windows, mesh=None, energy=None):
 # ======================================================================================
 
 
-class PopulationControl(ObjectSingleton):
+class PopulationControl(ObjectBase):
     # Annotations for Numba mode
     label: str = "population_control"
     active: bool

From 7bee17e7ccc70a38fee2b0a2bcf7a9fab157ed4a Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 13 Jul 2026 11:19:50 +0700
Subject: [PATCH 006/202] Update object base

---
 mcdc/object_/base.py | 66 +++++++++++++++++++++++++++++++++++++-------
 1 file changed, 56 insertions(+), 10 deletions(-)

diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index ecd1327cc..b9f313ede 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -1,42 +1,88 @@
 from mcdc.print_ import print_error
 
-# ======================================================================================
-# Object base classes
-# ======================================================================================
 
+class MCDCBase:
+    """Base class for all Python-side MC/DC objects.
+
+    ``MCDCBase`` provides functionality shared by framework objects,
+    including runtime type checking and metadata used during preparation
+    and execution.
+
+    Notes
+    -----
+    This class represents the root of the Python object hierarchy. It does
+    not correspond directly to objects stored in the compiled simulation.
+    """
 
-class ObjectBase:
     def __init__(self):
-        if "non_numba" in dir(self):
+        """Initialize common object metadata."""
+        if hasattr(self, "non_numba"):
             self.non_numba += ["non_numba", "label"]
         else:
             self.non_numba = ["non_numba", "label"]
 
     def __setattr__(self, key, value):
+        """Assign an attribute with runtime type checking.
+
+        Attribute assignments are validated against the class type
+        annotations before being stored.
+        """
         hints = getattr(self.__class__, "__annotations__", {})
         if key in hints and not check_type(value, hints[key], self.__class__, self):
             print_error(f"{key} must be {hints[key]!r}, got {value!r}")
         super().__setattr__(key, value)
 
 
-class ObjectNonSingleton(ObjectBase):
+class MCDCObject(MCDCBase):
+    """Base class for compiled MC/DC objects.
+
+    ``MCDCObject`` represents objects that are collected during simulation
+    compilation and assigned unique identifiers for the compiled model.
+
+    Notes
+    -----
+    During compilation, each object is assigned an object identifier and the
+    identifier of the compilation in which it was collected.
+    """
+
     ID: int
+    compile_ID: int
 
     def __init__(self):
+        """Initialize compilation metadata."""
         self.ID = -1
+        self.compile_ID = 0
         super().__init__()
 
-        if "non_numba" in dir(self):
-            self.non_numba += ["ID"]
+        if hasattr(self, "non_numba"):
+            self.non_numba += ["ID", "compile_ID"]
         else:
-            self.non_numba = ["ID"]
+            self.non_numba = ["ID", "compile_ID"]
+
+
+class MCDCPolymorphic(MCDCObject):
+    """Base class for polymorphic compiled objects.
 
+    Polymorphic objects belong to families that share a common compiled
+    representation while supporting multiple concrete object types.
+
+    Notes
+    -----
+    In addition to the object identifier, polymorphic objects receive a
+    child identifier that is unique within their polymorphic family.
+    """
 
-class ObjectPolymorphic(ObjectNonSingleton):
     child_ID: int
     type: int
 
     def __init__(self, type_):
+        """Initialize polymorphic compilation metadata.
+
+        Parameters
+        ----------
+        type_ : int
+            Integer identifier specifying the concrete polymorphic type.
+        """
         self.child_ID = -1
         self.type = type_
         super().__init__()

From d4bbdcfbe547f741aa6534a4bdb83f266d4c5405 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 13 Jul 2026 11:26:11 +0700
Subject: [PATCH 007/202] Update object base

---
 mcdc/code_factory/numba_objects_generator.py | 40 ++++++++++----------
 mcdc/object_/base.py                         |  2 +-
 mcdc/object_/cell.py                         |  6 +--
 mcdc/object_/data.py                         |  4 +-
 mcdc/object_/distribution.py                 |  4 +-
 mcdc/object_/electron_reaction.py            |  4 +-
 mcdc/object_/element.py                      |  4 +-
 mcdc/object_/gpu_tools.py                    |  4 +-
 mcdc/object_/material.py                     |  4 +-
 mcdc/object_/mesh.py                         |  4 +-
 mcdc/object_/neutron_reaction.py             |  4 +-
 mcdc/object_/nuclide.py                      |  4 +-
 mcdc/object_/particle.py                     |  8 ++--
 mcdc/object_/settings.py                     |  4 +-
 mcdc/object_/simulation.py                   |  4 +-
 mcdc/object_/source.py                       |  4 +-
 mcdc/object_/surface.py                      |  4 +-
 mcdc/object_/tally.py                        |  4 +-
 mcdc/object_/technique.py                    | 12 +++---
 mcdc/object_/universe.py                     |  6 +--
 20 files changed, 65 insertions(+), 65 deletions(-)

diff --git a/mcdc/code_factory/numba_objects_generator.py b/mcdc/code_factory/numba_objects_generator.py
index c466b92d6..b7fee5bd0 100644
--- a/mcdc/code_factory/numba_objects_generator.py
+++ b/mcdc/code_factory/numba_objects_generator.py
@@ -20,9 +20,9 @@
 import mcdc.object_.base as base
 
 from mcdc.object_.base import (
-    ObjectBase,
-    ObjectNonSingleton,
-    ObjectPolymorphic,
+    MCDCBase,
+    MCDCObject,
+    MCDCPolymorphic,
     ObjectSingleton,
 )
 from mcdc.object_.particle import Particle, ParticleBank, ParticleData
@@ -52,7 +52,7 @@
 base_classes = [
     getattr(base, x)
     for x in dir(base)
-    if isinstance(getattr(base, x), type) and issubclass(getattr(base, x), ObjectBase)
+    if isinstance(getattr(base, x), type) and issubclass(getattr(base, x), MCDCBase)
 ]
 
 all_classes = [ParticleData, Particle]
@@ -67,7 +67,7 @@
         item = getattr(file, item_name)
         if (
             isinstance(item, type)
-            and issubclass(item, ObjectBase)
+            and issubclass(item, MCDCBase)
             and item not in all_classes
         ):
             all_classes.append(item)
@@ -110,7 +110,7 @@ def generate_numba_objects(simulation):
         annotations[mcdc_class.label] = {}
         structures[mcdc_class.label] = []
         accessor_targets[mcdc_class.label] = []
-        if issubclass(mcdc_class, ObjectNonSingleton):
+        if issubclass(mcdc_class, MCDCObject):
             records[mcdc_class.label] = []
         else:
             records[mcdc_class.label] = {}
@@ -140,7 +140,7 @@ def generate_numba_objects(simulation):
             classes.append(item)
 
         # If polymorphic, don't include the polymorphic base
-        if issubclass(mcdc_class, ObjectPolymorphic):
+        if issubclass(mcdc_class, MCDCPolymorphic):
             classes = [mcdc_class]
 
         # Get the annotations
@@ -205,10 +205,10 @@ def generate_numba_objects(simulation):
 
     # Add ID for non-singleton
     for class_ in mcdc_classes:
-        if issubclass(class_, ObjectNonSingleton):
+        if issubclass(class_, MCDCObject):
             structures[class_.label].append(("ID", type_map[int]))
         # Set parent and child ID and type if polymorphic
-        if issubclass(class_, ObjectPolymorphic):
+        if issubclass(class_, MCDCPolymorphic):
             if class_.__name__[-4:] == "Base" or class_.__name__ == "Tally":
                 structures[class_.label].append(("child_type", type_map[int]))
                 structures[class_.label].append(("child_ID", type_map[int]))
@@ -241,7 +241,7 @@ def generate_numba_objects(simulation):
         if (
             not x.startswith("__")
             and (
-                isinstance(getattr(simulation, x), ObjectBase)
+                isinstance(getattr(simulation, x), MCDCBase)
                 or not callable(getattr(simulation, x))
             )
             and x not in simulation.non_numba
@@ -515,10 +515,10 @@ def set_structure(label, structures, accessor_targets, annotations):
 
         # MC/DC class
         def non_polymorphic(x):
-            # Only treat real classes that inherit from ObjectNonSingleton
+            # Only treat real classes that inherit from MCDCObject
             return (
                 isinstance(x, type)
-                and issubclass(x, ObjectNonSingleton)
+                and issubclass(x, MCDCObject)
                 and x not in polymorphic_bases
             )
 
@@ -575,7 +575,7 @@ def set_object(
         class_ = object_.__class__
 
     # Set the parent first if polymorphics
-    if isinstance(object_, ObjectPolymorphic) and class_ not in polymorphic_bases:
+    if isinstance(object_, MCDCPolymorphic) and class_ not in polymorphic_bases:
         for parent_class in polymorphic_bases:
             if issubclass(class_, parent_class):
                 set_object(
@@ -636,9 +636,9 @@ def set_object(
             data["size"] += len(attribute_flatten)
 
         # Non-singleton object
-        elif isinstance(attribute, ObjectNonSingleton):
+        elif isinstance(attribute, MCDCObject):
             if (
-                not isinstance(attribute, ObjectPolymorphic)
+                not isinstance(attribute, MCDCPolymorphic)
                 or annotation[attribute_name] in polymorphic_bases
             ):
                 record[f"{attribute_name}_ID"] = attribute.ID
@@ -653,7 +653,7 @@ def set_object(
             attribute_flatten = list(flatten(attribute))
             singular_name = plural_to_singular(attribute_name)
 
-            if not issubclass(inner_type, ObjectNonSingleton):
+            if not issubclass(inner_type, MCDCObject):
                 print_error(
                     f"[ERROR] Get a list of non-object for {attribute_name}: {attribute}"
                 )
@@ -662,7 +662,7 @@ def set_object(
             record[f"{singular_name}_IDs_offset"] = data["size"]
             if set_data:
                 if (
-                    not issubclass(inner_type, ObjectPolymorphic)
+                    not issubclass(inner_type, MCDCPolymorphic)
                     or inner_type in polymorphic_bases
                 ):
                     data["array"][
@@ -679,8 +679,8 @@ def set_object(
         return
 
     # Set ID of non-singleton
-    if isinstance(object_, ObjectNonSingleton):
-        if not isinstance(object_, ObjectPolymorphic):
+    if isinstance(object_, MCDCObject):
+        if not isinstance(object_, MCDCPolymorphic):
             record["ID"] = object_.ID
 
         # Set parent and child ID and type if polymorphic
@@ -714,7 +714,7 @@ def set_object(
     # Register the record
     if isinstance(object_, ObjectSingleton):
         records[class_.label] = record
-    elif isinstance(object_, ObjectNonSingleton):
+    elif isinstance(object_, MCDCObject):
         records[class_.label].append(record)
 
 
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index b9f313ede..2629b30eb 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -147,7 +147,7 @@ def register_object(object_):
         print_error(f"Unidentified object list for object {object_}")
 
     object_.ID = len(object_list)
-    if isinstance(object_, ObjectPolymorphic):
+    if isinstance(object_, MCDCPolymorphic):
         object_.child_ID = sum([x.type == object_.type for x in object_list])
     object_list.append(object_)
 
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index d28d336ff..6f637d8a4 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -28,7 +28,7 @@
     FILL_UNIVERSE,
     PI,
 )
-from mcdc.object_.base import ObjectNonSingleton
+from mcdc.object_.base import MCDCObject
 from mcdc.object_.material import MaterialBase
 from mcdc.object_.tally import TallyCollision, TallyTracklength
 from mcdc.object_.universe import Universe, Lattice
@@ -39,7 +39,7 @@
 # ======================================================================================
 
 
-class Region(ObjectNonSingleton):
+class Region(MCDCObject):
     type: str
     A: Surface | Region | NoneType
     B: Region | int | NoneType
@@ -74,7 +74,7 @@ def __repr__(self):
 # ======================================================================================
 
 
-class Cell(ObjectNonSingleton):
+class Cell(MCDCObject):
     """
     Define a cell from a region and a fill.
 
diff --git a/mcdc/object_/data.py b/mcdc/object_/data.py
index c8ab82821..404c617f2 100644
--- a/mcdc/object_/data.py
+++ b/mcdc/object_/data.py
@@ -17,7 +17,7 @@
     INTERPOLATION_SEMILOGY,
     INTERPOLATION_LOG,
 )
-from mcdc.object_.base import ObjectPolymorphic
+from mcdc.object_.base import MCDCPolymorphic
 from mcdc.print_ import print_1d_array, print_error
 
 # ======================================================================================
@@ -25,7 +25,7 @@
 # ======================================================================================
 
 
-class DataBase(ObjectPolymorphic):
+class DataBase(MCDCPolymorphic):
     # Annotations for Numba mode
     label: str = "data"
 
diff --git a/mcdc/object_/distribution.py b/mcdc/object_/distribution.py
index f732d2ffe..936f7eedb 100644
--- a/mcdc/object_/distribution.py
+++ b/mcdc/object_/distribution.py
@@ -20,7 +20,7 @@
     INTERPOLATION_HISTOGRAM,
     INTERPOLATION_LINEAR,
 )
-from mcdc.object_.base import ObjectPolymorphic
+from mcdc.object_.base import MCDCPolymorphic
 from mcdc.object_.data import DataTable
 from mcdc.object_.util import (
     cdf_from_pdf,
@@ -35,7 +35,7 @@
 # ======================================================================================
 
 
-class DistributionBase(ObjectPolymorphic):
+class DistributionBase(MCDCPolymorphic):
     # Annotations for Numba mode
     label: str = "distribution"
 
diff --git a/mcdc/object_/electron_reaction.py b/mcdc/object_/electron_reaction.py
index 441ebb189..452dfa3c4 100644
--- a/mcdc/object_/electron_reaction.py
+++ b/mcdc/object_/electron_reaction.py
@@ -15,7 +15,7 @@
     REFERENCE_FRAME_COM,
     REFERENCE_FRAME_LAB,
 )
-from mcdc.object_.base import ObjectPolymorphic
+from mcdc.object_.base import MCDCPolymorphic
 from mcdc.object_.data import DataBase, DataTable
 from mcdc.object_.distribution import DistributionBase, DistributionMultiTable
 from mcdc.print_ import print_1d_array
@@ -25,7 +25,7 @@
 # ======================================================================================
 
 
-class ElectronReactionBase(ObjectPolymorphic):
+class ElectronReactionBase(MCDCPolymorphic):
     # Annotations for Numba mode
     label: str = "electron_reaction"
     #
diff --git a/mcdc/object_/element.py b/mcdc/object_/element.py
index acc1270a0..e3d317408 100644
--- a/mcdc/object_/element.py
+++ b/mcdc/object_/element.py
@@ -7,7 +7,7 @@
 
 ####
 
-from mcdc.object_.base import ObjectNonSingleton
+from mcdc.object_.base import MCDCObject
 from mcdc.object_.electron_reaction import (
     ElectronReactionBremsstrahlung,
     ElectronReactionElasticScattering,
@@ -16,7 +16,7 @@
 )
 
 
-class Element(ObjectNonSingleton):
+class Element(MCDCObject):
     # Annotations for Numba mode
     label: str = "element"
     #
diff --git a/mcdc/object_/gpu_tools.py b/mcdc/object_/gpu_tools.py
index f5d077a06..6715367ee 100644
--- a/mcdc/object_/gpu_tools.py
+++ b/mcdc/object_/gpu_tools.py
@@ -3,11 +3,11 @@
 
 ####
 
-from mcdc.object_.base import ObjectBase
+from mcdc.object_.base import MCDCBase
 
 
 @dataclass
-class GPUMeta(ObjectBase):
+class GPUMeta(MCDCBase):
     # Annotations for Numba mode
     label: str = "gpu_meta"
     #
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 50dc88e79..72e2ab0a6 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -9,7 +9,7 @@
 ####
 
 from mcdc.constant import MATERIAL, MATERIAL_MG
-from mcdc.object_.base import ObjectPolymorphic
+from mcdc.object_.base import MCDCPolymorphic
 from mcdc.object_.element import Element
 from mcdc.object_.nuclide import Nuclide
 from mcdc.object_.util import ISOTOPIC_ABUNDANCE
@@ -20,7 +20,7 @@
 # ======================================================================================
 
 
-class MaterialBase(ObjectPolymorphic):
+class MaterialBase(MCDCPolymorphic):
     # Annotations for Numba mode
     label: str = "material"
     #
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index 3eb018eb2..1d68054ee 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -7,7 +7,7 @@
 ####
 
 from mcdc.constant import INF, MESH_STRUCTURED, MESH_UNIFORM
-from mcdc.object_.base import ObjectPolymorphic
+from mcdc.object_.base import MCDCPolymorphic
 from mcdc.print_ import print_1d_array
 
 # ======================================================================================
@@ -15,7 +15,7 @@
 # ======================================================================================
 
 
-class MeshBase(ObjectPolymorphic):
+class MeshBase(MCDCPolymorphic):
     # Annotations for Numba mode
     label: str = "mesh"
     #
diff --git a/mcdc/object_/neutron_reaction.py b/mcdc/object_/neutron_reaction.py
index c7c2d55cf..54313009d 100644
--- a/mcdc/object_/neutron_reaction.py
+++ b/mcdc/object_/neutron_reaction.py
@@ -17,7 +17,7 @@
     REFERENCE_FRAME_COM,
     REFERENCE_FRAME_LAB,
 )
-from mcdc.object_.base import ObjectPolymorphic
+from mcdc.object_.base import MCDCPolymorphic
 from mcdc.object_.data import encode_interpolation
 from mcdc.object_.distribution import (
     DistributionBase,
@@ -36,7 +36,7 @@
 # ======================================================================================
 
 
-class NeutronReactionBase(ObjectPolymorphic):
+class NeutronReactionBase(MCDCPolymorphic):
     # Annotations for Numba mode
     label: str = "neutron_reaction"
     #
diff --git a/mcdc/object_/nuclide.py b/mcdc/object_/nuclide.py
index 8e798e77c..72a9e195f 100644
--- a/mcdc/object_/nuclide.py
+++ b/mcdc/object_/nuclide.py
@@ -8,7 +8,7 @@
 ####
 
 from mcdc.constant import INTERPOLATION_LINEAR
-from mcdc.object_.base import ObjectNonSingleton
+from mcdc.object_.base import MCDCObject
 from mcdc.object_.data import DataBase, DataPolynomial, DataTable
 from mcdc.object_.distribution import DistributionBase
 from mcdc.object_.neutron_reaction import (
@@ -25,7 +25,7 @@
 # ======================================================================================
 
 
-class Nuclide(ObjectNonSingleton):
+class Nuclide(MCDCObject):
     # Annotations for Numba mode
     label: str = "nuclide"
     #
diff --git a/mcdc/object_/particle.py b/mcdc/object_/particle.py
index 624277b9e..477ac7f7f 100644
--- a/mcdc/object_/particle.py
+++ b/mcdc/object_/particle.py
@@ -8,11 +8,11 @@
 ####
 
 from mcdc.constant import PARTICLE_NEUTRON
-from mcdc.object_.base import ObjectBase, ObjectBase
+from mcdc.object_.base import MCDCBase, MCDCBase
 
 
 @dataclass
-class ParticleData(ObjectBase):
+class ParticleData(MCDCBase):
     label: str = "particle_data"
     x: float = 0.0
     y: float = 0.0
@@ -29,7 +29,7 @@ class ParticleData(ObjectBase):
 
 
 @dataclass
-class CollisionData(ObjectBase):
+class CollisionData(MCDCBase):
     label: str = "collision_data"
     energy_deposition: float = 0.0
 
@@ -45,7 +45,7 @@ class Particle(ParticleData):
     event: int = -1
 
 
-class ParticleBank(ObjectBase):
+class ParticleBank(MCDCBase):
     label: str = "particle_bank"
     non_numba: list[str] = ["particles"]
     particles: list[ParticleData] = []
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index 1d8e66a20..869968e92 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -9,7 +9,7 @@
 ####
 
 from mcdc.constant import *
-from mcdc.object_.base import ObjectBase
+from mcdc.object_.base import MCDCBase
 from mcdc.object_.util import is_sorted
 from mcdc.print_ import print_error
 
@@ -19,7 +19,7 @@
 
 
 @dataclass
-class Settings(ObjectBase):
+class Settings(MCDCBase):
     # Annotations for Numba mode
     label: str = "settings"
 
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index f04bef20e..783beb6d8 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -23,7 +23,7 @@
 
 ####
 
-from mcdc.object_.base import ObjectBase
+from mcdc.object_.base import MCDCBase
 from mcdc.object_.data import DataBase, DataNone
 from mcdc.object_.distribution import DistributionBase, DistributionNone
 from mcdc.object_.gpu_tools import GPUMeta
@@ -45,7 +45,7 @@
 # ======================================================================================
 
 
-class Simulation(ObjectBase):
+class Simulation(MCDCBase):
     """MC/DC transport simulation.
 
     A ``Simulation`` represents a complete transport calculation. It combines
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 6570a97ab..47ba9370b 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -17,7 +17,7 @@
     INF,
     PI,
 )
-from mcdc.object_.base import ObjectNonSingleton
+from mcdc.object_.base import MCDCObject
 from mcdc.object_.distribution import DistributionTabulated, DistributionPMF
 from mcdc.object_.util import move_object
 from mcdc.print_ import print_error
@@ -37,7 +37,7 @@ def decode_particle_type(type_):
 # ======================================================================================
 
 
-class Source(ObjectNonSingleton):
+class Source(MCDCObject):
     """
     Define a particle source.
 
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 09a863763..edb1886a8 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -29,7 +29,7 @@
     SURFACE_TORUS_Z,
     SURFACE_TORUS,
 )
-from mcdc.object_.base import ObjectNonSingleton
+from mcdc.object_.base import MCDCObject
 from mcdc.object_.cell import Region
 from mcdc.object_.tally import TallySurfaceCrossing
 from mcdc.object_.util import move_object
@@ -40,7 +40,7 @@
 # ======================================================================================
 
 
-class Surface(ObjectNonSingleton):
+class Surface(MCDCObject):
     """
     Geometric surface primitive with optional boundary condition and motion.
 
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 8d357a350..5ec21df91 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -43,11 +43,11 @@
     TALLY_TRACKLENGTH,
 )
 from mcdc.object_.mesh import MeshBase, MeshStructured, MeshUniform
-from mcdc.object_.base import ObjectPolymorphic
+from mcdc.object_.base import MCDCPolymorphic
 from mcdc.print_ import print_1d_array, print_error
 
 
-class Tally(ObjectPolymorphic):
+class Tally(MCDCPolymorphic):
     # Annotations for Numba mode
     label: str = "tally"
 
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index d26e9dda5..a54e60806 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -1,7 +1,7 @@
 import numpy as np
 
 from mcdc.constant import INF
-from mcdc.object_.base import ObjectBase
+from mcdc.object_.base import MCDCBase
 from mcdc.object_.mesh import MeshBase, MeshUniform
 from mcdc.print_ import print_error
 from numpy.typing import NDArray
@@ -12,7 +12,7 @@
 # ======================================================================================
 
 
-class ImplicitCapture(ObjectBase):
+class ImplicitCapture(MCDCBase):
     # Annotations for Numba mode
     label: str = "implicit_capture"
     active: bool
@@ -29,7 +29,7 @@ def __call__(self, active: bool = True):
 # ======================================================================================
 
 
-class WeightedEmission(ObjectBase):
+class WeightedEmission(MCDCBase):
     # Annotations for Numba mode
     label: str = "weighted_emission"
 
@@ -50,7 +50,7 @@ def __call__(self, active: bool = True, weight_target: float = 1.0):
 # ======================================================================================
 
 
-class GlobalWeightRoulette(ObjectBase):
+class GlobalWeightRoulette(MCDCBase):
     # Annotations for Numba mode
     label: str = "global_weight_roulette"
 
@@ -78,7 +78,7 @@ def __call__(self, weight_threshold: float = 0.0, weight_target: float = 1.0):
 # ======================================================================================
 
 
-class WeightWindows(ObjectBase):
+class WeightWindows(MCDCBase):
     label: str = "weight_windows"
 
     active: bool
@@ -180,7 +180,7 @@ def __call__(self, weight_windows, mesh=None, energy=None):
 # ======================================================================================
 
 
-class PopulationControl(ObjectBase):
+class PopulationControl(MCDCBase):
     # Annotations for Numba mode
     label: str = "population_control"
     active: bool
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index a14942fe4..789757693 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -15,7 +15,7 @@
 ####
 
 from mcdc.constant import INF
-from mcdc.object_.base import ObjectNonSingleton
+from mcdc.object_.base import MCDCObject
 from mcdc.util import flatten
 
 # ======================================================================================
@@ -23,7 +23,7 @@
 # ======================================================================================
 
 
-class Universe(ObjectNonSingleton):
+class Universe(MCDCObject):
     """
     Define a list of cells as a universe.
 
@@ -85,7 +85,7 @@ def __repr__(self):
 # ======================================================================================
 
 
-class Lattice(ObjectNonSingleton):
+class Lattice(MCDCObject):
     """
     Define a regular lattice of universes.
 

From dc61e051bbb6a5da8b4e71eb122ee6d890128edc Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 13 Jul 2026 12:04:55 +0700
Subject: [PATCH 008/202] update object base

---
 mcdc/main.py               | 77 ++++++++++++++++++++++++++++++++------
 mcdc/object_/base.py       | 38 ++++++++++---------
 mcdc/object_/simulation.py |  5 ++-
 3 files changed, 90 insertions(+), 30 deletions(-)

diff --git a/mcdc/main.py b/mcdc/main.py
index 31864d521..a2e082821 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -1,9 +1,16 @@
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from mcdc.object_.simulation import Simulation
+    from mcdc.object_.base import MCDCObject
+
+
 # ======================================================================================
 # Run Simulation
 # ======================================================================================
 
 
-def run_simulation(simulationPy):
+def run_simulation(simulationPy: Simulation):
     """
     Execute the MC/DC simulation.
 
@@ -321,17 +328,61 @@ def prepare(simulationPy):
 # ======================================================================================
 
 
-def compile_simulation(simulationPy, compile_ID):
-    # Empty out
-    # Go over cells in the root universe
+def compile_simulation(simulationPy: Simulation, compile_ID: int):
 
-    from mcdc.object_.material import (
-        Material,
-        MaterialMG,
-        set_elements_from_nuclides,
-        set_nuclides_from_elements,
-        update_fissionable_from_nuclides,
-    )
+    # ==================================================================================
+    # Reset derived object lists
+    # ==================================================================================
+
+    # Physics
+    simulationPy.data = [simulationPy.data[0]]  # Keep None
+    simulationPy.distributions = [simulationPy.distributions[0]]  # Keep None
+    simulationPy.neutron_reactions = []
+    simulationPy.electron_reactions = []
+    simulationPy.nuclides = []
+    simulationPy.elements = []
+    simulationPy.materials = []
+
+    # Geometry
+    simulationPy.surfaces = []
+    simulationPy.regions = []
+    simulationPy.cells = []
+    simulationPy.universes = [simulationPy.universes[0]]  # Keep root universe
+    simulationPy.lattices = []
+    simulationPy.meshes = []
+
+    # ==================================================================================
+    # Object IDs
+    # ==================================================================================
+
+    next_ID = {
+        "data": 1,
+        "distribution": 1,
+        "neutron_reaction": 0,
+        "electron_reaction": 0,
+        "nuclide": 0,
+        "element": 0,
+        "material": 0,
+        "surface": 0,
+        "region": 0,
+        "cell": 0,
+        "universe": 1,
+        "lattice": 0,
+        "mesh": 0,
+    }
+
+    # ==================================================================================
+    # Compile root universe
+    # ==================================================================================
+
+    root_universe = simulationPy.universes[0]
+    root_universe.ID = 0
+    root_universe.compile_ID = compile_ID
+
+    for cell in root_universe.cells:
+        set_IDs(cell, "cell", next_ID, compile_ID)
+        cell.ID = next_ID["cell"]
+        cell.compile_ID = compile_ID
 
     # ==================================================================================
     # Set material data as needed
@@ -508,6 +559,10 @@ def compile_simulation(simulationPy, compile_ID):
     return simulation_container, data
 
 
+def set_IDs(object_: MCDCObject, next_ID: dict, compile_ID: int) -> None:
+    object_.ID = next_ID[object_.label]
+
+
 # ======================================================================================
 # Misc.
 # ======================================================================================
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index 2629b30eb..6dfe36a6f 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -5,21 +5,25 @@ class MCDCBase:
     """Base class for all Python-side MC/DC objects.
 
     ``MCDCBase`` provides functionality shared by framework objects,
-    including runtime type checking and metadata used during preparation
-    and execution.
+    including runtime type checking and common metadata used during
+    preparation and execution.
 
     Notes
     -----
     This class represents the root of the Python object hierarchy. It does
     not correspond directly to objects stored in the compiled simulation.
+    Framework metadata includes an object label and the list of attributes
+    excluded from the compiled representation.
     """
 
+    non_numba: list[str] = ["non_numba", "label"]
+    label: str
+
     def __init__(self):
-        """Initialize common object metadata."""
-        if hasattr(self, "non_numba"):
-            self.non_numba += ["non_numba", "label"]
-        else:
-            self.non_numba = ["non_numba", "label"]
+        """Initialize common framework metadata."""
+        # Create an instance-local copy so subclasses can safely extend it.
+        self.non_numba = list(self.non_numba)
+        self.label = "(Unlabeled)"
 
     def __setattr__(self, key, value):
         """Assign an attribute with runtime type checking.
@@ -37,7 +41,8 @@ class MCDCObject(MCDCBase):
     """Base class for compiled MC/DC objects.
 
     ``MCDCObject`` represents objects that are collected during simulation
-    compilation and assigned unique identifiers for the compiled model.
+    compilation and assigned deterministic identifiers for the compiled
+    model.
 
     Notes
     -----
@@ -50,21 +55,18 @@ class MCDCObject(MCDCBase):
 
     def __init__(self):
         """Initialize compilation metadata."""
-        self.ID = -1
-        self.compile_ID = 0
         super().__init__()
 
-        if hasattr(self, "non_numba"):
-            self.non_numba += ["ID", "compile_ID"]
-        else:
-            self.non_numba = ["ID", "compile_ID"]
+        self.ID = -1
+        self.compile_ID = 0
+        self.non_numba += ["ID", "compile_ID"]
 
 
 class MCDCPolymorphic(MCDCObject):
     """Base class for polymorphic compiled objects.
 
     Polymorphic objects belong to families that share a common compiled
-    representation while supporting multiple concrete object types.
+    representation while supporting multiple concrete subclasses.
 
     Notes
     -----
@@ -75,7 +77,7 @@ class MCDCPolymorphic(MCDCObject):
     child_ID: int
     type: int
 
-    def __init__(self, type_):
+    def __init__(self, type_: int):
         """Initialize polymorphic compilation metadata.
 
         Parameters
@@ -83,10 +85,10 @@ def __init__(self, type_):
         type_ : int
             Integer identifier specifying the concrete polymorphic type.
         """
-        self.child_ID = -1
-        self.type = type_
         super().__init__()
 
+        self.child_ID = -1
+        self.type = type_
         self.non_numba += ["child_ID"]
 
 
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 783beb6d8..c97153c10 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -213,7 +213,10 @@ def __init__(self, name: str = "") -> None:
         # Tallies
         self.tallies = []
 
-        # Settings
+        # ==============================================================================
+        # Simulation settings and techniques
+        # ==============================================================================
+
         self.settings = Settings()
 
         # Techniques

From 2f016da358b121fba922436cc779c986bab9c5f7 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 13 Jul 2026 13:35:04 +0700
Subject: [PATCH 009/202] update object base

---
 mcdc/object_/base.py | 169 ++++++++++++++++++++++++++++++++++---------
 1 file changed, 135 insertions(+), 34 deletions(-)

diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index 6dfe36a6f..1d761db60 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -5,25 +5,49 @@ class MCDCBase:
     """Base class for all Python-side MC/DC objects.
 
     ``MCDCBase`` provides functionality shared by framework objects,
-    including runtime type checking and common metadata used during
-    preparation and execution.
+    including runtime type checking and common metadata.
+
+    Parameters
+    ----------
+    label : str
+        Framework label identifying the object category.
+
+    non_numba : list of str
+        Additional attribute names excluded from the compiled
+        representation.
+
+    Attributes
+    ----------
+    label : str
+        Framework label identifying the object category.
+
+    non_numba : list of str
+        Names of object attributes that are excluded from the compiled
+        representation.
 
     Notes
     -----
-    This class represents the root of the Python object hierarchy. It does
-    not correspond directly to objects stored in the compiled simulation.
-    Framework metadata includes an object label and the list of attributes
-    excluded from the compiled representation.
+    This class is the root of the Python-side MC/DC object hierarchy. It does
+    not directly correspond to objects stored in the compiled simulation.
     """
 
-    non_numba: list[str] = ["non_numba", "label"]
     label: str
+    non_numba: list[str] = ["non_numba", "label"]
+
+    def __init__(self, label: str, non_numba: list[str]):
+        """Initialize common framework metadata.
 
-    def __init__(self):
-        """Initialize common framework metadata."""
-        # Create an instance-local copy so subclasses can safely extend it.
-        self.non_numba = list(self.non_numba)
-        self.label = "(Unlabeled)"
+        Parameters
+        ----------
+        label : str
+            Framework label identifying the object category.
+
+        non_numba : list of str
+            Additional attribute names excluded from the compiled
+            representation.
+        """
+        self.label = label
+        self.non_numba = ["label", "non_numba"] + non_numba
 
     def __setattr__(self, key, value):
         """Assign an attribute with runtime type checking.
@@ -41,55 +65,132 @@ class MCDCObject(MCDCBase):
     """Base class for compiled MC/DC objects.
 
     ``MCDCObject`` represents objects that are collected during simulation
-    compilation and assigned deterministic identifiers for the compiled
-    model.
+    compilation and assigned deterministic identifiers.
+
+    Parameters
+    ----------
+    label : str
+        Framework label identifying the object category.
+
+    non_numba : list of str
+        Additional attribute names excluded from the compiled representation.
+
+    Attributes
+    ----------
+    ID : int
+        Identifier of the object within its compiled collection. The default
+        value is ``-1`` until the object is collected during compilation.
+
+    compile_ID : int
+        Identifier of the compilation in which ``ID`` was assigned. The default
+        value is ``0`` until the object is collected during compilation.
 
     Notes
     -----
-    During compilation, each object is assigned an object identifier and the
-    identifier of the compilation in which it was collected.
+    During compilation, each object receives a unique object identifier within
+    its collection and records the compilation in which the identifier was
+    assigned.
     """
 
     ID: int
     compile_ID: int
 
-    def __init__(self):
-        """Initialize compilation metadata."""
-        super().__init__()
+    def __init__(self, label: str, non_numba: list[str]):
+        """Initialize compilation metadata.
+
+        Parameters
+        ----------
+        label : str
+            Framework label identifying the object category.
+
+        non_numba : list of str
+            Additional attribute names excluded from the compiled
+            representation.
+        """
+        super().__init__(label, non_numba)
 
         self.ID = -1
         self.compile_ID = 0
-        self.non_numba += ["ID", "compile_ID"]
+        self.non_numba += ["compile_ID"]
 
 
 class MCDCPolymorphic(MCDCObject):
-    """Base class for polymorphic compiled objects.
+    """Base class for polymorphic compiled MC/DC objects.
 
-    Polymorphic objects belong to families that share a common compiled
-    representation while supporting multiple concrete subclasses.
+    Polymorphic objects belong to object families identified by ``label``.
+    Within each family, concrete subclasses are identified by ``child_label``
+    and ``child_type``.
 
-    Notes
-    -----
-    In addition to the object identifier, polymorphic objects receive a
-    child identifier that is unique within their polymorphic family.
+    Parameters
+    ----------
+    label : str
+        Framework label identifying the object family.
+
+    child_label : str
+        Framework label identifying the concrete polymorphic subtype.
+
+    child_type : int
+        Integer identifier specifying the concrete polymorphic subtype.
+
+    non_numba : list of str
+        Additional attribute names excluded from the compiled representation.
+
+    Attributes
+    ----------
+    ID : int
+        Identifier of the object within its compiled collection. The default
+        value is ``-1`` until the object is collected during compilation.
+
+    compile_ID : int
+        Identifier of the compilation in which ``ID`` and ``child_ID`` were
+        assigned. The default value is ``0`` until compilation.
+
+    child_label : str
+        Framework label identifying the concrete polymorphic subtype.
+
+    child_type : int
+        Integer discriminator used to represent the concrete subtype in the
+        compiled model.
+
+    child_ID : int
+        Identifier of the object within its concrete polymorphic subtype. The
+        default value is ``-1`` until compilation.
     """
 
+    child_label: str
+    child_type: int
     child_ID: int
-    type: int
 
-    def __init__(self, type_: int):
+    def __init__(
+        self,
+        label: str,
+        child_label: str,
+        child_type: int,
+        non_numba: list[str],
+    ):
         """Initialize polymorphic compilation metadata.
 
         Parameters
         ----------
-        type_ : int
-            Integer identifier specifying the concrete polymorphic type.
+        label : str
+            Framework label identifying the object family.
+
+        child_label : str
+            Framework label identifying the concrete polymorphic subtype.
+
+        child_type : int
+            Integer identifier specifying the concrete polymorphic subtype.
+
+        non_numba : list of str
+            Additional attribute names excluded from the compiled
+            representation.
         """
-        super().__init__()
+        super().__init__(label, non_numba)
 
+        self.child_label = child_label
+        self.child_type = child_type
         self.child_ID = -1
-        self.type = type_
-        self.non_numba += ["child_ID"]
+        self.non_numba += ["child_label"]
 
 
 # ======================================================================================

From 812912ac42a5790cdc6d3099e9f26730f04a39da Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 13 Jul 2026 13:36:26 +0700
Subject: [PATCH 010/202] update Data objects

---
 mcdc/object_/data.py | 324 +++++++++++++++++++++++++++++--------------
 1 file changed, 217 insertions(+), 107 deletions(-)

diff --git a/mcdc/object_/data.py b/mcdc/object_/data.py
index 404c617f2..20cff8124 100644
--- a/mcdc/object_/data.py
+++ b/mcdc/object_/data.py
@@ -1,21 +1,20 @@
-import numpy as np
-
 from collections.abc import Sequence
-from numpy import float64, int64
-from numpy.typing import NDArray
+from numbers import Integral
 from typing import Annotated
 
-####
+import numpy as np
+from numpy import float64, int64
+from numpy.typing import NDArray
 
 from mcdc.constant import (
     DATA_NONE,
-    DATA_TABLE,
     DATA_POLYNOMIAL,
+    DATA_TABLE,
     INTERPOLATION_HISTOGRAM,
     INTERPOLATION_LINEAR,
+    INTERPOLATION_LOG,
     INTERPOLATION_SEMILOGX,
     INTERPOLATION_SEMILOGY,
-    INTERPOLATION_LOG,
 )
 from mcdc.object_.base import MCDCPolymorphic
 from mcdc.print_ import print_1d_array, print_error
@@ -26,43 +25,81 @@
 
 
 class DataBase(MCDCPolymorphic):
-    # Annotations for Numba mode
-    label: str = "data"
+    """Base class for compiled data objects.
 
-    def __init__(self, type_):
-        super().__init__(type_)
+    Data objects store numerical information used by physics models,
+    distributions, and other MC/DC objects. Concrete subclasses determine the
+    representation of the stored data.
+    """
 
-    def __repr__(self):
-        text = "\n"
-        text += f"{decode_type(self.type)}\n"
-        text += f"  - ID: {self.ID}\n"
-        return text
+    def __init__(
+        self,
+        child_label: str,
+        child_type: int,
+        non_numba: list[str],
+    ) -> None:
+        """Initialize data framework metadata.
 
+        Parameters
+        ----------
+        child_label : str
+            Framework label identifying the concrete data representation.
+
+        child_type : int
+            Integer identifier specifying the concrete data representation.
+
+        non_numba : list of str
+            Additional attribute names excluded from the compiled
+            representation.
+        """
+        super().__init__("data", child_label, child_type, non_numba)
+
+    def __repr__(self) -> str:
+        """Return a human-readable description of the data object."""
+        return f"\n{decode_type(self.child_type)}\n"
+
+
+def decode_type(type_: int) -> str:
+    """Convert a data type code to a human-readable name.
 
-def decode_type(type_):
+    Parameters
+    ----------
+    type_ : int
+        Data type code.
+
+    Returns
+    -------
+    str
+        Human-readable data type name.
+
+    Raises
+    ------
+    ValueError
+        If the data type code is unknown.
+    """
     if type_ == DATA_NONE:
         return "Data (None)"
-    elif type_ == DATA_TABLE:
+    if type_ == DATA_TABLE:
         return "Data (Table)"
-    elif type_ == DATA_POLYNOMIAL:
+    if type_ == DATA_POLYNOMIAL:
         return "Data (Polynomial function)"
 
+    raise ValueError(f"Unknown data type: {type_}")
+
 
 # ======================================================================================
 # None
 # ======================================================================================
 # Placeholder for data that does not need to store anything:
-#   - Fission multiplicity and delayed precursor data for non-fissionable nuclide
+#   - Fission multiplicity and delayed precursor data for non-fissionable nuclides
 
 
 class DataNone(DataBase):
-    # Annotations for Numba mode
-    label: str = "none_data"
+    """Placeholder for the absence of stored data."""
 
-    def __init__(self):
-        type_ = DATA_NONE
-        super().__init__(type_)
-        self.ID = 0
+    def __init__(self) -> None:
+        """Create an empty data object."""
+        super().__init__("none_data", DATA_NONE, [])
 
 
 # ======================================================================================
@@ -71,26 +108,26 @@ def __init__(self):
 
 
 class DataTable(DataBase):
-    """
-    Tabulated one-dimensional data with ENDF/ACE-style interpolation regions.
+    """Tabulated one-dimensional data with interpolation regions.
 
-    The interpolation laws apply only to `y`. The optional `aux` array stores
-    additional data aligned with `x`, such as a CDF associated with a PDF table.
-    Auxiliary data are stored for lookup only and are not interpolated.
+    Interpolation laws are applied to ``y`` over regions of ``x``. Optional
+    auxiliary arrays may store additional values aligned with ``x``, such as
+    cumulative distribution functions associated with tabulated probability
+    densities. Auxiliary data are stored for lookup and are not interpolated.
     """
 
-    # Annotations for Numba mode
-    label: str = "table_data"
-    #
+    # Main data
     N: int
     x: NDArray[float64]
     y: NDArray[float64]
-    #
+
+    # Interpolation rules
     interpolations: NDArray[int64]
     interpolation_boundaries: NDArray[int64]
-    #
+
+    # Auxiliary data
     N_aux: int
-    aux: Annotated[NDArray[np.float64], ("N_aux", "N")]
+    aux: Annotated[NDArray[float64], ("N_aux", "N")]
 
     def __init__(
         self,
@@ -100,38 +137,46 @@ def __init__(
         interpolation_boundaries: Sequence[int] | None = None,
         aux: NDArray[float64] | None = None,
     ) -> None:
-        """
-        Create a tabulated data object.
+        """Create a tabulated data object.
 
         Parameters
         ----------
         x : ndarray of float64
-            Independent variable values.
+            One-dimensional independent-variable values.
+
         y : ndarray of float64
-            Dependent variable values.
+            One-dimensional dependent-variable values aligned with ``x``.
+
         interpolations : int or sequence of int
-            Interpolation law or list of interpolation laws.
+            Interpolation law applied to the entire table, or an ordered
+            sequence of interpolation laws for multiple regions.
+
         interpolation_boundaries : sequence of int, optional
-            Region boundaries. Required when `interpolations` is a sequence.
+            Exclusive upper index of each interpolation region. Required when
+            multiple interpolation laws are provided. The final boundary must
+            equal ``len(x)``.
+
         aux : ndarray of float64, optional
-            Auxiliary data aligned with `x`. A one-dimensional array is stored
-            internally with shape `(1, N)`. A two-dimensional array must have
-            shape `(N_aux, N)`. Auxiliary data are not interpolated.
+            Auxiliary data aligned with ``x``. A one-dimensional array is
+            stored with shape ``(1, N)``. A two-dimensional array must have
+            shape ``(N_aux, N)``.
 
         Notes
         -----
-        Boundaries are stored as Python-style exclusive upper indices.
-        Therefore the final boundary should be `len(x)`.
+        Interpolation boundaries use Python-style exclusive upper indices.
         """
-
-        # Set type
-        type_ = DATA_TABLE
-        super().__init__(type_)
+        super().__init__("table_data", DATA_TABLE, [])
 
         # Set primary data
-        self.x = x
-        self.y = y
-        self.N = len(x)
+        self.x = np.asarray(x, dtype=float64)
+        self.y = np.asarray(y, dtype=float64)
+
+        if self.x.ndim != 1:
+            print_error("x must be one-dimensional.")
+        if self.y.ndim != 1:
+            print_error("y must be one-dimensional.")
+
+        self.N = len(self.x)
 
         # Basic size checks
         if self.N == 0:
@@ -142,36 +187,51 @@ def __init__(
         # Set auxiliary data
         if aux is None:
             self.N_aux = 0
-            self.aux = np.zeros((0, self.N), dtype=float)
-        elif aux.ndim == 1:
-            self.N_aux = 1
-            if len(aux) != self.N:
-                print_error("1D aux must have the same length as x.")
-            self.aux = np.zeros((1, self.N), dtype=float)
-            self.aux[0, :] = aux
-        elif aux.ndim == 2:
-            self.N_aux = aux.shape[0]
-            if aux.shape[1] != self.N:
-                print_error("2D aux must have shape (N_aux, len(x)).")
-            self.aux = aux
+            self.aux = np.zeros((0, self.N), dtype=float64)
         else:
-            print_error("aux must be None, 1D, or 2D.")
+            aux_array = np.asarray(aux, dtype=float64)
+
+            if aux_array.ndim == 1:
+                if len(aux_array) != self.N:
+                    print_error("One-dimensional aux must have the same length as x.")
+
+                self.N_aux = 1
+                self.aux = aux_array.reshape(1, self.N)
 
-        # Set interpolations and boundaries
-        if isinstance(interpolations, int):
-            self.interpolations = np.array([interpolations], dtype=int)
-            self.interpolation_boundaries = np.array([self.N], dtype=int)
+            elif aux_array.ndim == 2:
+                if aux_array.shape[1] != self.N:
+                    print_error("Two-dimensional aux must have shape (N_aux, len(x)).")
+
+                self.N_aux = aux_array.shape[0]
+                self.aux = aux_array
+
+            else:
+                print_error("aux must be None, one-dimensional, or two-dimensional.")
+
+        # Set interpolation rules and boundaries
+        if isinstance(interpolations, Integral):
+            self.interpolations = np.array([interpolations], dtype=int64)
+            self.interpolation_boundaries = np.array([self.N], dtype=int64)
         else:
-            self.interpolations = np.array(interpolations, dtype=int)
+            self.interpolations = np.asarray(interpolations, dtype=int64)
+
+            if self.interpolations.ndim != 1:
+                print_error("interpolations must be one-dimensional.")
 
             if interpolation_boundaries is None:
-                print_error("Missing interpolation boundaries in tabulated data.")
+                print_error(
+                    "interpolation_boundaries is required when multiple "
+                    "interpolation laws are provided."
+                )
 
-            self.interpolation_boundaries = np.array(
+            self.interpolation_boundaries = np.asarray(
                 interpolation_boundaries,
-                dtype=int,
+                dtype=int64,
             )
 
+            if self.interpolation_boundaries.ndim != 1:
+                print_error("interpolation_boundaries must be one-dimensional.")
+
         # Interpolation-region checks
         if len(self.interpolations) == 0:
             print_error("At least one interpolation law is required.")
@@ -182,7 +242,7 @@ def __init__(
             )
 
         if self.interpolation_boundaries[-1] != self.N:
-            print_error("Last interpolation boundary must equal len(x).")
+            print_error("The last interpolation boundary must equal len(x).")
 
         previous = 0
         for boundary in self.interpolation_boundaries:
@@ -190,8 +250,13 @@ def __init__(
                 print_error("interpolation_boundaries must be strictly increasing.")
             if boundary > self.N:
                 print_error("interpolation_boundaries cannot exceed len(x).")
+
             previous = boundary
 
+        # Validate interpolation codes
+        for interpolation in self.interpolations:
+            decode_interpolation(interpolation)
+
     def __repr__(self) -> str:
         """Return a human-readable summary of the tabulated data."""
         text = super().__repr__()
@@ -200,58 +265,93 @@ def __repr__(self) -> str:
 
         if self.N_aux > 0:
             text += f"  - aux shape: {self.aux.shape}\n"
-            for i in range(len(self.aux)):
-                text += f"    - aux[{i}]: {print_1d_array(self.aux[i])}\n"
+            for i, values in enumerate(self.aux):
+                text += f"    - aux[{i}]: {print_1d_array(values)}\n"
 
         if len(self.interpolations) == 1:
             text += (
-                f"  - Interpolation: "
+                "  - Interpolation: "
                 f"{decode_interpolation(self.interpolations[0])}\n"
             )
         else:
             text += "  - Interpolation regions:\n"
 
             start = 0
-            for interp, end in zip(
+            for interpolation, end in zip(
                 self.interpolations,
                 self.interpolation_boundaries,
             ):
-                text += f"    - [{start}, {end}): " f"{decode_interpolation(interp)}\n"
+                text += (
+                    f"    - [{start}, {end}): "
+                    f"{decode_interpolation(interpolation)}\n"
+                )
                 start = end
 
         return text
 
 
-def decode_interpolation(type_) -> str:
-    """Convert an interpolation integer code to its string name."""
+def decode_interpolation(type_: int) -> str:
+    """Convert an interpolation type code to its string name.
+
+    Parameters
+    ----------
+    type_ : int
+        Interpolation type code.
+
+    Returns
+    -------
+    str
+        Interpolation name.
+
+    Raises
+    ------
+    ValueError
+        If the interpolation type code is unknown.
+    """
     if type_ == INTERPOLATION_HISTOGRAM:
         return "histogram"
-    elif type_ == INTERPOLATION_LINEAR:
+    if type_ == INTERPOLATION_LINEAR:
         return "linear"
-    elif type_ == INTERPOLATION_SEMILOGX:
+    if type_ == INTERPOLATION_SEMILOGX:
         return "semilog-x"
-    elif type_ == INTERPOLATION_SEMILOGY:
+    if type_ == INTERPOLATION_SEMILOGY:
         return "semilog-y"
-    elif type_ == INTERPOLATION_LOG:
+    if type_ == INTERPOLATION_LOG:
         return "log"
-    else:
-        raise ValueError(f"Unknown interpolation type: {type_}")
+
+    raise ValueError(f"Unknown interpolation type: {type_}")
 
 
-def encode_interpolation(type_) -> int:
-    """Convert an interpolation string name to its integer code."""
-    if type_ == "histogram":
+def encode_interpolation(name: str) -> int:
+    """Convert an interpolation name to its integer type code.
+
+    Parameters
+    ----------
+    name : str
+        Interpolation name.
+
+    Returns
+    -------
+    int
+        Interpolation type code.
+
+    Raises
+    ------
+    ValueError
+        If the interpolation name is unknown.
+    """
+    if name == "histogram":
         return INTERPOLATION_HISTOGRAM
-    elif type_ == "linear":
+    if name == "linear":
         return INTERPOLATION_LINEAR
-    elif type_ == "semilog-x":
+    if name == "semilog-x":
         return INTERPOLATION_SEMILOGX
-    elif type_ == "semilog-y":
+    if name == "semilog-y":
         return INTERPOLATION_SEMILOGY
-    elif type_ == "log":
+    if name == "log":
         return INTERPOLATION_LOG
-    else:
-        raise ValueError(f"Unknown interpolation name: {type_}")
+
+    raise ValueError(f"Unknown interpolation name: {name}")
 
 
 # ======================================================================================
@@ -260,18 +360,28 @@ def encode_interpolation(type_) -> int:
 
 
 class DataPolynomial(DataBase):
-    # Annotations for Numba mode
-    label: str = "polynomial_data"
-    #
+    """Polynomial data represented by an ordered coefficient array."""
+
     coefficients: NDArray[float64]
 
-    def __init__(self, coeffs):
-        type_ = DATA_POLYNOMIAL
-        super().__init__(type_)
+    def __init__(self, coefficients: NDArray[float64]) -> None:
+        """Create a polynomial data object.
+
+        Parameters
+        ----------
+        coefficients : ndarray of float64
+            One-dimensional polynomial coefficients ordered according to the
+            convention used by the consuming MC/DC method.
+        """
+        super().__init__("polynomial_data", DATA_POLYNOMIAL, [])
+
+        self.coefficients = np.asarray(coefficients, dtype=float64)
 
-        self.coefficients = coeffs
+        if self.coefficients.ndim != 1:
+            print_error("coefficients must be one-dimensional.")
 
-    def __repr__(self):
+    def __repr__(self) -> str:
+        """Return a human-readable summary of the polynomial data."""
         text = super().__repr__()
         text += f"  - coefficients {print_1d_array(self.coefficients)}\n"
         return text

From 2143e53355e9140ca5be937ce380182d0517e5e7 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 13 Jul 2026 13:39:55 +0700
Subject: [PATCH 011/202] update simulation

---
 mcdc/main.py               | 32 ++++++++++++++++--------------
 mcdc/object_/cell.py       | 13 ++++++-------
 mcdc/object_/simulation.py | 40 ++++++++++++++++++--------------------
 3 files changed, 42 insertions(+), 43 deletions(-)

diff --git a/mcdc/main.py b/mcdc/main.py
index a2e082821..8db600c7d 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -1,9 +1,5 @@
-from typing import TYPE_CHECKING
-
-if TYPE_CHECKING:
-    from mcdc.object_.simulation import Simulation
-    from mcdc.object_.base import MCDCObject
-
+from mcdc.object_.simulation import Simulation
+from mcdc.object_.base import MCDCObject
 
 # ======================================================================================
 # Run Simulation
@@ -356,8 +352,8 @@ def compile_simulation(simulationPy: Simulation, compile_ID: int):
     # ==================================================================================
 
     next_ID = {
-        "data": 1,
-        "distribution": 1,
+        "data": 0,
+        "distribution": 0,
         "neutron_reaction": 0,
         "electron_reaction": 0,
         "nuclide": 0,
@@ -366,23 +362,27 @@ def compile_simulation(simulationPy: Simulation, compile_ID: int):
         "surface": 0,
         "region": 0,
         "cell": 0,
-        "universe": 1,
+        "universe": 0,
         "lattice": 0,
         "mesh": 0,
     }
 
     # ==================================================================================
-    # Compile root universe
+    # Assign ID to reserved objects
+    # ==================================================================================
+
+    set_IDs(simulationPy.data[0], next_ID, compile_ID)
+    set_IDs(simulationPy.distributions[0], next_ID, compile_ID)
+    set_IDs(simulationPy.universes[0], next_ID, compile_ID)
+
+    # ==================================================================================
+    # Compile root universe cells
     # ==================================================================================
 
     root_universe = simulationPy.universes[0]
-    root_universe.ID = 0
-    root_universe.compile_ID = compile_ID
 
     for cell in root_universe.cells:
-        set_IDs(cell, "cell", next_ID, compile_ID)
-        cell.ID = next_ID["cell"]
-        cell.compile_ID = compile_ID
+        set_IDs(cell, next_ID, compile_ID)
 
     # ==================================================================================
     # Set material data as needed
@@ -561,6 +561,8 @@ def compile_simulation(simulationPy: Simulation, compile_ID: int):
 
 def set_IDs(object_: MCDCObject, next_ID: dict, compile_ID: int) -> None:
     object_.ID = next_ID[object_.label]
+    object_.compile_ID = compile_ID
+    next_ID[object_.label] += 1
 
 
 # ======================================================================================
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 6f637d8a4..55c24b4af 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -98,19 +98,15 @@ class Cell(MCDCObject):
     mcdc.Universe : Groups cells into a universe.
     """
 
-    # Annotations for Numba mode
-    label: str = "cell"
-    non_numba: list[str] = ["region", "fill", "region_RPN"]
-    #
     name: str
-    region: Region
-    fill: MaterialBase | Universe | Lattice | NoneType
+    region: Region  # Non-numba
+    fill: MaterialBase | Universe | Lattice | NoneType  # Non-numba
     fill_translated: bool
     fill_rotated: bool
     translation: Annotated[NDArray[float64], (3,)]
     rotation: Annotated[NDArray[float64], (3,)]
     region_RPN_tokens: list[int]
-    region_RPN: Boolean
+    region_RPN: Boolean  # Non-numba
     surfaces: list[Surface]
     collision_tallies: list[TallyCollision]
     tracklength_tallies: list[TallyTracklength]
@@ -126,7 +122,10 @@ def __init__(
         translation: Sequence[float] = [0.0, 0.0, 0.0],
         rotation: Sequence[float] = [0.0, 0.0, 0.0],
     ):
+        # MC/DC framework metadata
         super().__init__()
+        self.label = "cell"
+        self.non_numba += ["region", "fill", "region_RPN"]
 
         # Set name
         if name == "":
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index c97153c10..d7dbfde56 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -65,24 +65,12 @@ class Simulation(MCDCBase):
     the execution backend.
     """
 
-    _next_compile_ID: int = 1
-
-    # Annotations for Numba mode
-    label: str = "simulation"
-    non_numba: list[str] = [
-        "regions",
-        "bank_active",
-        "bank_census",
-        "bank_source",
-        "bank_future",
-        "_next_compile_ID",
-        "compiled",
-    ]
+    _next_compile_ID: int = 1  # Non-Numba
 
     # Basic parameters
     name: str
-    compile_ID: int
-    compiled: bool
+    compile_ID: int  # Non-Numba
+    compiled: bool  # Non-Numba
 
     # Physics
     data: list[DataBase]
@@ -96,7 +84,7 @@ class Simulation(MCDCBase):
 
     # Geometry
     surfaces: list[Surface]
-    regions: list[Region]
+    regions: list[Region]  # Non-Numba
     cells: list[Cell]
     universes: list[Universe]
     lattices: list[Lattice]
@@ -116,10 +104,10 @@ class Simulation(MCDCBase):
     population_control: PopulationControl
 
     # Particle banks
-    bank_active: ParticleBank
-    bank_census: ParticleBank
-    bank_source: ParticleBank
-    bank_future: ParticleBank
+    bank_active: ParticleBank  # Non-Numba
+    bank_census: ParticleBank  # Non-Numba
+    bank_source: ParticleBank  # Non-Numba
+    bank_future: ParticleBank  # Non-Numba
 
     # Simulation indices
     idx_work: int
@@ -180,7 +168,17 @@ def __init__(self, name: str = "") -> None:
             User-defined simulation name. If omitted, an unnamed simulation is
             created.
         """
-        super().__init__()
+        non_numba = [
+            "regions",
+            "bank_active",
+            "bank_census",
+            "bank_source",
+            "bank_future",
+            "_next_compile_ID",
+            "compiled",
+            "compile_ID",
+        ]
+        super().__init__("simulation", non_numba)
 
         # Set name
         self.name = name or "(Unnamed simulation)"

From 707758ce804b2af55003de5859814c2f7d024293 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 13 Jul 2026 14:03:14 +0700
Subject: [PATCH 012/202] update distribution

---
 mcdc/object_/distribution.py | 691 ++++++++++++++++++++++-------------
 1 file changed, 442 insertions(+), 249 deletions(-)

diff --git a/mcdc/object_/distribution.py b/mcdc/object_/distribution.py
index 936f7eedb..820e4cba6 100644
--- a/mcdc/object_/distribution.py
+++ b/mcdc/object_/distribution.py
@@ -2,9 +2,7 @@
 
 from collections.abc import Sequence
 from numpy import float64, int64
-from numpy.typing import NDArray
-
-####
+from numpy.typing import ArrayLike, NDArray
 
 from mcdc.constant import (
     DISTRIBUTION_NONE,
@@ -36,83 +34,157 @@
 
 
 class DistributionBase(MCDCPolymorphic):
-    # Annotations for Numba mode
-    label: str = "distribution"
+    """Base class for probability distributions.
+
+    Distribution objects describe probability laws used throughout MC/DC,
+    including source distributions and secondary-particle distributions.
+
+    Parameters
+    ----------
+    child_label : str
+        Framework label identifying the concrete distribution subtype.
+
+    child_type : int
+        Integer identifier specifying the concrete distribution subtype.
 
-    def __init__(self, type_):
-        super().__init__(type_)
+    non_numba : list of str
+        Additional attribute names excluded from the compiled representation.
+    """
+
+    def __init__(
+        self,
+        child_label: str,
+        child_type: int,
+        non_numba: list[str],
+    ) -> None:
+        """Initialize distribution framework metadata."""
+        super().__init__(
+            label="distribution",
+            child_label=child_label,
+            child_type=child_type,
+            non_numba=non_numba,
+        )
 
-    def __repr__(self):
+    def __repr__(self) -> str:
+        """Return a human-readable description of the distribution."""
         text = "\n"
-        text += f"{decode_type(self.type)}\n"
+        text += f"{decode_type(self.child_type)}\n"
         text += f"  - ID: {self.ID}\n"
         return text
 
 
-def decode_type(type_):
-    if type_ == DISTRIBUTION_NONE:
+def decode_type(child_type: int) -> str:
+    """Convert a distribution type code to a human-readable name.
+
+    Parameters
+    ----------
+    child_type : int
+        Distribution type code.
+
+    Returns
+    -------
+    str
+        Human-readable distribution name.
+
+    Raises
+    ------
+    ValueError
+        If the distribution type code is unknown.
+    """
+    if child_type == DISTRIBUTION_NONE:
         return "Distribution (None)"
-    elif type_ == DISTRIBUTION_PMF:
+    if child_type == DISTRIBUTION_PMF:
         return "Distribution (PMF)"
-    elif type_ == DISTRIBUTION_TABULATED:
+    if child_type == DISTRIBUTION_TABULATED:
         return "Distribution (Tabulated)"
-    elif type_ == DISTRIBUTION_MULTITABLE:
-        return "Distribution (Multi Table)"
-    elif type_ == DISTRIBUTION_LEVEL_SCATTERING:
+    if child_type == DISTRIBUTION_MULTITABLE:
+        return "Distribution (Multi-table)"
+    if child_type == DISTRIBUTION_LEVEL_SCATTERING:
         return "Distribution (Level scattering)"
-    elif type_ == DISTRIBUTION_EVAPORATION:
+    if child_type == DISTRIBUTION_EVAPORATION:
         return "Distribution (Evaporation)"
-    elif type_ == DISTRIBUTION_MAXWELLIAN:
+    if child_type == DISTRIBUTION_MAXWELLIAN:
         return "Distribution (Maxwellian spectrum)"
-    elif type_ == DISTRIBUTION_KALBACH_MANN:
+    if child_type == DISTRIBUTION_KALBACH_MANN:
         return "Distribution (Kalbach-Mann)"
-    elif type_ == DISTRIBUTION_TABULATED_ENERGY_ANGLE:
+    if child_type == DISTRIBUTION_TABULATED_ENERGY_ANGLE:
         return "Distribution (Tabulated energy-angle)"
-    elif type_ == DISTRIBUTION_N_BODY:
+    if child_type == DISTRIBUTION_N_BODY:
         return "Distribution (N-body)"
 
+    raise ValueError(f"Unknown distribution type: {child_type}")
+
 
 # ======================================================================================
 # None
 # ======================================================================================
-# Placeholder for distribution that does not need to store data:
-#   - Isotropic
-#   - Energy-correlated angle (stored in the energy distribution)
+# Placeholder for a distribution that does not need to store data:
+#   - Isotropic distributions
+#   - Energy-correlated angles stored in the energy distribution
 
 
 class DistributionNone(DistributionBase):
-    # Annotations for Numba mode
-    label: str = "none_distribution"
-
-    def __init__(self):
-        type_ = DISTRIBUTION_NONE
-        super().__init__(type_)
-        self.ID = 0
+    """Placeholder for the absence of a stored distribution."""
+
+    def __init__(self) -> None:
+        """Create an empty distribution object."""
+        super().__init__(
+            child_label="none_distribution",
+            child_type=DISTRIBUTION_NONE,
+            non_numba=[],
+        )
 
 
 # ======================================================================================
-# Probability Mass Function (PMF)
+# Probability mass function
 # ======================================================================================
 
 
 class DistributionPMF(DistributionBase):
-    # Annotations for Numba mode
-    label: str = "pmf_distribution"
-    #
+    """Discrete probability mass function."""
+
     value: NDArray[float64]
     pmf: NDArray[float64]
     cmf: NDArray[float64]
 
-    def __init__(self, value, pmf):
-        type_ = DISTRIBUTION_PMF
-        super().__init__(type_)
+    def __init__(
+        self,
+        value: ArrayLike,
+        pmf: ArrayLike,
+    ) -> None:
+        """Create a discrete probability mass function.
 
-        self.value = value
-        self.pmf = pmf
+        Parameters
+        ----------
+        value : array_like
+            Values sampled by the distribution.
 
-        self.pmf, self.cmf = cmf_from_pmf(pmf)
+        pmf : array_like
+            Probability masses corresponding to ``value``. The masses are
+            normalized internally.
+        """
+        super().__init__(
+            child_label="pmf_distribution",
+            child_type=DISTRIBUTION_PMF,
+            non_numba=[],
+        )
+
+        self.value = np.asarray(value, dtype=float64)
+        pmf_array = np.asarray(pmf, dtype=float64)
+
+        if self.value.ndim != 1:
+            print_error("value must be one-dimensional.")
+        if pmf_array.ndim != 1:
+            print_error("pmf must be one-dimensional.")
+        if len(self.value) == 0:
+            print_error("value and pmf must contain at least one entry.")
+        if len(self.value) != len(pmf_array):
+            print_error("value and pmf must have the same length.")
 
-    def __repr__(self):
+        self.pmf, self.cmf = cmf_from_pmf(pmf_array)
+
+    def __repr__(self) -> str:
+        """Return a human-readable summary of the PMF."""
         text = super().__repr__()
         text += f"  - value {print_1d_array(self.value)}\n"
         text += f"  - pmf {print_1d_array(self.pmf)}\n"
@@ -125,66 +197,89 @@ def __repr__(self):
 
 
 class DistributionTabulated(DistributionBase):
-    """
-    One-dimensional tabulated probability distribution.
+    """One-dimensional tabulated probability distribution.
 
-    The distribution is stored as a DataTable whose independent variable is the
-    sample value and whose dependent variable is the normalized PDF. The CDF is
-    stored as auxiliary table data and is used for sampling.
+    The distribution is stored as a :class:`DataTable` whose independent
+    variable contains sample values and whose dependent variable contains the
+    normalized probability density. The cumulative distribution is stored as
+    auxiliary table data for sampling.
 
-    If constructed from a PDF, the PDF is assumed to be piecewise linear.
-    If constructed from a CDF, the CDF is assumed to be piecewise linear, which
-    implies a histogram PDF.
+    A PDF input is treated as piecewise linear. A CDF input is treated as
+    piecewise linear, producing a histogram PDF.
     """
 
-    # Annotations for Numba mode
-    label: str = "tabulated_distribution"
-    #
     pdf: DataTable
 
     def __init__(
         self,
-        value: NDArray[float64],
-        pdf: NDArray[float64] | None = None,
-        cdf: NDArray[float64] | None = None,
+        value: ArrayLike,
+        pdf: ArrayLike | None = None,
+        cdf: ArrayLike | None = None,
     ) -> None:
-        """
-        Construct a tabulated probability distribution from either a PDF or CDF.
+        """Create a tabulated distribution from either a PDF or CDF.
 
         Parameters
         ----------
-        value : ndarray of float64
+        value : array_like
             Sample values.
-        pdf : ndarray of float64, optional
-            Probability density values at the sample values. If provided, the
-            PDF is normalized and the CDF is computed by trapezoidal
-            integration.
-        cdf : ndarray of float64, optional
-            Cumulative distribution values at the sample values. If provided,
-            the CDF is normalized and a histogram PDF is derived from it.
+
+        pdf : array_like, optional
+            Probability densities at the sample values. The PDF is normalized
+            and its CDF is calculated by trapezoidal integration.
+
+        cdf : array_like, optional
+            Cumulative probabilities at the sample values. The CDF is
+            normalized and a histogram PDF is derived from it.
 
         Notes
         -----
-        Exactly one of `pdf` or `cdf` must be provided. PDF input uses linear
-        interpolation. CDF input uses histogram interpolation for the derived
-        PDF.
+        Exactly one of ``pdf`` or ``cdf`` must be provided.
         """
-
-        type_ = DISTRIBUTION_TABULATED
-        super().__init__(type_)
+        super().__init__(
+            child_label="tabulated_distribution",
+            child_type=DISTRIBUTION_TABULATED,
+            non_numba=[],
+        )
 
         if (pdf is None) == (cdf is None):
             print_error("Exactly one of pdf or cdf must be provided.")
 
+        value_array = np.asarray(value, dtype=float64)
+
+        if value_array.ndim != 1:
+            print_error("value must be one-dimensional.")
+        if len(value_array) == 0:
+            print_error("value must contain at least one entry.")
+
         if pdf is not None:
+            pdf_array = np.asarray(pdf, dtype=float64)
+
+            if pdf_array.ndim != 1:
+                print_error("pdf must be one-dimensional.")
+            if len(pdf_array) != len(value_array):
+                print_error("value and pdf must have the same length.")
+
             interpolation = INTERPOLATION_LINEAR
-            pdf_normalized, cdf_normalized = cdf_from_pdf(value, pdf)
+            pdf_normalized, cdf_normalized = cdf_from_pdf(
+                value_array,
+                pdf_array,
+            )
         else:
+            cdf_array = np.asarray(cdf, dtype=float64)
+
+            if cdf_array.ndim != 1:
+                print_error("cdf must be one-dimensional.")
+            if len(cdf_array) != len(value_array):
+                print_error("value and cdf must have the same length.")
+
             interpolation = INTERPOLATION_HISTOGRAM
-            pdf_normalized, cdf_normalized = pdf_from_cdf(value, cdf)
+            pdf_normalized, cdf_normalized = pdf_from_cdf(
+                value_array,
+                cdf_array,
+            )
 
         self.pdf = DataTable(
-            value,
+            value_array,
             pdf_normalized,
             interpolation,
             aux=cdf_normalized,
@@ -192,13 +287,10 @@ def __init__(
 
     def __repr__(self) -> str:
         """Return a human-readable summary of the distribution."""
-
         text = super().__repr__()
-
         text += f"  - value {print_1d_array(self.pdf.x)}\n"
         text += f"  - probability density {print_1d_array(self.pdf.y)}\n"
-        text += f"  - cumulative distribution: " f"{print_1d_array(self.pdf.aux[0])}\n"
-
+        text += "  - cumulative distribution " f"{print_1d_array(self.pdf.aux[0])}\n"
         return text
 
 
@@ -208,109 +300,129 @@ def __repr__(self) -> str:
 
 
 class DistributionMultiTable(DistributionBase):
-    """
-    Distribution represented by multiple tabulated distributions on a grid.
+    """Distribution represented by tabulated distributions on a grid.
 
-    Each grid point owns one DistributionTabulated object. The flattened
-    `value` array is split into per-grid tables using `offset`.
+    Each grid point owns one :class:`DistributionTabulated`. The flattened
+    ``value`` array is divided into individual tables using ``offset``.
     """
 
-    # Annotations for Numba mode
-    label: str = "multi_table_distribution"
-    #
     grid: NDArray[float64]
     tables: list[DistributionTabulated]
 
     def __init__(
         self,
-        grid: NDArray[float64],
-        offset: NDArray[int64],
-        value: NDArray[float64],
-        pdf: NDArray[float64] | None = None,
-        cdf: NDArray[float64] | None = None,
+        grid: ArrayLike,
+        offset: ArrayLike,
+        value: ArrayLike,
+        pdf: ArrayLike | None = None,
+        cdf: ArrayLike | None = None,
     ) -> None:
-        """
-        Construct a multi-table distribution.
+        """Create a multi-table distribution.
 
         Parameters
         ----------
-        grid : ndarray of float64
+        grid : array_like
             Grid values associated with the tabulated distributions.
-        offset : ndarray of int64
-            Starting index of each table in the flattened `value` array.
-        value : ndarray of float64
+
+        offset : array_like
+            Starting index of each table in the flattened arrays.
+
+        value : array_like
             Flattened sample values for all tables.
-        pdf : ndarray of float64, optional
-            Flattened PDF values. Exactly one of `pdf` or `cdf` must be given.
-        cdf : ndarray of float64, optional
-            Flattened CDF values. Exactly one of `pdf` or `cdf` must be given.
-        """
 
-        type_ = DISTRIBUTION_MULTITABLE
-        super().__init__(type_)
+        pdf : array_like, optional
+            Flattened PDF values.
+
+        cdf : array_like, optional
+            Flattened CDF values.
+
+        Notes
+        -----
+        Exactly one of ``pdf`` or ``cdf`` must be provided.
+        """
+        super().__init__(
+            child_label="multi_table_distribution",
+            child_type=DISTRIBUTION_MULTITABLE,
+            non_numba=[],
+        )
 
         if (pdf is None) == (cdf is None):
             print_error("Exactly one of pdf or cdf must be provided.")
 
-        if len(grid) != len(offset):
-            print_error("grid and offset must have the same length.")
+        self.grid = np.asarray(grid, dtype=float64)
+        offset_array = np.asarray(offset, dtype=int64)
+        value_array = np.asarray(value, dtype=float64)
 
-        if len(grid) == 0:
-            print_error("grid must contain at least one value.")
+        if self.grid.ndim != 1:
+            print_error("grid must be one-dimensional.")
+        if offset_array.ndim != 1:
+            print_error("offset must be one-dimensional.")
+        if value_array.ndim != 1:
+            print_error("value must be one-dimensional.")
 
-        if offset[0] != 0:
+        if len(self.grid) == 0:
+            print_error("grid must contain at least one value.")
+        if len(self.grid) != len(offset_array):
+            print_error("grid and offset must have the same length.")
+        if len(value_array) == 0:
+            print_error("value must contain at least one value.")
+        if offset_array[0] != 0:
             print_error("offset[0] must be zero.")
+        if np.any(offset_array[1:] <= offset_array[:-1]):
+            print_error("offset must be strictly increasing.")
+        if offset_array[-1] >= len(value_array):
+            print_error("Every offset must refer to an element in value.")
 
-        if len(value) == 0:
-            print_error("value must contain at least one value.")
+        pdf_array = None
+        cdf_array = None
 
-        if pdf is not None and len(pdf) != len(value):
-            print_error("pdf and value must have the same length.")
+        if pdf is not None:
+            pdf_array = np.asarray(pdf, dtype=float64)
 
-        if cdf is not None and len(cdf) != len(value):
-            print_error("cdf and value must have the same length.")
+            if pdf_array.ndim != 1:
+                print_error("pdf must be one-dimensional.")
+            if len(pdf_array) != len(value_array):
+                print_error("pdf and value must have the same length.")
 
-        self.grid = grid
+        if cdf is not None:
+            cdf_array = np.asarray(cdf, dtype=float64)
 
-        stop = np.empty(len(offset), dtype=int)
-        stop[:-1] = offset[1:]
-        stop[-1] = len(value)
+            if cdf_array.ndim != 1:
+                print_error("cdf must be one-dimensional.")
+            if len(cdf_array) != len(value_array):
+                print_error("cdf and value must have the same length.")
 
-        self.tables = []
+        stop = np.empty(len(offset_array), dtype=int64)
+        stop[:-1] = offset_array[1:]
+        stop[-1] = len(value_array)
 
-        for i in range(len(grid)):
-            start_i = offset[i]
-            stop_i = stop[i]
+        self.tables = []
 
+        for start_i, stop_i in zip(offset_array, stop):
             if stop_i <= start_i:
                 print_error("Each table must contain at least one value.")
 
-            if pdf is not None:
-                # Piecewise linear PDF
-                new_table = DistributionTabulated(
-                    value[start_i:stop_i],
-                    pdf=pdf[start_i:stop_i],
+            if pdf_array is not None:
+                table = DistributionTabulated(
+                    value_array[start_i:stop_i],
+                    pdf=pdf_array[start_i:stop_i],
                 )
             else:
-                # Piecewise linear CDF
-                new_table = DistributionTabulated(
-                    value[start_i:stop_i],
-                    cdf=cdf[start_i:stop_i],
+                table = DistributionTabulated(
+                    value_array[start_i:stop_i],
+                    cdf=cdf_array[start_i:stop_i],
                 )
 
-            self.tables.append(new_table)
+            self.tables.append(table)
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the multi-table distribution."""
-
+        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
         text += f"  - grid: {print_1d_array(self.grid)}\n"
         text += f"  - tables: {len(self.tables)}\n"
 
         for i, table in enumerate(self.tables):
-            text += (
-                f"    - table[{i}] " f"(grid={self.grid[i]:.6g}, " f"N={table.pdf.N})\n"
-            )
+            text += f"    - table[{i}] " f"(grid={self.grid[i]:.6g}, N={table.pdf.N})\n"
 
         return text
 
@@ -321,22 +433,26 @@ def __repr__(self) -> str:
 
 
 class DistributionLevelScattering(DistributionBase):
-    # Annotations for Numba mode
-    label: str = "level_scattering_distribution"
-    #
+    """Level-scattering energy distribution."""
+
     C1: float
     C2: float
 
-    def __init__(self, C1, C2):
-        type_ = DISTRIBUTION_LEVEL_SCATTERING
-        super().__init__(type_)
+    def __init__(self, C1: float, C2: float) -> None:
+        """Create a level-scattering distribution."""
+        super().__init__(
+            child_label="level_scattering_distribution",
+            child_type=DISTRIBUTION_LEVEL_SCATTERING,
+            non_numba=[],
+        )
 
         self.C1 = C1
         self.C2 = C2
 
-    def __repr__(self):
+    def __repr__(self) -> str:
+        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
-        text += f"  - C1 {print_1d_array(self.C1)} [/eV^l]\n"
+        text += f"  - C1: {self.C1} [/eV^l]\n"
         text += f"  - C2: {self.C2}\n"
         return text
 
@@ -347,22 +463,25 @@ def __repr__(self):
 
 
 class DistributionEvaporation(DistributionBase):
-    # Annotations for Numba mode
-    label: str = "evaporation_distribution"
-    #
+    """Evaporation energy distribution."""
+
     nuclear_temperature: DataTable
     restriction_energy: float
 
     def __init__(
         self,
-        nuclear_temperature_energy_grid,
-        nuclear_temperature_value,
-        restriction_energy,
-        temperature_interpolations,
-        interpolation_boundaries,
-    ):
-        type_ = DISTRIBUTION_EVAPORATION
-        super().__init__(type_)
+        nuclear_temperature_energy_grid: ArrayLike,
+        nuclear_temperature_value: ArrayLike,
+        restriction_energy: float,
+        temperature_interpolations: int | Sequence[int],
+        interpolation_boundaries: Sequence[int] | None,
+    ) -> None:
+        """Create an evaporation distribution."""
+        super().__init__(
+            child_label="evaporation_distribution",
+            child_type=DISTRIBUTION_EVAPORATION,
+            non_numba=[],
+        )
 
         self.restriction_energy = restriction_energy
         self.nuclear_temperature = DataTable(
@@ -372,36 +491,46 @@ def __init__(
             interpolation_boundaries,
         )
 
-    def __repr__(self):
+    def __repr__(self) -> str:
+        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
         text += f"  - Restriction energy: {self.restriction_energy} [eV]\n"
-        text += f"  - Nuclear temperature {print_1d_array(self.nuclear_temperature.y)} [eV]\n"
-        text += f"  - Nuclear temperature energy grid {print_1d_array(self.nuclear_temperature.x)} [eV]\n"
+        text += (
+            "  - Nuclear temperature "
+            f"{print_1d_array(self.nuclear_temperature.y)} [eV]\n"
+        )
+        text += (
+            "  - Nuclear temperature energy grid "
+            f"{print_1d_array(self.nuclear_temperature.x)} [eV]\n"
+        )
         return text
 
 
 # ======================================================================================
-# Maxwellian distribution
+# Maxwellian
 # ======================================================================================
 
 
 class DistributionMaxwellian(DistributionBase):
-    # Annotations for Numba mode
-    label: str = "maxwellian_distribution"
-    #
+    """Maxwellian energy distribution."""
+
     nuclear_temperature: DataTable
     restriction_energy: float
 
     def __init__(
         self,
-        nuclear_temperature_energy_grid,
-        nuclear_temperature_value,
-        restriction_energy,
-        temperature_interpolations,
-        interpolation_boundaries,
-    ):
-        type_ = DISTRIBUTION_MAXWELLIAN
-        super().__init__(type_)
+        nuclear_temperature_energy_grid: ArrayLike,
+        nuclear_temperature_value: ArrayLike,
+        restriction_energy: float,
+        temperature_interpolations: int | Sequence[int],
+        interpolation_boundaries: Sequence[int] | None,
+    ) -> None:
+        """Create a Maxwellian distribution."""
+        super().__init__(
+            child_label="maxwellian_distribution",
+            child_type=DISTRIBUTION_MAXWELLIAN,
+            non_numba=[],
+        )
 
         self.restriction_energy = restriction_energy
         self.nuclear_temperature = DataTable(
@@ -411,11 +540,18 @@ def __init__(
             interpolation_boundaries,
         )
 
-    def __repr__(self):
+    def __repr__(self) -> str:
+        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
         text += f"  - Restriction energy: {self.restriction_energy} [eV]\n"
-        text += f"  - Nuclear temperature {print_1d_array(self.nuclear_temperature.y)} [eV]\n"
-        text += f"  - Nuclear temperature energy grid {print_1d_array(self.nuclear_temperature.x)} [eV]\n"
+        text += (
+            "  - Nuclear temperature "
+            f"{print_1d_array(self.nuclear_temperature.y)} [eV]\n"
+        )
+        text += (
+            "  - Nuclear temperature energy grid "
+            f"{print_1d_array(self.nuclear_temperature.x)} [eV]\n"
+        )
         return text
 
 
@@ -425,9 +561,8 @@ def __repr__(self):
 
 
 class DistributionKalbachMann(DistributionBase):
-    # Annotations for Numba mode
-    label: str = "kalbach_mann_distribution"
-    #
+    """Kalbach-Mann correlated energy-angle distribution."""
+
     energy: NDArray[float64]
     offset: NDArray[int64]
     energy_out: NDArray[float64]
@@ -437,29 +572,45 @@ class DistributionKalbachMann(DistributionBase):
     angular_slope: NDArray[float64]
 
     def __init__(
-        self, energy, offset, energy_out, pdf, precompound_factor, angular_slope
-    ):
-        type_ = DISTRIBUTION_KALBACH_MANN
-        super().__init__(type_)
-
-        self.energy = energy
-        self.offset = offset
-
-        self.energy_out = energy_out
-        self.pdf = pdf
+        self,
+        energy: ArrayLike,
+        offset: ArrayLike,
+        energy_out: ArrayLike,
+        pdf: ArrayLike,
+        precompound_factor: ArrayLike,
+        angular_slope: ArrayLike,
+    ) -> None:
+        """Create a Kalbach-Mann distribution."""
+        super().__init__(
+            child_label="kalbach_mann_distribution",
+            child_type=DISTRIBUTION_KALBACH_MANN,
+            non_numba=[],
+        )
 
-        self.precompound_factor = precompound_factor
-        self.angular_slope = angular_slope
+        self.energy = np.asarray(energy, dtype=float64)
+        self.offset = np.asarray(offset, dtype=int64)
+        self.energy_out = np.asarray(energy_out, dtype=float64)
+        pdf_array = np.asarray(pdf, dtype=float64)
+        self.precompound_factor = np.asarray(
+            precompound_factor,
+            dtype=float64,
+        )
+        self.angular_slope = np.asarray(angular_slope, dtype=float64)
 
-        self.pdf, self.cdf = multi_cdf_from_pdf(offset, energy_out, pdf)
+        self.pdf, self.cdf = multi_cdf_from_pdf(
+            self.offset,
+            self.energy_out,
+            pdf_array,
+        )
 
-    def __repr__(self):
+    def __repr__(self) -> str:
+        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
         text += f"  - grid {print_1d_array(self.energy)} [eV]\n"
         text += f"  - offset {print_1d_array(self.offset)}\n"
         text += f"  - energy {print_1d_array(self.energy_out)} [eV]\n"
         text += f"  - energy-pdf {print_1d_array(self.pdf)} [/eV]\n"
-        text += f"  - precompound factor {print_1d_array(self.precompound_factor)}\n"
+        text += "  - precompound factor " f"{print_1d_array(self.precompound_factor)}\n"
         text += f"  - angular slope {print_1d_array(self.angular_slope)}\n"
         return text
 
@@ -470,118 +621,160 @@ def __repr__(self):
 
 
 class DistributionTabulatedEnergyAngle(DistributionBase):
-    # Annotations for Numba mode
-    label: str = "tabulated_energy_angle_distribution"
-    #
+    """Tabulated correlated energy-angle distribution."""
+
     energy: NDArray[float64]
     offset: NDArray[int64]
     energy_out: NDArray[float64]
     pdf: NDArray[float64]
     cdf: NDArray[float64]
-    cosine_offset_: NDArray[int64]  # "cosine_offset" is reserved to describe "cosine"
+    cosine_offset_: NDArray[int64]
     cosine: NDArray[float64]
     cosine_pdf: NDArray[float64]
     cosine_cdf: NDArray[float64]
 
     def __init__(
-        self, energy, offset, energy_out, pdf, cosine_offset, cosine, cosine_pdf
-    ):
-        type_ = DISTRIBUTION_TABULATED_ENERGY_ANGLE
-        super().__init__(type_)
-
-        self.energy = energy
-        self.offset = offset
+        self,
+        energy: ArrayLike,
+        offset: ArrayLike,
+        energy_out: ArrayLike,
+        pdf: ArrayLike,
+        cosine_offset: ArrayLike,
+        cosine: ArrayLike,
+        cosine_pdf: ArrayLike,
+    ) -> None:
+        """Create a tabulated correlated energy-angle distribution."""
+        super().__init__(
+            child_label="tabulated_energy_angle_distribution",
+            child_type=DISTRIBUTION_TABULATED_ENERGY_ANGLE,
+            non_numba=[],
+        )
 
-        self.energy_out = energy_out
-        self.pdf = pdf
-        self.cosine_offset_ = cosine_offset
+        self.energy = np.asarray(energy, dtype=float64)
+        self.offset = np.asarray(offset, dtype=int64)
+        self.energy_out = np.asarray(energy_out, dtype=float64)
+        pdf_array = np.asarray(pdf, dtype=float64)
+        self.cosine_offset_ = np.asarray(cosine_offset, dtype=int64)
+        self.cosine = np.asarray(cosine, dtype=float64)
+        cosine_pdf_array = np.asarray(cosine_pdf, dtype=float64)
+
+        self.pdf, self.cdf = multi_cdf_from_pdf(
+            self.offset,
+            self.energy_out,
+            pdf_array,
+        )
 
-        self.cosine = cosine
-        self.cosine_pdf = cosine_pdf
+        self.cosine_pdf = cosine_pdf_array.copy()
+        self.cosine_cdf = np.zeros_like(self.cosine_pdf)
 
-        self.pdf, self.cdf = multi_cdf_from_pdf(offset, energy_out, pdf)
+        for i in range(len(self.offset)):
+            energy_start = self.offset[i]
 
-        self.cosine_cdf = np.zeros_like(self.cosine_pdf)
-        for i in range(len(offset)):
-            start = offset[i]
-            if i + 1 < len(offset):
-                end = offset[i + 1]
+            if i + 1 < len(self.offset):
+                energy_stop = self.offset[i + 1]
             else:
-                end = len(cosine)
-            inner_offset = cosine_offset[start:end]
+                energy_stop = len(self.energy_out)
+
+            inner_offset = self.cosine_offset_[energy_start:energy_stop]
+
+            if len(inner_offset) == 0:
+                print_error(
+                    "Each incident-energy table must reference at least one "
+                    "cosine distribution."
+                )
+
+            cosine_start = inner_offset[0]
 
-            start = inner_offset[0]
-            if i + 1 < len(offset):
-                end = cosine_offset[end]
+            if i + 1 < len(self.offset):
+                cosine_stop = self.cosine_offset_[energy_stop]
             else:
-                end = len(cosine)
+                cosine_stop = len(self.cosine)
 
-            inner_offset_local = inner_offset - inner_offset[0]
-            self.cosine_pdf[start:end], self.cosine_cdf[start:end] = multi_cdf_from_pdf(
-                inner_offset_local, cosine[start:end], cosine_pdf[start:end]
+            inner_offset_local = inner_offset - cosine_start
+
+            (
+                self.cosine_pdf[cosine_start:cosine_stop],
+                self.cosine_cdf[cosine_start:cosine_stop],
+            ) = multi_cdf_from_pdf(
+                inner_offset_local,
+                self.cosine[cosine_start:cosine_stop],
+                cosine_pdf_array[cosine_start:cosine_stop],
             )
 
-    def __repr__(self):
+    def __repr__(self) -> str:
+        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
         text += f"  - grid {print_1d_array(self.energy)} [eV]\n"
         text += f"  - offset {print_1d_array(self.offset)}\n"
         text += f"  - energy {print_1d_array(self.energy_out)} [eV]\n"
         text += f"  - energy-pdf {print_1d_array(self.pdf)} [/eV]\n"
-        text += f"  - cosine-offset {print_1d_array(self.cosine_offset_)}\n"
+        text += "  - cosine-offset " f"{print_1d_array(self.cosine_offset_)}\n"
         text += f"  - cosine {print_1d_array(self.cosine)}\n"
         text += f"  - cosine-pdf {print_1d_array(self.cosine_pdf)}\n"
         return text
 
 
 # ======================================================================================
-# N-Body
+# N-body
 # ======================================================================================
 
 
 class DistributionNBody(DistributionBase):
-    """
-    N-body energy distribution represented by a tabulated PDF and CDF.
+    """N-body energy distribution represented by a tabulated PDF and CDF.
 
-    The input PDF is normalized internally, and the corresponding CDF is
-    constructed for sampling.
+    The input probability density is normalized internally, and the
+    corresponding cumulative distribution is generated for sampling.
     """
 
-    # Annotations for Numba mode
-    label: str = "nbody_distribution"
-    #
     pdf: DataTable
 
     def __init__(
         self,
-        values: NDArray[float64],
-        probabilities: NDArray[float64],
+        values: ArrayLike,
+        probabilities: ArrayLike,
     ) -> None:
-        """
-        Construct an N-body distribution from tabulated PDF values.
+        """Create an N-body distribution.
 
         Parameters
         ----------
-        value : ndarray
+        values : array_like
             Tabulated sample values.
-        probabilities : ndarray
-            Probability density values at the tabulated sample values. The
-            values do not need to be normalized.
+
+        probabilities : array_like
+            Probability densities at the sample values. The values do not need
+            to be normalized.
         """
+        super().__init__(
+            child_label="nbody_distribution",
+            child_type=DISTRIBUTION_N_BODY,
+            non_numba=[],
+        )
+
+        value_array = np.asarray(values, dtype=float64)
+        probability_array = np.asarray(probabilities, dtype=float64)
 
-        type_ = DISTRIBUTION_N_BODY
-        super().__init__(type_)
+        if value_array.ndim != 1:
+            print_error("values must be one-dimensional.")
+        if probability_array.ndim != 1:
+            print_error("probabilities must be one-dimensional.")
+        if len(value_array) != len(probability_array):
+            print_error("values and probabilities must have the same length.")
 
-        pdf_normalized, cdf_normalized = cdf_from_pdf(values, probabilities)
+        pdf_normalized, cdf_normalized = cdf_from_pdf(
+            value_array,
+            probability_array,
+        )
 
         self.pdf = DataTable(
-            values,
+            value_array,
             pdf_normalized,
             INTERPOLATION_LINEAR,
             aux=cdf_normalized,
         )
 
-    def __repr__(self):
+    def __repr__(self) -> str:
+        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
-        text += f"  - value {print_1d_array(self.value)}\n"
-        text += f"  - pdf {print_1d_array(self.pdf)}\n"
+        text += f"  - value {print_1d_array(self.pdf.x)}\n"
+        text += f"  - pdf {print_1d_array(self.pdf.y)}\n"
         return text

From aae2cd071a4814bc46fe49aa1b4e6a1d618069bf Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 16 Jul 2026 11:12:06 +0700
Subject: [PATCH 013/202] rename stale workflow

---
 .github/workflows/{mark_stale_issues.yml => stale-issues.yml} | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)
 rename .github/workflows/{mark_stale_issues.yml => stale-issues.yml} (94%)

diff --git a/.github/workflows/mark_stale_issues.yml b/.github/workflows/stale-issues.yml
similarity index 94%
rename from .github/workflows/mark_stale_issues.yml
rename to .github/workflows/stale-issues.yml
index 697123c3b..2c3163b59 100644
--- a/.github/workflows/mark_stale_issues.yml
+++ b/.github/workflows/stale-issues.yml
@@ -17,7 +17,7 @@ jobs:
         with:
           days-before-issue-stale: 90
           days-before-issue-close: -1
-          stale-issue-label: stale
+          stale-issue-label: "status: stale"
           stale-issue-message: >
             This issue has had no activity in the past 90 days and has been marked as stale.
             If this issue is still relevant, please leave a comment with any updates so we know it still needs attention.

From 04470952a30267cec0d10b7948c1a4e4b1c78827 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 16 Jul 2026 11:13:08 +0700
Subject: [PATCH 014/202] use shared organization workflow

---
 .github/workflows/stale-issues.yml | 17 +----------------
 1 file changed, 1 insertion(+), 16 deletions(-)

diff --git a/.github/workflows/stale-issues.yml b/.github/workflows/stale-issues.yml
index 2c3163b59..cf51fcea7 100644
--- a/.github/workflows/stale-issues.yml
+++ b/.github/workflows/stale-issues.yml
@@ -7,22 +7,7 @@ on:
 
 permissions:
   issues: write
-  pull-requests: write
 
 jobs:
   stale:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/stale@v9
-        with:
-          days-before-issue-stale: 90
-          days-before-issue-close: -1
-          stale-issue-label: "status: stale"
-          stale-issue-message: >
-            This issue has had no activity in the past 90 days and has been marked as stale.
-            If this issue is still relevant, please leave a comment with any updates so we know it still needs attention.
-            Otherwise, maintainers may close this issue in the future. Thank you for your contribution!
-
-          # Do not stale PRs
-          days-before-pr-stale: -1
-          days-before-pr-close: -1
+    uses: mcdc-project/.github/.github/workflows/stale-issues.yml@main

From c478f5c9aac62252b62a009cfbd4b038c56d5a1c Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 18 Jul 2026 15:15:12 +0700
Subject: [PATCH 015/202] update material, particle, settings, simulation,
 universe

---
 mcdc/object_/material.py   | 42 +++++++++++++++++++++++---------------
 mcdc/object_/particle.py   |  5 ++---
 mcdc/object_/settings.py   |  6 ++----
 mcdc/object_/simulation.py | 17 ++++++++++++++-
 mcdc/object_/universe.py   | 10 ++-------
 5 files changed, 48 insertions(+), 32 deletions(-)

diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 72e2ab0a6..8d7636edd 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -21,14 +21,23 @@
 
 
 class MaterialBase(MCDCPolymorphic):
-    # Annotations for Numba mode
-    label: str = "material"
-    #
     name: str
     fissionable: bool
 
-    def __init__(self, type_, name):
-        super().__init__(type_)
+    def __init__(
+        self,
+        name: str,
+        child_label: str,
+        child_type: int,
+        non_numba: list[str],
+    ) -> None:
+        """Initialize material base framework metadata."""
+        super().__init__(
+            label="material",
+            child_label=child_label,
+            child_type=child_type,
+            non_numba=non_numba,
+        )
 
         # Set name
         if name == "":
@@ -88,10 +97,6 @@ class Material(MaterialBase):
     mcdc.MaterialMG : Creates a multigroup material.
     """
 
-    # Annotations for Numba mode
-    label: str = "native_material"
-    non_numba: list[str] = ["nuclide_composition", "element_composition"]
-    #
     nuclide_composition: dict[Nuclide, float]
     element_composition: dict[Element, float]
     #
@@ -107,8 +112,12 @@ def __init__(
         element_composition: dict[str, float] = {},
         temperature: float = 293.6,
     ):
-        type_ = MATERIAL
-        super().__init__(type_, name)
+        super().__init__(
+            name,
+            child_label="native_material",
+            child_type=MATERIAL,
+            non_numba=["nuclide_composition", "element_composition"],
+        )
 
         # Temperature
         self.temperature = temperature
@@ -271,9 +280,6 @@ class MaterialMG(MaterialBase):
     mcdc.Material : Creates a continuous-energy material.
     """
 
-    # Annotations for Numba mode
-    label: str = "multigroup_material"
-    #
     G: int
     J: int
     mgxs_speed: Annotated[NDArray[float64], ("G",)]
@@ -305,8 +311,12 @@ def __init__(
         speed: NDArray[float64] | NoneType = None,
         decay_rate: NDArray[float64] | NoneType = None,
     ):
-        type_ = MATERIAL_MG
-        super().__init__(type_, name)
+        super().__init__(
+            name,
+            child_label="multigroup_material",
+            child_type=MATERIAL,
+            non_numba=[],
+        )
 
         # Energy group size
         if capture is not None:
diff --git a/mcdc/object_/particle.py b/mcdc/object_/particle.py
index 477ac7f7f..5fd7f3fb9 100644
--- a/mcdc/object_/particle.py
+++ b/mcdc/object_/particle.py
@@ -46,13 +46,12 @@ class Particle(ParticleData):
 
 
 class ParticleBank(MCDCBase):
-    label: str = "particle_bank"
-    non_numba: list[str] = ["particles"]
     particles: list[ParticleData] = []
     size: Annotated[NDArray[int64], (1,)]
     tag: str = ""
 
     def __init__(self, tag):
-        super().__init__()
+        """Initialize particle bank framework metadata."""
+        super().__init__(label="particle_bank", non_numba=["particles"])
         self.tag = tag
         self.size = np.zeros(1, dtype=int64)
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index 869968e92..d650fc4eb 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -20,9 +20,6 @@
 
 @dataclass
 class Settings(MCDCBase):
-    # Annotations for Numba mode
-    label: str = "settings"
-
     # Basic
     N_particle: int = 0
     N_batch: int = 1
@@ -73,7 +70,8 @@ class Settings(MCDCBase):
     gpu_storage: int = GPU_STORAGE_SEPARATE
 
     def __post_init__(self):
-        super().__init__()
+        """Initialize settings framework metadata."""
+        super().__init__(label="settings", non_numba=[])
 
     def set_time_census(self, time, tally_frequency=None):
         # Make sure that the time grid points are sorted
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index d7dbfde56..6286e831a 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -204,7 +204,7 @@ def __init__(self, name: str = "") -> None:
         self.surfaces = []
         self.regions = []
         self.cells = []
-        self.universes = [Universe("Root Universe", root=True)]
+        self.universes = [Universe("Root Universe")]
         self.lattices = []
         self.meshes = []
 
@@ -339,6 +339,21 @@ def set_tallies(self, tallies: Sequence[Tally]) -> None:
         self.tallies = list(tallies)
         self.compiled = False
 
+    def set_root_universe(self, cells: Sequence[Cell]) -> None:
+        """Set the cells of the root universe.
+
+        Parameters
+        ----------
+        cells : Sequence[Cell]
+            Cells contained directly in the root universe.
+
+        Notes
+        -----
+        The root universe occupies index ``0`` in the compiled universe array.
+        Geometry tracking begins from this universe by default.
+        """
+        self.universes[0].cells = list(cells)
+
     # ==================================================================================
     # Operations
     # ==================================================================================
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index 789757693..e1b9556dd 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -47,18 +47,12 @@ class Universe(MCDCObject):
     """
 
     # Annotations for Numba mode
-    label: str = "universe"
-    #
     name: str
     cells: list[Cell]
 
-    def __init__(self, name: str = "", cells: list[Cell] = [], root: bool = False):
+    def __init__(self, name: str = "", cells: list[Cell] = []):
         # Custom treatment for root universe
-        if root:
-            super().__init__()
-            self.ID = 0
-        else:
-            super().__init__()
+        super().__init__(label="universe", non_numba=[])
 
         # Set name
         if name == "":

From 5ce8f8874c8a4275d89daac10a195f121c28baf8 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 18 Jul 2026 15:28:58 +0700
Subject: [PATCH 016/202] update cell, material, mesh, source, surface

---
 mcdc/object_/cell.py     |  6 ++----
 mcdc/object_/material.py |  2 +-
 mcdc/object_/mesh.py     | 41 +++++++++++++++++++++++++---------------
 mcdc/object_/source.py   |  5 +----
 mcdc/object_/surface.py  |  6 ++----
 5 files changed, 32 insertions(+), 28 deletions(-)

diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 55c24b4af..d80c25aab 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -45,7 +45,7 @@ class Region(MCDCObject):
     B: Region | int | NoneType
 
     def __init__(self, type_, A, B):
-        super().__init__()
+        super().__init__(label="region", non_numba=[])
 
         self.type = type_
         self.A = A
@@ -123,9 +123,7 @@ def __init__(
         rotation: Sequence[float] = [0.0, 0.0, 0.0],
     ):
         # MC/DC framework metadata
-        super().__init__()
-        self.label = "cell"
-        self.non_numba += ["region", "fill", "region_RPN"]
+        super().__init__(label="cell", non_numba=["region", "fill", "region_RPN"])
 
         # Set name
         if name == "":
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 8d7636edd..4213b7693 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -314,7 +314,7 @@ def __init__(
         super().__init__(
             name,
             child_label="multigroup_material",
-            child_type=MATERIAL,
+            child_type=MATERIAL_MG,
             non_numba=[],
         )
 
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index 1d68054ee..9e97f4ecf 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -16,17 +16,26 @@
 
 
 class MeshBase(MCDCPolymorphic):
-    # Annotations for Numba mode
-    label: str = "mesh"
-    #
     name: str
     N_bin: int
     Nx: int
     Ny: int
     Nz: int
 
-    def __init__(self, type_, name):
-        super().__init__(type_)
+    def __init__(
+        self,
+        name: str,
+        child_label: str,
+        child_type: int,
+        non_numba: list[str],
+    ) -> None:
+        """Initialize mesh base framework metadata."""
+        super().__init__(
+            label="mesh",
+            child_label=child_label,
+            child_type=child_type,
+            non_numba=non_numba,
+        )
 
         # Set name
         if name == "":
@@ -84,9 +93,6 @@ class MeshUniform(MeshBase):
     mcdc.TallyMesh : Creates a tally on a mesh.
     """
 
-    # Annotations for Numba mode
-    label: str = "uniform_mesh"
-    #
     x0: float
     dx: float
     Nx: int
@@ -104,8 +110,12 @@ def __init__(
         y: tuple[float, float, int] = (-INF, 2 * INF, 1),
         z: tuple[float, float, int] = (-INF, 2 * INF, 1),
     ):
-        type_ = MESH_UNIFORM
-        super().__init__(type_, name)
+        super().__init__(
+            name,
+            child_label="uniform mesh",
+            child_type=MESH_UNIFORM,
+            non_numba=[],
+        )
 
         # Set the grid
         self.x0 = x[0]
@@ -160,9 +170,6 @@ class MeshStructured(MeshBase):
     mcdc.TallyMesh : Creates a tally on a mesh.
     """
 
-    # Annotations for Numba mode
-    label: str = "structured_mesh"
-    #
     x: NDArray[float64]
     y: NDArray[float64]
     z: NDArray[float64]
@@ -174,8 +181,12 @@ def __init__(
         y: Sequence[float] | NDArray[float64] = np.array([-INF, INF]),
         z: Sequence[float] | NDArray[float64] = np.array([-INF, INF]),
     ):
-        type_ = MESH_STRUCTURED
-        super().__init__(type_, name)
+        super().__init__(
+            name,
+            child_label="structured mesh",
+            child_type=MESH_STRUCTURED,
+            non_numba=[],
+        )
 
         # Set the grid
         self.x = np.array(x)
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 47ba9370b..d4d8920fe 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -164,9 +164,6 @@ class Source(MCDCObject):
     ... )
     """
 
-    # Annotations for Numba mode
-    label: str = "source"
-    #
     name: str
     # Position
     point_source: bool
@@ -226,7 +223,7 @@ def __init__(
         probability: float = 1.0,
     ):
 
-        super().__init__()
+        super().__init__(label="source", non_numba=[])
 
         # Set name
         if name == "":
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index edb1886a8..533749836 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -101,9 +101,6 @@ class Surface(MCDCObject):
         Human-readable boundary condition name.
     """
 
-    # Annotations for Numba mode
-    label: str = "surface"
-    #
     type: int
     name: str
     boundary_condition: int
@@ -135,7 +132,8 @@ class Surface(MCDCObject):
     tallies: list[TallySurfaceCrossing]
 
     def __init__(self, type_, name, boundary_condition):
-        super().__init__()
+        """Initialize surface framework metadata."""
+        super().__init__(label="surface", non_numba=[])
 
         # Type and name
         self.type = type_

From c01eaa5a797c646481804f35ebacf53b558cc4d3 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 18 Jul 2026 16:11:15 +0700
Subject: [PATCH 017/202] update tally

---
 mcdc/object_/tally.py | 38 ++++++++++++++++++++------------------
 1 file changed, 20 insertions(+), 18 deletions(-)

diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 5ec21df91..7c1d4bc99 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -313,10 +313,6 @@ def decode_score_type(type_, lower_case=False):
 
 
 class TallySurfaceCrossing(Tally):
-    # Annotations for Numba mode
-    label: str = "surface_crossing_tally"
-    non_numba: list[str] = ["surface", "cell"]
-
     # Spatial filters
     surface: Surface | NoneType
     surface_filtered: bool
@@ -337,8 +333,12 @@ def __init__(
         energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
-        type_ = TALLY_SURFACE_CROSSING
-        super(Tally, self).__init__(type_)
+        super(Tally, self).__init__(
+            label="tally",
+            child_label="surface_crossing_tally",
+            child_type=TALLY_SURFACE_CROSSING,
+            non_numba=["surface", "cell"],
+        )
         super().__init__(
             name,
             scores,
@@ -397,10 +397,6 @@ def __repr__(self):
 
 
 class TallyCollision(Tally):
-    # Annotations for Numba mode
-    label: str = "collision_tally"
-    non_numba: list[str] = ["cell", "mesh"]
-
     # Spatial filters
     cell: Cell | NoneType
     cell_filtered: bool
@@ -427,12 +423,17 @@ def __init__(
         energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
-        type_ = TALLY_COLLISION
         spatial_shape = None
         if mesh is not None:
             spatial_shape = (mesh.Nx, mesh.Ny, mesh.Nz)
 
-        super(Tally, self).__init__(type_)
+        super(Tally, self).__init__(
+            label="tally",
+            child_label="collision_tally",
+            child_type=TALLY_COLLISION,
+            non_numba=["cell", "mesh"],
+        )
+
         super().__init__(
             name,
             scores,
@@ -508,10 +509,6 @@ def __repr__(self):
 
 
 class TallyTracklength(Tally):
-    # Annotations for Numba mode
-    label: str = "tracklength_tally"
-    non_numba: list[str] = ["cell", "mesh"]
-
     # Spatial filters
     cell: Cell | NoneType
     cell_filtered: bool
@@ -538,12 +535,17 @@ def __init__(
         energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
-        type_ = TALLY_TRACKLENGTH
         spatial_shape = None
         if mesh is not None:
             spatial_shape = (mesh.Nx, mesh.Ny, mesh.Nz)
 
-        super(Tally, self).__init__(type_)
+        super(Tally, self).__init__(
+            label="tally",
+            child_label="tracklength_tally",
+            child_type=TALLY_TRACKLENGTH,
+            non_numba=["cell", "mesh"],
+        )
+
         super().__init__(
             name,
             scores,

From f3c1673dcb7d24ef43503acaf90fb8bba80e8cc3 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 19 Jul 2026 07:22:30 +0700
Subject: [PATCH 018/202] wip

---
 mcdc/code_factory/python_objects_compiler.py |  76 +++
 mcdc/main.py                                 | 248 +--------
 mcdc/object_/base.py                         | 510 +++++++------------
 mcdc/object_/cell.py                         |  29 +-
 mcdc/object_/material.py                     |   2 +-
 mcdc/object_/simulation.py                   | 119 ++---
 6 files changed, 319 insertions(+), 665 deletions(-)
 create mode 100644 mcdc/code_factory/python_objects_compiler.py

diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
new file mode 100644
index 000000000..eda678305
--- /dev/null
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -0,0 +1,76 @@
+from mcdc.object_.base import MCDCObject
+from mcdc.object_.simulation import Simulation
+
+
+def compile_simulation(simulationPy: Simulation):
+    from mcdc.object_.base import MCDC_OBJECT_LABELS
+    from mcdc.object_.data import DataNone
+    from mcdc.object_.distribution import DistributionNone
+
+    # Reset derived object lists
+    simulationPy._reset_object_lists()
+
+    # Object IDs counter
+    # TODO: Remove
+    next_ID = dict.fromkeys(MCDC_OBJECT_LABELS, 0)
+
+    # Compile reserved objects
+    compile_object(simulationPy.root_universe, simulationPy)
+
+    # Root universe
+    simulationPy.universes.append(simulationPy.root_universe)
+
+    # "None" objects
+    simulationPy.data.append(DataNone())
+    simulationPy.distributions.append(DistributionNone())
+
+    # Assign IDs
+    assign_IDs(simulationPy.data[0], next_ID, compile_ID)
+    assign_IDs(simulationPy.distributions[0], next_ID, compile_ID)
+    assign_IDs(simulationPy.universes[0], next_ID, compile_ID)
+
+    # ==================================================================================
+    # Compile model
+    # ==================================================================================
+
+    root_universe = simulationPy.universes[0]
+
+    # Loop over root universe cells
+    for cell in root_universe.cells:
+        assign_IDs(cell, next_ID, compile_ID)
+
+        # Fill
+        fill = cell.fill
+
+        ## Material
+        if isinstance(fill, MaterialBase):
+            simulationPy.materials.append(fill)
+            assign_IDs(fill, next_ID, compile_ID)
+
+        ## Universe
+        elif isinstance(fill, Universe):
+            simulationPy.universes.append(fill)
+            assign_IDs(fill, next_ID, compile_ID)
+
+        ## Lattice
+        elif isinstance(fill, Lattice):
+            simulationPy.lattices.append(fill)
+            assign_IDs(fill, next_ID, compile_ID)
+
+
+def compile_object(object_: MCDCObject, simulationPy: Simulation) -> None:
+    object_type = type(object_)
+    print(object_type)
+    matching_members = {
+        k: v
+        for k, v in vars(simulationPy).items()
+        if isinstance(v, list) and all(isinstance(x, object_type) for x in v)
+    }
+    print(matching_members)
+    exit()
+
+    # Assign ID
+
+    object_.ID = next_ID[object_.label]
+    object_.compile_ID = compile_ID
+    next_ID[object_.label] += 1
diff --git a/mcdc/main.py b/mcdc/main.py
index 8db600c7d..8425d857c 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -1,5 +1,7 @@
+from mcdc.object_.material import MaterialBase
 from mcdc.object_.simulation import Simulation
 from mcdc.object_.base import MCDCObject
+from mcdc.object_.universe import Lattice, Universe
 
 # ======================================================================================
 # Run Simulation
@@ -319,252 +321,6 @@ def prepare(simulationPy):
     return simulation_container, data
 
 
-# ======================================================================================
-# Compile Simulation
-# ======================================================================================
-
-
-def compile_simulation(simulationPy: Simulation, compile_ID: int):
-
-    # ==================================================================================
-    # Reset derived object lists
-    # ==================================================================================
-
-    # Physics
-    simulationPy.data = [simulationPy.data[0]]  # Keep None
-    simulationPy.distributions = [simulationPy.distributions[0]]  # Keep None
-    simulationPy.neutron_reactions = []
-    simulationPy.electron_reactions = []
-    simulationPy.nuclides = []
-    simulationPy.elements = []
-    simulationPy.materials = []
-
-    # Geometry
-    simulationPy.surfaces = []
-    simulationPy.regions = []
-    simulationPy.cells = []
-    simulationPy.universes = [simulationPy.universes[0]]  # Keep root universe
-    simulationPy.lattices = []
-    simulationPy.meshes = []
-
-    # ==================================================================================
-    # Object IDs
-    # ==================================================================================
-
-    next_ID = {
-        "data": 0,
-        "distribution": 0,
-        "neutron_reaction": 0,
-        "electron_reaction": 0,
-        "nuclide": 0,
-        "element": 0,
-        "material": 0,
-        "surface": 0,
-        "region": 0,
-        "cell": 0,
-        "universe": 0,
-        "lattice": 0,
-        "mesh": 0,
-    }
-
-    # ==================================================================================
-    # Assign ID to reserved objects
-    # ==================================================================================
-
-    set_IDs(simulationPy.data[0], next_ID, compile_ID)
-    set_IDs(simulationPy.distributions[0], next_ID, compile_ID)
-    set_IDs(simulationPy.universes[0], next_ID, compile_ID)
-
-    # ==================================================================================
-    # Compile root universe cells
-    # ==================================================================================
-
-    root_universe = simulationPy.universes[0]
-
-    for cell in root_universe.cells:
-        set_IDs(cell, next_ID, compile_ID)
-
-    # ==================================================================================
-    # Set material data as needed
-    # ==================================================================================
-
-    # Set material compositions based on transported particles
-    for material in simulationPy.materials:
-        if not isinstance(material, Material):
-            continue
-
-        if settings.neutron_transport and len(material.nuclides) == 0:
-            set_nuclides_from_elements(material)
-
-        if settings.electron_transport and len(material.elements) == 0:
-            set_elements_from_nuclides(material)
-
-    # Set nuclear and atomic data for transported particles
-    if settings.neutron_transport:
-        for nuclide in simulationPy.nuclides:
-            nuclide.set_neutron_data(simulationPy)
-
-        for material in simulationPy.materials:
-            if isinstance(material, Material):
-                update_fissionable_from_nuclides(material)
-
-    if settings.electron_transport:
-        for element in simulationPy.elements:
-            element.set_electron_data()
-
-    # Set physics mode
-    if len(simulationPy.materials) == 0:
-        # Default physics in dummy mode
-        settings.neutron_multigroup_mode = True
-    else:
-        settings.neutron_multigroup_mode = isinstance(
-            simulationPy.materials[0], MaterialMG
-        )
-
-    # ==================================================================================
-    # Adjust simulation parameters as needed
-    # ==================================================================================
-
-    # Reset time grid size of all tallies if census-based tally is desired
-    if settings.use_census_based_tally:
-        N_bin = settings.census_tally_frequency
-        for tally in simulationPy.tallies:
-            tally._use_census_based_tally(N_bin)
-
-    # Normalize source probability
-    norm = 0.0
-    for source in simulationPy.sources:
-        norm += source.probability
-    for source in simulationPy.sources:
-        source.probability /= norm
-
-    # Create root universe if not defined
-    if len(simulationPy.universes[0].cells) == 0:
-        simulationPy.universes[0].cells = simulationPy.cells
-
-    # Initial guess
-    simulationPy.k_eff = settings.k_init
-
-    # Activate tally scoring for fixed-source
-    if not settings.neutron_eigenvalue_mode:
-        simulationPy.cycle_active = True
-    # All active eigenvalue cycle?
-    elif settings.N_inactive == 0:
-        simulationPy.cycle_active = True
-
-    # ==================================================================================
-    # Set particle bank sizes
-    # ==================================================================================
-
-    # Some sizes
-    N_particle = settings.N_particle
-    N_work = math.ceil(N_particle / MPI.COMM_WORLD.Get_size())
-    N_census = settings.N_census
-
-    # Determine bank size
-    if settings.neutron_eigenvalue_mode or N_census == 1:
-        settings.future_bank_buffer_ratio = 0.0
-    if not settings.neutron_eigenvalue_mode and N_census == 1:
-        settings.census_bank_buffer_ratio = 0.0
-        settings.source_bank_buffer_ratio = 0.0
-    size_active = settings.active_bank_buffer
-    size_census = int((settings.census_bank_buffer_ratio) * N_work)
-    size_source = int((settings.source_bank_buffer_ratio) * N_work)
-    size_future = int((settings.future_bank_buffer_ratio) * N_work)
-
-    # Set bank size
-    simulationPy.bank_active.size[0] = size_active
-    simulationPy.bank_census.size[0] = size_census
-    simulationPy.bank_source.size[0] = size_source
-    simulationPy.bank_future.size[0] = size_future
-
-    # ==================================================================================
-    # Generate Numba-supported "Objects"
-    # ==================================================================================
-
-    from mcdc.code_factory.numba_objects_generator import generate_numba_objects
-    from mcdc.code_factory.literals_generator import make_literals
-
-    make_literals(simulationPy)
-
-    simulation_container, data = generate_numba_objects(simulationPy)
-    simulation = simulation_container[0]
-
-    # Reload mcdc getters and setters
-    import importlib
-    import mcdc.mcdc_get as mcdc_get
-    import mcdc.mcdc_set as mcdc_set
-
-    importlib.reload(mcdc_get)
-    importlib.reload(mcdc_set)
-
-    # ==================================================================================
-    # Adapt functions as needed
-    # ==================================================================================
-
-    # Pick physics model
-    import mcdc.transport.physics as physics
-
-    if settings.neutron_multigroup_mode:
-        physics.neutron.particle_speed = physics.neutron.multigroup.particle_speed
-        physics.neutron.macro_xs = physics.neutron.multigroup.macro_xs
-        physics.neutron.neutron_production_xs = (
-            physics.neutron.multigroup.neutron_production_xs
-        )
-        physics.neutron.collision = physics.neutron.multigroup.collision
-
-    # Pick Python-version RNG if needed
-    import mcdc.config as config
-    import mcdc.transport.rng as rng
-
-    if config.mode == "python":
-        rng.wrapping_add = rng.wrapping_add_python
-        rng.wrapping_mul = rng.wrapping_mul_python
-
-    # TODO: Find out why the following is needed to avoid circular import
-    import mcdc.transport.particle_bank as particle_bank_module
-
-    # ==================================================================================
-    # Source particles from file
-    # ==================================================================================
-    # TODO: Use parallel h5py, may need to compile for speed
-
-    import h5py
-
-    # All ranks, take turn
-    for i in range(simulation["mpi_size"]):
-        if simulation["mpi_rank"] == i:
-            if settings.use_source_file:
-                with h5py.File(settings.source_file_name, "r") as f:
-                    # Get source particle size
-                    N_particle = f["particles_size"][()]
-
-                    # Redistribute work
-                    mpi.distribute_work(N_particle, simulation)
-                    N_local = simulation["mpi_work_size"]
-                    start = simulation["mpi_work_start"]
-                    end = start + N_local
-
-                    # Add particles to source bank
-                    simulation["bank_source"]["particles"][:N_local] = f["particles"][
-                        start:end
-                    ]
-                    simulation["bank_source"]["size"] = N_local
-        MPI.COMM_WORLD.Barrier()
-
-    # ==================================================================================
-    # Finalize
-    # ==================================================================================
-
-    return simulation_container, data
-
-
-def set_IDs(object_: MCDCObject, next_ID: dict, compile_ID: int) -> None:
-    object_.ID = next_ID[object_.label]
-    object_.compile_ID = compile_ID
-    next_ID[object_.label] += 1
-
-
 # ======================================================================================
 # Misc.
 # ======================================================================================
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index 1d761db60..ffdde6c45 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -2,59 +2,14 @@
 
 
 class MCDCBase:
-    """Base class for all Python-side MC/DC objects.
-
-    ``MCDCBase`` provides functionality shared by framework objects,
-    including runtime type checking and common metadata.
-
-    Parameters
-    ----------
-    label : str
-        Framework label identifying the object category.
-
-    non_numba : list of str
-        Additional attribute names excluded from the compiled
-        representation.
-
-    Attributes
-    ----------
-    label : str
-        Framework label identifying the object category.
-
-    non_numba : list of str
-        Names of object attributes that are excluded from the compiled
-        representation.
-
-    Notes
-    -----
-    This class is the root of the Python-side MC/DC object hierarchy. It does
-    not directly correspond to objects stored in the compiled simulation.
-    """
-
     label: str
-    non_numba: list[str] = ["non_numba", "label"]
+    non_numba: list[str]
 
     def __init__(self, label: str, non_numba: list[str]):
-        """Initialize common framework metadata.
-
-        Parameters
-        ----------
-        label : str
-            Framework label identifying the object category.
-
-        non_numba : list of str
-            Additional attribute names excluded from the compiled
-            representation.
-        """
         self.label = label
         self.non_numba = ["label", "non_numba"] + non_numba
 
     def __setattr__(self, key, value):
-        """Assign an attribute with runtime type checking.
-
-        Attribute assignments are validated against the class type
-        annotations before being stored.
-        """
         hints = getattr(self.__class__, "__annotations__", {})
         if key in hints and not check_type(value, hints[key], self.__class__, self):
             print_error(f"{key} must be {hints[key]!r}, got {value!r}")
@@ -62,51 +17,10 @@ def __setattr__(self, key, value):
 
 
 class MCDCObject(MCDCBase):
-    """Base class for compiled MC/DC objects.
-
-    ``MCDCObject`` represents objects that are collected during simulation
-    compilation and assigned deterministic identifiers.
-
-    Parameters
-    ----------
-    label : str
-        Framework label identifying the object category.
-
-    non_numba : list of str
-        Additional attribute names excluded from the compiled representation.
-
-    Attributes
-    ----------
-    ID : int
-        Identifier of the object within its compiled collection. The default
-        value is ``-1`` until the object is collected during compilation.
-
-    compile_ID : int
-        Identifier of the compilation in which ``ID`` was assigned. The default
-        value is ``0`` until the object is collected during compilation.
-
-    Notes
-    -----
-    During compilation, each object receives a unique object identifier within
-    its collection and records the compilation in which the identifier was
-    assigned.
-    """
-
     ID: int
     compile_ID: int
 
     def __init__(self, label: str, non_numba: list[str]):
-        """Initialize compilation metadata.
-
-        Parameters
-        ----------
-        label : str
-            Framework label identifying the object category.
-
-        non_numba : list of str
-            Additional attribute names excluded from the compiled
-            representation.
-        """
         super().__init__(label, non_numba)
 
         self.ID = -1
@@ -115,48 +29,6 @@ def __init__(self, label: str, non_numba: list[str]):
 
 
 class MCDCPolymorphic(MCDCObject):
-    """Base class for polymorphic compiled MC/DC objects.
-
-    Polymorphic objects belong to object families identified by ``label``.
-    Within each family, concrete subclasses are identified by ``child_label``
-    and ``child_type``.
-
-    Parameters
-    ----------
-    label : str
-        Framework label identifying the object family.
-
-    child_label : str
-        Framework label identifying the concrete polymorphic subtype.
-
-    child_type : int
-        Integer identifier specifying the concrete polymorphic subtype.
-
-    non_numba : list of str
-        Additional attribute names excluded from the compiled representation.
-
-    Attributes
-    ----------
-    ID : int
-        Identifier of the object within its compiled collection. The default
-        value is ``-1`` until the object is collected during compilation.
-
-    compile_ID : int
-        Identifier of the compilation in which ``ID`` and ``child_ID`` were
-        assigned. The default value is ``0`` until compilation.
-
-    child_label : str
-        Framework label identifying the concrete polymorphic subtype.
-
-    child_type : int
-        Integer discriminator used to represent the concrete subtype in the
-        compiled model.
-
-    child_ID : int
-        Identifier of the object within its concrete polymorphic subtype. The
-        default value is ``-1`` until compilation.
-    """
-
     child_label: str
     child_type: int
     child_ID: int
@@ -168,23 +40,6 @@ def __init__(
         child_type: int,
         non_numba: list[str],
     ):
-        """Initialize polymorphic compilation metadata.
-
-        Parameters
-        ----------
-        label : str
-            Framework label identifying the object family.
-
-        child_label : str
-            Framework label identifying the concrete polymorphic subtype.
-
-        child_type : int
-            Integer identifier specifying the concrete polymorphic subtype.
-
-        non_numba : list of str
-            Additional attribute names excluded from the compiled
-            representation.
-        """
         super().__init__(label, non_numba)
 
         self.child_label = child_label
@@ -193,66 +48,62 @@ def __init__(
         self.non_numba += ["child_label"]
 
 
-# ======================================================================================
-# Helper functions
-# ======================================================================================
-
-
-def register_object(object_):
-    from mcdc.object_.simulation import simulation
-
-    from mcdc.object_.cell import Region, Cell
-    from mcdc.object_.universe import Universe, Lattice
-    from mcdc.object_.data import DataBase
-    from mcdc.object_.distribution import DistributionBase
-    from mcdc.object_.element import Element
-    from mcdc.object_.electron_reaction import ElectronReactionBase
-    from mcdc.object_.material import MaterialBase
-    from mcdc.object_.mesh import MeshBase
-    from mcdc.object_.nuclide import Nuclide
-    from mcdc.object_.neutron_reaction import NeutronReactionBase
-    from mcdc.object_.source import Source
-    from mcdc.object_.surface import Surface
-    from mcdc.object_.tally import Tally
-
-    object_list = []
-    if isinstance(object_, Cell):
-        object_list = simulation.cells
-    elif isinstance(object_, DataBase):
-        object_list = simulation.data
-    elif isinstance(object_, DistributionBase):
-        object_list = simulation.distributions
-    elif isinstance(object_, Lattice):
-        object_list = simulation.lattices
-    elif isinstance(object_, MaterialBase):
-        object_list = simulation.materials
-    elif isinstance(object_, MeshBase):
-        object_list = simulation.meshes
-    elif isinstance(object_, Element):
-        object_list = simulation.elements
-    elif isinstance(object_, ElectronReactionBase):
-        object_list = simulation.electron_reactions
-    elif isinstance(object_, Nuclide):
-        object_list = simulation.nuclides
-    elif isinstance(object_, NeutronReactionBase):
-        object_list = simulation.neutron_reactions
-    elif isinstance(object_, Region):
-        object_list = simulation.regions
-    elif isinstance(object_, Source):
-        object_list = simulation.sources
-    elif isinstance(object_, Surface):
-        object_list = simulation.surfaces
-    elif isinstance(object_, Tally):
-        object_list = simulation.tallies
-    elif isinstance(object_, Universe):
-        object_list = simulation.universes
-    else:
-        print_error(f"Unidentified object list for object {object_}")
-
-    object_.ID = len(object_list)
-    if isinstance(object_, MCDCPolymorphic):
-        object_.child_ID = sum([x.type == object_.type for x in object_list])
-    object_list.append(object_)
+MCDC_OBJECT_LABELS = [
+    # Geometry
+    "surface",
+    "region",
+    "cell",
+    "universe",
+    "lattice",
+    # Materials
+    "material",
+    "native_material",
+    "multigroup_material",
+    "element",
+    "nuclide",
+    # Source
+    "source",
+    # Tallies
+    "tally",
+    "surface_crossing_tally",
+    "collision_tally",
+    "tracklength_tally",
+    # Meshes
+    "mesh",
+    "uniform_mesh",
+    "structured_mesh",
+    # Neutron reactions
+    "neutron_reaction",
+    "neutron_elastic_scattering_reaction",
+    "neutron_capture_reaction",
+    "neutron_inelastic_scattering_reaction",
+    "neutron_fission_reaction",
+    # Electron reactions
+    "electron_reaction",
+    "electron_ionization_reaction",
+    "electron_elastic_scattering_reaction",
+    "electron_bremsstrahlung_reaction",
+    "electron_excitation_reaction",
+    # Data
+    "data",
+    "none_data",
+    "table_data",
+    "polynomial_data",
+    # Distribution
+    "distribution",
+    "none_distribution",
+    "pmf_distribution",
+    "tabulated_distribution",
+    "mult_table_distribution",
+    "level_scattering_distribution",
+    "evaporation_distribution",
+    "maxwellian_distribution",
+    "kalbach_mann_distribution",
+    "tabulated_energy_angle_distribution",
+    "nbody_distribution",
+    # Misc.
+    "gpu_meta",
+]
 
 
 # ======================================================================================
@@ -265,130 +116,6 @@ def register_object(object_):
 from typing import get_origin, get_args, Union, Annotated
 
 
-def _name_from_str(s: str) -> str:
-    s = _strip_prefixes(s)
-    # strip generic args like "NDArray[float64]" → "NDArray"
-    s = s.split("[", 1)[0]
-    return s.split(".")[-1].strip()
-
-
-def _mro_name_match(value, want: str) -> bool:
-    """Subclass-friendly match without resolving: compare wanted name to any base in MRO."""
-    want_name = _name_from_str(want)
-    return any(base.__name__ == want_name for base in value.__class__.mro())
-
-
-# ---------- helpers for STRING annotations ----------
-_ANN_RE = re.compile(r"^\s*(?:typing\.)?Annotated\[(.*)\]\s*$")
-
-
-def _split_top_level(s: str, sep: str = ",", brackets: str = "[]()") -> list[str]:
-    out, buf, depth = [], [], 0
-    opens = set(brackets[::2])
-    closes = set(brackets[1::2])
-    pairs = dict(zip(brackets[1::2], brackets[::2]))
-    for ch in s:
-        if ch in opens:
-            depth += 1
-        elif ch in closes:
-            depth -= 1
-        if ch == sep and depth == 0:
-            out.append("".join(buf).strip())
-            buf = []
-        else:
-            buf.append(ch)
-    if buf:
-        out.append("".join(buf).strip())
-    return out
-
-
-def _strip_prefixes(s: str) -> str:
-    # normalize common module prefixes used in annotations
-    return (
-        s.replace("typing.", "")
-        .replace("numpy.typing.", "")
-        .replace("numpy.", "")
-        .replace("np.", "")
-    )
-
-
-def _parse_annotated_str(hint_str: str):
-    """
-    If hint_str is 'Annotated[ ... ]', return (base_str, meta_list) else None.
-    meta_list items remain raw strings (no eval).
-    """
-    m = _ANN_RE.match(_strip_prefixes(hint_str))
-    if not m:
-        return None
-    inner = m.group(1)
-    parts = _split_top_level(inner, sep=",")
-    if not parts:
-        return None
-    base = parts[0].strip()
-    meta = [p.strip() for p in parts[1:]]
-    return base, meta
-
-
-def _shape_tuple_from_str(s: str):
-    """
-    Parse '(3,)', '(None, 3)', '(2,3,4)' → tuple[int|None, ...] or None if not a shape.
-    """
-    s = s.strip()
-    if not (s.startswith("(") and s.endswith(")")):
-        return None
-    body = s[1:-1].strip()
-    if not body:
-        return ()
-    items = _split_top_level(body, sep=",")
-    out = []
-    for it in items:
-        it = it.strip()
-        if it == "":
-            continue  # allow trailing comma
-        if it == "None":
-            out.append(None)
-        else:
-            try:
-                out.append(int(it))
-            except ValueError:
-                return None
-    return tuple(out)
-
-
-def _is_ndarray_base_str(base_str: str) -> bool:
-    base_norm = _strip_prefixes(base_str)
-    return base_norm.startswith("NDArray[") or base_norm.startswith("ndarray[")
-
-
-def _extract_ndarray_dtype_key_from_str(base_str: str) -> str | None:
-    base_norm = _strip_prefixes(base_str)
-    if "[" not in base_norm or "]" not in base_norm:
-        return None
-    inside = base_norm[base_norm.find("[") + 1 : base_norm.rfind("]")].strip()
-    return _strip_prefixes(inside)  # e.g. 'float' or 'float64'
-
-
-def _dtype_matches(arr: np.ndarray, dtype_key: str | None) -> bool:
-    if dtype_key is None:
-        return True
-    key = dtype_key.lower()
-    if key == "float":
-        return np.issubdtype(arr.dtype, np.floating)
-    if key == "int":
-        return np.issubdtype(arr.dtype, np.integer)
-    try:
-        return arr.dtype == np.dtype(key)  # e.g. 'float64', 'int32'
-    except TypeError:
-        return True  # unknown key → do not fail hard
-
-
-def _shape_matches(arr: np.ndarray, shape: tuple[int | None, ...]) -> bool:
-    if arr.ndim != len(shape):
-        return False
-    return all(dim is None or dim == s for s, dim in zip(arr.shape, shape))
-
-
-# ---------- main checker ----------
 def check_type(value, hint, cls, obj=None) -> bool:
     """
     Best-effort runtime checker tolerant of *string* annotations (no eval).
@@ -522,3 +249,126 @@ def check_type(value, hint, cls, obj=None) -> bool:
         return isinstance(value, origin)
     except TypeError:
         return True
+
+
+def _name_from_str(s: str) -> str:
+    s = _strip_prefixes(s)
+    # strip generic args like "NDArray[float64]" → "NDArray"
+    s = s.split("[", 1)[0]
+    return s.split(".")[-1].strip()
+
+
+def _mro_name_match(value, want: str) -> bool:
+    """Subclass-friendly match without resolving: compare wanted name to any base in MRO."""
+    want_name = _name_from_str(want)
+    return any(base.__name__ == want_name for base in value.__class__.mro())
+
+
+# ---------- helpers for STRING annotations ----------
+_ANN_RE = re.compile(r"^\s*(?:typing\.)?Annotated\[(.*)\]\s*$")
+
+
+def _split_top_level(s: str, sep: str = ",", brackets: str = "[]()") -> list[str]:
+    out, buf, depth = [], [], 0
+    opens = set(brackets[::2])
+    closes = set(brackets[1::2])
+    pairs = dict(zip(brackets[1::2], brackets[::2]))
+    for ch in s:
+        if ch in opens:
+            depth += 1
+        elif ch in closes:
+            depth -= 1
+        if ch == sep and depth == 0:
+            out.append("".join(buf).strip())
+            buf = []
+        else:
+            buf.append(ch)
+    if buf:
+        out.append("".join(buf).strip())
+    return out
+
+
+def _strip_prefixes(s: str) -> str:
+    # normalize common module prefixes used in annotations
+    return (
+        s.replace("typing.", "")
+        .replace("numpy.typing.", "")
+        .replace("numpy.", "")
+        .replace("np.", "")
+    )
+
+
+def _parse_annotated_str(hint_str: str):
+    """
+    If hint_str is 'Annotated[ ... ]', return (base_str, meta_list) else None.
+    meta_list items remain raw strings (no eval).
+    """
+    m = _ANN_RE.match(_strip_prefixes(hint_str))
+    if not m:
+        return None
+    inner = m.group(1)
+    parts = _split_top_level(inner, sep=",")
+    if not parts:
+        return None
+    base = parts[0].strip()
+    meta = [p.strip() for p in parts[1:]]
+    return base, meta
+
+
+def _shape_tuple_from_str(s: str):
+    """
+    Parse '(3,)', '(None, 3)', '(2,3,4)' → tuple[int|None, ...] or None if not a shape.
+    """
+    s = s.strip()
+    if not (s.startswith("(") and s.endswith(")")):
+        return None
+    body = s[1:-1].strip()
+    if not body:
+        return ()
+    items = _split_top_level(body, sep=",")
+    out = []
+    for it in items:
+        it = it.strip()
+        if it == "":
+            continue  # allow trailing comma
+        if it == "None":
+            out.append(None)
+        else:
+            try:
+                out.append(int(it))
+            except ValueError:
+                return None
+    return tuple(out)
+
+
+def _is_ndarray_base_str(base_str: str) -> bool:
+    base_norm = _strip_prefixes(base_str)
+    return base_norm.startswith("NDArray[") or base_norm.startswith("ndarray[")
+
+
+def _extract_ndarray_dtype_key_from_str(base_str: str) -> str | None:
+    base_norm = _strip_prefixes(base_str)
+    if "[" not in base_norm or "]" not in base_norm:
+        return None
+    inside = base_norm[base_norm.find("[") + 1 : base_norm.rfind("]")].strip()
+    return _strip_prefixes(inside)  # e.g. 'float' or 'float64'
+
+
+def _dtype_matches(arr: np.ndarray, dtype_key: str | None) -> bool:
+    if dtype_key is None:
+        return True
+    key = dtype_key.lower()
+    if key == "float":
+        return np.issubdtype(arr.dtype, np.floating)
+    if key == "int":
+        return np.issubdtype(arr.dtype, np.integer)
+    try:
+        return arr.dtype == np.dtype(key)  # e.g. 'float64', 'int32'
+    except TypeError:
+        return True  # unknown key → do not fail hard
+
+
+def _shape_matches(arr: np.ndarray, shape: tuple[int | None, ...]) -> bool:
+    if arr.ndim != len(shape):
+        return False
+    return all(dim is None or dim == s for s, dim in zip(arr.shape, shape))
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index d80c25aab..1ddd73277 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -99,20 +99,22 @@ class Cell(MCDCObject):
     """
 
     name: str
+
     region: Region  # Non-numba
+    region_RPN_tokens: list[int]
+    region_RPN: Boolean  # Non-numba
+    surfaces: list[Surface]
+
     fill: MaterialBase | Universe | Lattice | NoneType  # Non-numba
+    fill_type: int
+    fill_ID: int
     fill_translated: bool
     fill_rotated: bool
     translation: Annotated[NDArray[float64], (3,)]
     rotation: Annotated[NDArray[float64], (3,)]
-    region_RPN_tokens: list[int]
-    region_RPN: Boolean  # Non-numba
-    surfaces: list[Surface]
+
     collision_tallies: list[TallyCollision]
     tracklength_tallies: list[TallyTracklength]
-    #
-    fill_type: int
-    fill_ID: int
 
     def __init__(
         self,
@@ -125,19 +127,8 @@ def __init__(
         # MC/DC framework metadata
         super().__init__(label="cell", non_numba=["region", "fill", "region_RPN"])
 
-        # Set name
-        if name == "":
-            self.name = "(Unnamed cell)"
-        else:
-            self.name = name
-
-        # Set region
-        if region is None:
-            self.region = Region("all", None, None)
-        else:
-            self.region = region
-
-        # Set fill
+        self.name = name or "(Unnamed cell)"
+        self.region = region or Region("all", None, None)
         self.fill = fill
 
         # Local coordinate modifier
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 4213b7693..5b7878f08 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -49,7 +49,7 @@ def __init__(
 
     def __repr__(self):
         text = "\n"
-        text += f"{decode_type(self.type)}\n"
+        text += f"{decode_type(self.child_type)}\n"
         text += f"  - Name: {self.name}\n"
         text += f"  - Fissionable: {self.fissionable}\n"
         return text
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 6286e831a..a47d96366 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -24,8 +24,8 @@
 ####
 
 from mcdc.object_.base import MCDCBase
-from mcdc.object_.data import DataBase, DataNone
-from mcdc.object_.distribution import DistributionBase, DistributionNone
+from mcdc.object_.data import DataBase
+from mcdc.object_.distribution import DistributionBase
 from mcdc.object_.gpu_tools import GPUMeta
 from mcdc.object_.mesh import MeshBase
 from mcdc.object_.particle import ParticleBank
@@ -87,6 +87,7 @@ class Simulation(MCDCBase):
     regions: list[Region]  # Non-Numba
     cells: list[Cell]
     universes: list[Universe]
+    root_universe: Universe
     lattices: list[Lattice]
     meshes: list[MeshBase]
 
@@ -168,48 +169,29 @@ def __init__(self, name: str = "") -> None:
             User-defined simulation name. If omitted, an unnamed simulation is
             created.
         """
-        non_numba = [
-            "regions",
-            "bank_active",
-            "bank_census",
-            "bank_source",
-            "bank_future",
-            "_next_compile_ID",
-            "compiled",
-            "compile_ID",
-        ]
-        super().__init__("simulation", non_numba)
-
-        # Set name
-        self.name = name or "(Unnamed simulation)"
+        super().__init__(
+            label="simulation",
+            non_numba=[
+                "regions",
+                "root_universe",
+                "bank_active",
+                "bank_census",
+                "bank_source",
+                "bank_future",
+                "_next_compile_ID",
+                "compiled",
+                "compile_ID",
+            ],
+        )
 
         self.compile_ID = 0
         self.compiled = False
 
-        # ==============================================================================
-        # Simulation objects
-        # ==============================================================================
-
-        # Physics
-        self.data = [DataNone()]
-        self.distributions = [DistributionNone()]
-        self.neutron_reactions = []
-        self.electron_reactions = []
-        self.nuclides = []
-        self.elements = []
-        self.materials = []
-        self.sources = []
-
-        # Geometry
-        self.surfaces = []
-        self.regions = []
-        self.cells = []
-        self.universes = [Universe("Root Universe")]
-        self.lattices = []
-        self.meshes = []
+        self.name = name or "(Unnamed simulation)"
+        self.root_universe = Universe("Root Universe")
 
-        # Tallies
-        self.tallies = []
+        # Initialize with empty object lists
+        self._reset_object_lists()
 
         # ==============================================================================
         # Simulation settings and techniques
@@ -287,6 +269,28 @@ def __init__(self, name: str = "") -> None:
         self.gpu_meta = GPUMeta()
         self.source_seed = 0
 
+    def _reset_object_lists(self) -> None:
+        # Physics
+        self.data = []
+        self.distributions = []
+        self.neutron_reactions = []
+        self.electron_reactions = []
+        self.nuclides = []
+        self.elements = []
+        self.materials = []
+        self.sources = []
+
+        # Geometry
+        self.surfaces = []
+        self.regions = []
+        self.cells = []
+        self.universes = []
+        self.lattices = []
+        self.meshes = []
+
+        # Tallies
+        self.tallies = []
+
     # ==================================================================================
     # Simulation object setters
     # ==================================================================================
@@ -304,7 +308,7 @@ def set_model(self, cells: Sequence[Cell]) -> None:
         Only the root cells are stored. Connected geometry and physics objects are
         discovered automatically during compilation.
         """
-        self.universes[0].cells = list(cells)
+        self.root_universe.cells = list(cells)
         self.compiled = False
 
     def set_sources(self, sources: Sequence[Source]) -> None:
@@ -339,21 +343,6 @@ def set_tallies(self, tallies: Sequence[Tally]) -> None:
         self.tallies = list(tallies)
         self.compiled = False
 
-    def set_root_universe(self, cells: Sequence[Cell]) -> None:
-        """Set the cells of the root universe.
-
-        Parameters
-        ----------
-        cells : Sequence[Cell]
-            Cells contained directly in the root universe.
-
-        Notes
-        -----
-        The root universe occupies index ``0`` in the compiled universe array.
-        Geometry tracking begins from this universe by default.
-        """
-        self.universes[0].cells = list(cells)
-
     # ==================================================================================
     # Operations
     # ==================================================================================
@@ -371,18 +360,12 @@ def compile(self) -> None:
         simulation for execution or other operations that require the compiled
         representation.
         """
-        from mcdc.main import compile_simulation
-
-        compile_ID = type(self)._next_compile_ID
+        from mcdc.code_factory.python_objects_compiler import compile_simulation
 
-        try:
-            compile_simulation(self, compile_ID)
-        except Exception:
-            self.compiled = False
-            raise
-
-        self.compile_ID = compile_ID
+        self.compile_ID = type(self)._next_compile_ID
         type(self)._next_compile_ID += 1
+
+        compile_simulation(self)
         self.compiled = True
 
     def visualize_model(
@@ -461,10 +444,8 @@ def run(self) -> None:
         if not self.compiled:
             self.compile()
 
-        try:
-            run_simulation(self)
-        finally:
-            self.compiled = False
+        run_simulation(self)
+        self.compiled = False
 
     def __repr__(self) -> str:
         return (

From a09a8cdf27b47a81f4985c74502d4445b8f814b6 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 20 Jul 2026 21:01:04 +0700
Subject: [PATCH 019/202] add object compilation

---
 mcdc/code_factory/python_objects_compiler.py | 165 ++++---
 mcdc/main.py                                 |  19 +-
 mcdc/object_/base.py                         |  78 +--
 mcdc/object_/cell.py                         | 145 +++---
 mcdc/object_/data.py                         | 144 +-----
 mcdc/object_/distribution.py                 | 282 ++---------
 mcdc/object_/electron_reaction.py            |  15 +-
 mcdc/object_/material.py                     | 126 +----
 mcdc/object_/mesh.py                         |  11 +-
 mcdc/object_/neutron_reaction.py             |  15 +-
 mcdc/object_/simulation.py                   | 142 +-----
 mcdc/object_/source.py                       |  41 +-
 mcdc/object_/surface.py                      | 483 +------------------
 mcdc/object_/tally.py                        | 118 +++--
 mcdc/object_/universe.py                     | 107 ++--
 15 files changed, 424 insertions(+), 1467 deletions(-)

diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index eda678305..33f5ae759 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -1,76 +1,109 @@
-from mcdc.object_.base import MCDCObject
+from mcdc.object_.base import MCDCObject, MCDCPolymorphic
+from mcdc.object_.cell import Region, Cell
+from mcdc.object_.data import DataBase, DataNone
+from mcdc.object_.distribution import DistributionBase, DistributionNone
+from mcdc.object_.electron_reaction import ElectronReactionBase
+from mcdc.object_.element import Element
+from mcdc.object_.material import MaterialBase
+from mcdc.object_.mesh import MeshBase
+from mcdc.object_.neutron_reaction import NeutronReactionBase
+from mcdc.object_.nuclide import Nuclide
+from mcdc.object_.universe import Universe, Lattice
 from mcdc.object_.simulation import Simulation
+from mcdc.object_.source import Source
+from mcdc.object_.surface import Surface
+from mcdc.object_.tally import Tally
+from mcdc.print_ import print_error
 
+NONE_OBJECT_CLASSES = (DataNone, DistributionNone)  # Has customized compilation
 
-def compile_simulation(simulationPy: Simulation):
-    from mcdc.object_.base import MCDC_OBJECT_LABELS
-    from mcdc.object_.data import DataNone
-    from mcdc.object_.distribution import DistributionNone
 
-    # Reset derived object lists
-    simulationPy._reset_object_lists()
+def compile_simulation(simulation: Simulation):
+    # Reset model
+    simulation._reset_model()
 
-    # Object IDs counter
-    # TODO: Remove
-    next_ID = dict.fromkeys(MCDC_OBJECT_LABELS, 0)
+    # Reserved ojects
+    none_data = DataNone()
+    none_distribution = DistributionNone()
 
     # Compile reserved objects
-    compile_object(simulationPy.root_universe, simulationPy)
+    none_data._compile_into_simulation(simulation)
+    none_distribution._compile_into_simulation(simulation)
 
-    # Root universe
-    simulationPy.universes.append(simulationPy.root_universe)
-
-    # "None" objects
-    simulationPy.data.append(DataNone())
-    simulationPy.distributions.append(DistributionNone())
-
-    # Assign IDs
-    assign_IDs(simulationPy.data[0], next_ID, compile_ID)
-    assign_IDs(simulationPy.distributions[0], next_ID, compile_ID)
-    assign_IDs(simulationPy.universes[0], next_ID, compile_ID)
-
-    # ==================================================================================
     # Compile model
-    # ==================================================================================
-
-    root_universe = simulationPy.universes[0]
-
-    # Loop over root universe cells
-    for cell in root_universe.cells:
-        assign_IDs(cell, next_ID, compile_ID)
-
-        # Fill
-        fill = cell.fill
+    root_universe = simulation.root_universe
+    root_universe._compile_into_simulation(simulation)
+
+    # Compile source
+    sources = simulation.sources
+    simulation.sources = []
+    for source in sources:
+        source._compile_into_simulation(simulation)
+
+    # Compile tally
+    tallies = simulation.tallies
+    simulation.tallies = []
+    print(tallies)
+    for tally in tallies:
+        tally._compile_into_simulation(simulation)
+    print(simulation.tallies)
+
+    # Compile settings
+
+
+def register_object(object_: MCDCObject, simulation: Simulation) -> bool:
+    # Skip if already compiled
+    if object_.compile_ID == simulation.compile_ID:
+        return False
+
+    # Get the object list
+    if isinstance(object_, Cell):
+        object_list = simulation.cells
+    elif isinstance(object_, DataBase):
+        object_list = simulation.data
+    elif isinstance(object_, DistributionBase):
+        object_list = simulation.distributions
+    elif isinstance(object_, Lattice):
+        object_list = simulation.lattices
+    elif isinstance(object_, MaterialBase):
+        object_list = simulation.materials
+    elif isinstance(object_, MeshBase):
+        object_list = simulation.meshes
+    elif isinstance(object_, Element):
+        object_list = simulation.elements
+    elif isinstance(object_, ElectronReactionBase):
+        object_list = simulation.electron_reactions
+    elif isinstance(object_, Nuclide):
+        object_list = simulation.nuclides
+    elif isinstance(object_, NeutronReactionBase):
+        object_list = simulation.neutron_reactions
+    elif isinstance(object_, Region):
+        object_list = simulation.regions
+    elif isinstance(object_, Source):
+        object_list = simulation.sources
+    elif isinstance(object_, Surface):
+        object_list = simulation.surfaces
+    elif isinstance(object_, Tally):
+        object_list = simulation.tallies
+    elif isinstance(object_, Universe):
+        object_list = simulation.universes
+    else:
+        object_list = []
+        print_error(f"Unidentified object list for object {object_}")
 
-        ## Material
-        if isinstance(fill, MaterialBase):
-            simulationPy.materials.append(fill)
-            assign_IDs(fill, next_ID, compile_ID)
-
-        ## Universe
-        elif isinstance(fill, Universe):
-            simulationPy.universes.append(fill)
-            assign_IDs(fill, next_ID, compile_ID)
-
-        ## Lattice
-        elif isinstance(fill, Lattice):
-            simulationPy.lattices.append(fill)
-            assign_IDs(fill, next_ID, compile_ID)
-
-
-def compile_object(object_: MCDCObject, simulationPy: Simulation) -> None:
-    object_type = type(object_)
-    print(object_type)
-    matching_members = {
-        k: v
-        for k, v in vars(simulationPy).items()
-        if isinstance(v, list) and all(isinstance(x, object_type) for x in v)
-    }
-    print(matching_members)
-    exit()
-
-    # Assign ID
-
-    object_.ID = next_ID[object_.label]
-    object_.compile_ID = compile_ID
-    next_ID[object_.label] += 1
+    # Assign IDs
+    object_.ID = len(object_list)
+    if isinstance(object_, MCDCPolymorphic):
+        object_.child_ID = sum(
+            [
+                x.child_type == object_.child_type
+                for x in object_list
+                if isinstance(x, MCDCPolymorphic)
+            ]
+        )
+    object_.compile_ID = simulation.compile_ID
+
+    # Register to simulation (TODO: Resolve IDE error message)
+    object_list.append(object_)
+
+    return True
diff --git a/mcdc/main.py b/mcdc/main.py
index 8425d857c..9a5afc84b 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -9,16 +9,6 @@
 
 
 def run_simulation(simulationPy: Simulation):
-    """
-    Execute the MC/DC simulation.
-
-    Runs the transport simulation defined by the current problem
-    (materials, geometry, sources, tallies, and settings).
-    Results are written to an HDF5 output file.
-
-    Command-line arguments (``--N_particle``, ``--output``, etc.) override
-    the corresponding settings when provided.
-    """
     import mcdc.print_ as print_module
     from mpi4py import MPI
 
@@ -37,7 +27,7 @@ def run_simulation(simulationPy: Simulation):
     time_prep_start = MPI.Wtime()
 
     # Override settings with command-line arguments
-    override_settings()
+    override_settings(simulationPy)
 
     # Generate the program state:
     #   - `simulation`: the simulation structure, storing fixed side data and meta data
@@ -47,7 +37,7 @@ def run_simulation(simulationPy: Simulation):
     #       The use of container is necessary to ensure proper mutability and tracking
     #       of the structure when running in different kinds of machines supported by
     #       the Numba-based compilation framework.
-    simulation_container, data = preparation(simulationPy)
+    simulation_container, data = prepare(simulationPy)
     simulation = simulation_container[0]
 
     # Print headers
@@ -191,7 +181,7 @@ def prepare(simulationPy):
     if settings.use_census_based_tally:
         N_bin = settings.census_tally_frequency
         for tally in simulationPy.tallies:
-            tally._use_census_based_tally(N_bin)
+            tally._use_census_based_tally(N_bin, simulationPy)
 
     # Normalize source probability
     norm = 0.0
@@ -326,9 +316,8 @@ def prepare(simulationPy):
 # ======================================================================================
 
 
-def override_settings():
+def override_settings(simulationPy):
     import mcdc.config as config
-    from mcdc.object_.simulation import simulation as simulationPy
 
     settings = simulationPy.settings
 
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index ffdde6c45..5176769b5 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -27,6 +27,20 @@ def __init__(self, label: str, non_numba: list[str]):
         self.compile_ID = 0
         self.non_numba += ["compile_ID"]
 
+    def __repr__(self) -> str:
+        nice_label = self.label.replace("_", " ").title()
+        text = "\n"
+        text += f"{nice_label}\n"
+        if self.compile_ID > 0:
+            text += f"  (compile_ID={self.compile_ID}, ID={self.ID})\n"
+
+        return text
+
+    def _compile_into_simulation(self, simulation) -> bool:
+        from mcdc.code_factory.python_objects_compiler import register_object
+
+        return register_object(self, simulation)
+
 
 class MCDCPolymorphic(MCDCObject):
     child_label: str
@@ -47,63 +61,15 @@ def __init__(
         self.child_ID = -1
         self.non_numba += ["child_label"]
 
+    def __repr__(self) -> str:
+        nice_label = self.label.replace("_", " ").title()
+        nice_sublabel = self.child_label.replace("_", " ").title()
+        text = "\n"
+        text += f"{nice_label} - {nice_sublabel}\n"
+        if self.compile_ID > 0:
+            text += f"  (compile_ID={self.compile_ID}, ID={self.ID})\n"
 
-MCDC_OBJECT_LABELS = [
-    # Geometry
-    "surface",
-    "region",
-    "cell",
-    "universe",
-    "lattice",
-    # Materials
-    "material",
-    "native_material",
-    "multigroup_material",
-    "element",
-    "nuclide",
-    # Source
-    "source",
-    # Tallies
-    "tally",
-    "surface_crossing_tally",
-    "collision_tally",
-    "tracklength_tally",
-    # Meshes
-    "mesh",
-    "uniform_mesh",
-    "structured_mesh",
-    # Neutron reactions
-    "neutron_reaction",
-    "neutron_elastic_scattering_reaction",
-    "neutron_capture_reaction",
-    "neutron_inelastic_scattering_reaction",
-    "neutron_fission_reaction",
-    # Electron reactions
-    "electron_reaction",
-    "electron_ionization_reaction",
-    "electron_elastic_scattering_reaction",
-    "electron_bremsstrahlung_reaction",
-    "electron_excitation_reaction",
-    # Data
-    "data",
-    "none_data",
-    "table_data",
-    "polynomial_data",
-    # Distribution
-    "distribution",
-    "none_distribution",
-    "pmf_distribution",
-    "tabulated_distribution",
-    "mult_table_distribution",
-    "level_scattering_distribution",
-    "evaporation_distribution",
-    "maxwellian_distribution",
-    "kalbach_mann_distribution",
-    "tabulated_energy_angle_distribution",
-    "nbody_distribution",
-    # Misc.
-    "gpu_meta",
-]
+        return text
 
 
 # ======================================================================================
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 1ddd73277..ec9a823b2 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -45,7 +45,8 @@ class Region(MCDCObject):
     B: Region | int | NoneType
 
     def __init__(self, type_, A, B):
-        super().__init__(label="region", non_numba=[])
+        # MC/DC framework metadata
+        super().__init__("region", [])
 
         self.type = type_
         self.A = A
@@ -66,7 +67,7 @@ def __invert__(self):
         return Region("complement", self, None)
 
     def __repr__(self):
-        return f"Region: {str.capitalize(self.type)}"
+        return f"{str.capitalize(self.type)} Region"
 
 
 # ======================================================================================
@@ -75,36 +76,15 @@ def __repr__(self):
 
 
 class Cell(MCDCObject):
-    """
-    Define a cell from a region and a fill.
-
-    Parameters
-    ----------
-    region : Region, optional
-        The spatial region defining the cell boundaries.
-        Constructed using ``+surface`` / ``-surface`` half-space operators.
-    fill : Material or MaterialMG or Universe or Lattice, optional
-        The material or universe that fills the cell.
-    name : str, optional
-        User label.
-    translation : array_like of float, optional
-        Translation vector ``[tx, ty, tz]`` in cm.
-    rotation : array_like of float, optional
-        Rotation angles ``[rx, ry, rz]`` in degrees.
-
-    See Also
-    --------
-    mcdc.Surface : Creates surfaces that can be used to define cell regions.
-    mcdc.Universe : Groups cells into a universe.
-    """
-
     name: str
 
+    # Region definition
     region: Region  # Non-numba
     region_RPN_tokens: list[int]
     region_RPN: Boolean  # Non-numba
     surfaces: list[Surface]
 
+    # Fill definition
     fill: MaterialBase | Universe | Lattice | NoneType  # Non-numba
     fill_type: int
     fill_ID: int
@@ -113,6 +93,7 @@ class Cell(MCDCObject):
     translation: Annotated[NDArray[float64], (3,)]
     rotation: Annotated[NDArray[float64], (3,)]
 
+    # Attached tallies
     collision_tallies: list[TallyCollision]
     tracklength_tallies: list[TallyTracklength]
 
@@ -125,7 +106,7 @@ def __init__(
         rotation: Sequence[float] = [0.0, 0.0, 0.0],
     ):
         # MC/DC framework metadata
-        super().__init__(label="cell", non_numba=["region", "fill", "region_RPN"])
+        super().__init__("cell", ["region", "region_RPN", "fill"])
 
         self.name = name or "(Unnamed cell)"
         self.region = region or Region("all", None, None)
@@ -143,31 +124,21 @@ def __init__(
             # Convert ritation
             self.rotation *= PI / 180.0
 
-        # Set region Reversed Polished Notation (RPN)
-        # TODO
-        """
-        if self.region.type != "all":
-            self.region_RPN_tokens = generate_RPN_tokens(self.region)
-            self.region_RPN = generate_RPN(self.region_RPN_tokens)
-        else:
-            self.region_RPN_tokens = []
-            self.region_RPN = Boolean(True)
-        """
-
-        # List surfaces
-        # TODO
-        # self.surfaces = list_surfaces(self.region_RPN_tokens)
-
         # Cell tallies
         self.collision_tallies = []
         self.tracklength_tallies = []
 
-        # ==============================================================================
-        # Numba attribute manual set up
-        # ==============================================================================
+    def _compile_into_simulation(self, simulation) -> bool:
+        # Already compiled?
+        if not super()._compile_into_simulation(simulation):
+            return False
+
+        # Compile fill if needed
+        fill = self.fill
+        if fill:
+            fill._compile_into_simulation(simulation)
 
         # Numba representation of the cell fill
-        #   (Because polymorphic Ffill object is not supported)
         if isinstance(fill, MaterialBase):
             self.fill_type = FILL_MATERIAL
             self.fill_ID = fill.ID
@@ -180,20 +151,32 @@ def __init__(
         elif fill == None:
             self.fill_type = FILL_NONE
             self.fill_ID = -1
+
+        # Set region Reversed Polished Notation (RPN)
+        if self.region.type != "all":
+            self.region_RPN_tokens = generate_RPN_tokens(self.region, simulation)
+            self.region_RPN = generate_RPN(self.region_RPN_tokens)
         else:
-            print_error(f"Unsupported cell fill: {fill}")
+            self.region_RPN_tokens = []
+            self.region_RPN = Boolean(True)
+
+        # List surfaces
+        self.surfaces = list_surfaces(self.region_RPN_tokens, simulation)
+
+        return True
 
     def __repr__(self):
-        text = "\n"
-        text += f"Cell\n"
+        text = super().__repr__()
+
         text += f"  - Name: {self.name}\n"
-        text += f"  - {self.region}\n"
-        if isinstance(self.fill, MaterialBase):
-            text += f"  - Fill (material): {self.fill.name}\n"
-        elif isinstance(self.fill, Lattice):
-            text += f"  - Fill (lattice): {self.fill.name}\n"
-        elif isinstance(self.fill, Universe):
-            text += f"  - Fill (universe): {self.fill.name}\n"
+        if self.compile_ID > 0:
+            text += f"  - Region RPN: {self.region_RPN}\n"
+        else:
+            text += f"  - {self.region}\n"
+        if self.fill:
+            text += f"  - Fill [{self.fill.label.title().replace("_"," ")}]: {self.fill.name}\n"
+        else:
+            text += f"  - Fill [None]"
         if self.fill_translated:
             text += f"  - Translation: {self.translation}\n"
         if self.fill_rotated:
@@ -208,7 +191,9 @@ def __repr__(self):
         return text
 
 
-def generate_RPN_tokens(region):
+def generate_RPN_tokens(region, simulation):
+    from mcdc.object_.surface import Surface
+
     # The RPN tokens
     rpn_tokens = []
 
@@ -216,17 +201,46 @@ def generate_RPN_tokens(region):
     stack = [region]
     while len(stack) > 0:
         token = stack.pop()
+
+        # Resolve region token
         if isinstance(token, Region):
-            if token.type == "halfspace":
-                rpn_tokens.append(token.A.ID)
-                if token.B < 0:
+            A = token.A
+            B = token.B
+
+            if token.type == "halfspace" and (
+                isinstance(A, Surface) and isinstance(B, int)
+            ):
+                surface = A
+                sense = B
+
+                # Compile and register surface
+                surface._compile_into_simulation(simulation)
+                rpn_tokens.append(surface.ID)
+
+                if sense < 0:
                     rpn_tokens.append(BOOL_NOT)
-            elif token.type == "intersection":
+
+            elif token.type == "intersection" and (
+                isinstance(A, Region) and isinstance(B, Region)
+            ):
                 stack += ["&", token.A, token.B]
-            elif token.type == "union":
+
+            elif token.type == "union" and (
+                isinstance(A, Region) and isinstance(B, Region)
+            ):
                 stack += ["|", token.A, token.B]
-            elif token.type == "complement":
+
+            elif token.type == "complement" and (
+                isinstance(A, Region) and isinstance(B, Region)
+            ):
                 stack += ["~", token.A]
+
+            else:
+                print_error(
+                    f"Invalid RPN tokens for Region of type {token.type}: {A}, {B}"
+                )
+
+        # Register RPN token
         else:
             if token == "&":
                 rpn_tokens.append(BOOL_AND)
@@ -235,7 +249,7 @@ def generate_RPN_tokens(region):
             elif token == "~":
                 rpn_tokens.append(BOOL_NOT)
             else:
-                print_error(f"Unrecognized token in the generating region RPN: {token}")
+                print_error(f"Unrecognized RPN token: {token}")
 
     return rpn_tokens
 
@@ -265,13 +279,12 @@ def generate_RPN(rpn_tokens):
     return sympy.logic.boolalg.simplify_logic(stack[0])
 
 
-def list_surfaces(rpn_tokens):
+def list_surfaces(rpn_tokens, simulation):
     surfaces = []
 
     for token in rpn_tokens:
         if token >= 0:
             surface = simulation.surfaces[token]
-            if surface not in surfaces:
-                surfaces.append(surface)
+            surfaces.append(surface)
 
     return sorted(surfaces, key=attrgetter("ID"))
diff --git a/mcdc/object_/data.py b/mcdc/object_/data.py
index 20cff8124..b33290293 100644
--- a/mcdc/object_/data.py
+++ b/mcdc/object_/data.py
@@ -25,67 +25,15 @@
 
 
 class DataBase(MCDCPolymorphic):
-    """Base class for compiled data objects.
-
-    Data objects store numerical information used by physics models,
-    distributions, and other MC/DC objects. Concrete subclasses determine the
-    representation of the stored data.
-    """
-
     def __init__(
         self,
         child_label: str,
         child_type: int,
         non_numba: list[str],
     ) -> None:
-        """Initialize data framework metadata.
-
-        Parameters
-        ----------
-        child_label : str
-            Framework label identifying the concrete data representation.
-
-        child_type : int
-            Integer identifier specifying the concrete data representation.
-
-        non_numba : list of str
-            Additional attribute names excluded from the compiled
-            representation.
-        """
+        # MC/DC framework metadata
         super().__init__("data", child_label, child_type, non_numba)
 
-    def __repr__(self) -> str:
-        """Return a human-readable description of the data object."""
-        return f"\n{decode_type(self.child_type)}\n"
-
-
-def decode_type(type_: int) -> str:
-    """Convert a data type code to a human-readable name.
-
-    Parameters
-    ----------
-    type_ : int
-        Data type code.
-
-    Returns
-    -------
-    str
-        Human-readable data type name.
-
-    Raises
-    ------
-    ValueError
-        If the data type code is unknown.
-    """
-    if type_ == DATA_NONE:
-        return "Data (None)"
-    if type_ == DATA_TABLE:
-        return "Data (Table)"
-    if type_ == DATA_POLYNOMIAL:
-        return "Data (Polynomial function)"
-
-    raise ValueError(f"Unknown data type: {type_}")
-
 
 # ======================================================================================
 # None
@@ -95,10 +43,8 @@ def decode_type(type_: int) -> str:
 
 
 class DataNone(DataBase):
-    """Placeholder for the absence of stored data."""
-
     def __init__(self) -> None:
-        """Create an empty data object."""
+        # MC/DC framework metadata
         super().__init__("none_data", DATA_NONE, [])
 
 
@@ -108,14 +54,6 @@ def __init__(self) -> None:
 
 
 class DataTable(DataBase):
-    """Tabulated one-dimensional data with interpolation regions.
-
-    Interpolation laws are applied to ``y`` over regions of ``x``. Optional
-    auxiliary arrays may store additional values aligned with ``x``, such as
-    cumulative distribution functions associated with tabulated probability
-    densities. Auxiliary data are stored for lookup and are not interpolated.
-    """
-
     # Main data
     N: int
     x: NDArray[float64]
@@ -137,34 +75,7 @@ def __init__(
         interpolation_boundaries: Sequence[int] | None = None,
         aux: NDArray[float64] | None = None,
     ) -> None:
-        """Create a tabulated data object.
-
-        Parameters
-        ----------
-        x : ndarray of float64
-            One-dimensional independent-variable values.
-
-        y : ndarray of float64
-            One-dimensional dependent-variable values aligned with ``x``.
-
-        interpolations : int or sequence of int
-            Interpolation law applied to the entire table, or an ordered
-            sequence of interpolation laws for multiple regions.
-
-        interpolation_boundaries : sequence of int, optional
-            Exclusive upper index of each interpolation region. Required when
-            multiple interpolation laws are provided. The final boundary must
-            equal ``len(x)``.
-
-        aux : ndarray of float64, optional
-            Auxiliary data aligned with ``x``. A one-dimensional array is
-            stored with shape ``(1, N)``. A two-dimensional array must have
-            shape ``(N_aux, N)``.
-
-        Notes
-        -----
-        Interpolation boundaries use Python-style exclusive upper indices.
-        """
+        # MC/DC framework metadata
         super().__init__("table_data", DATA_TABLE, [])
 
         # Set primary data
@@ -258,8 +169,8 @@ def __init__(
             decode_interpolation(interpolation)
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the tabulated data."""
         text = super().__repr__()
+
         text += f"  - x {print_1d_array(self.x)}\n"
         text += f"  - y {print_1d_array(self.y)}\n"
 
@@ -291,23 +202,6 @@ def __repr__(self) -> str:
 
 
 def decode_interpolation(type_: int) -> str:
-    """Convert an interpolation type code to its string name.
-
-    Parameters
-    ----------
-    type_ : int
-        Interpolation type code.
-
-    Returns
-    -------
-    str
-        Interpolation name.
-
-    Raises
-    ------
-    ValueError
-        If the interpolation type code is unknown.
-    """
     if type_ == INTERPOLATION_HISTOGRAM:
         return "histogram"
     if type_ == INTERPOLATION_LINEAR:
@@ -323,23 +217,6 @@ def decode_interpolation(type_: int) -> str:
 
 
 def encode_interpolation(name: str) -> int:
-    """Convert an interpolation name to its integer type code.
-
-    Parameters
-    ----------
-    name : str
-        Interpolation name.
-
-    Returns
-    -------
-    int
-        Interpolation type code.
-
-    Raises
-    ------
-    ValueError
-        If the interpolation name is unknown.
-    """
     if name == "histogram":
         return INTERPOLATION_HISTOGRAM
     if name == "linear":
@@ -360,19 +237,10 @@ def encode_interpolation(name: str) -> int:
 
 
 class DataPolynomial(DataBase):
-    """Polynomial data represented by an ordered coefficient array."""
-
     coefficients: NDArray[float64]
 
     def __init__(self, coefficients: NDArray[float64]) -> None:
-        """Create a polynomial data object.
-
-        Parameters
-        ----------
-        coefficients : ndarray of float64
-            One-dimensional polynomial coefficients ordered according to the
-            convention used by the consuming MC/DC method.
-        """
+        # MC/DC framework metadata
         super().__init__("polynomial_data", DATA_POLYNOMIAL, [])
 
         self.coefficients = np.asarray(coefficients, dtype=float64)
@@ -381,7 +249,7 @@ def __init__(self, coefficients: NDArray[float64]) -> None:
             print_error("coefficients must be one-dimensional.")
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the polynomial data."""
         text = super().__repr__()
+
         text += f"  - coefficients {print_1d_array(self.coefficients)}\n"
         return text
diff --git a/mcdc/object_/distribution.py b/mcdc/object_/distribution.py
index 820e4cba6..1fd63f99b 100644
--- a/mcdc/object_/distribution.py
+++ b/mcdc/object_/distribution.py
@@ -34,85 +34,14 @@
 
 
 class DistributionBase(MCDCPolymorphic):
-    """Base class for probability distributions.
-
-    Distribution objects describe probability laws used throughout MC/DC,
-    including source distributions and secondary-particle distributions.
-
-    Parameters
-    ----------
-    child_label : str
-        Framework label identifying the concrete distribution subtype.
-
-    child_type : int
-        Integer identifier specifying the concrete distribution subtype.
-
-    non_numba : list of str
-        Additional attribute names excluded from the compiled representation.
-    """
-
     def __init__(
         self,
         child_label: str,
         child_type: int,
         non_numba: list[str],
     ) -> None:
-        """Initialize distribution framework metadata."""
-        super().__init__(
-            label="distribution",
-            child_label=child_label,
-            child_type=child_type,
-            non_numba=non_numba,
-        )
-
-    def __repr__(self) -> str:
-        """Return a human-readable description of the distribution."""
-        text = "\n"
-        text += f"{decode_type(self.child_type)}\n"
-        text += f"  - ID: {self.ID}\n"
-        return text
-
-
-def decode_type(child_type: int) -> str:
-    """Convert a distribution type code to a human-readable name.
-
-    Parameters
-    ----------
-    child_type : int
-        Distribution type code.
-
-    Returns
-    -------
-    str
-        Human-readable distribution name.
-
-    Raises
-    ------
-    ValueError
-        If the distribution type code is unknown.
-    """
-    if child_type == DISTRIBUTION_NONE:
-        return "Distribution (None)"
-    if child_type == DISTRIBUTION_PMF:
-        return "Distribution (PMF)"
-    if child_type == DISTRIBUTION_TABULATED:
-        return "Distribution (Tabulated)"
-    if child_type == DISTRIBUTION_MULTITABLE:
-        return "Distribution (Multi-table)"
-    if child_type == DISTRIBUTION_LEVEL_SCATTERING:
-        return "Distribution (Level scattering)"
-    if child_type == DISTRIBUTION_EVAPORATION:
-        return "Distribution (Evaporation)"
-    if child_type == DISTRIBUTION_MAXWELLIAN:
-        return "Distribution (Maxwellian spectrum)"
-    if child_type == DISTRIBUTION_KALBACH_MANN:
-        return "Distribution (Kalbach-Mann)"
-    if child_type == DISTRIBUTION_TABULATED_ENERGY_ANGLE:
-        return "Distribution (Tabulated energy-angle)"
-    if child_type == DISTRIBUTION_N_BODY:
-        return "Distribution (N-body)"
-
-    raise ValueError(f"Unknown distribution type: {child_type}")
+        # MC/DC framework metadata
+        super().__init__("distribution", child_label, child_type, non_numba)
 
 
 # ======================================================================================
@@ -124,15 +53,9 @@ def decode_type(child_type: int) -> str:
 
 
 class DistributionNone(DistributionBase):
-    """Placeholder for the absence of a stored distribution."""
-
     def __init__(self) -> None:
-        """Create an empty distribution object."""
-        super().__init__(
-            child_label="none_distribution",
-            child_type=DISTRIBUTION_NONE,
-            non_numba=[],
-        )
+        # MC/DC framework metadata
+        super().__init__("none_distribution", DISTRIBUTION_NONE, [])
 
 
 # ======================================================================================
@@ -141,33 +64,13 @@ def __init__(self) -> None:
 
 
 class DistributionPMF(DistributionBase):
-    """Discrete probability mass function."""
-
     value: NDArray[float64]
     pmf: NDArray[float64]
     cmf: NDArray[float64]
 
-    def __init__(
-        self,
-        value: ArrayLike,
-        pmf: ArrayLike,
-    ) -> None:
-        """Create a discrete probability mass function.
-
-        Parameters
-        ----------
-        value : array_like
-            Values sampled by the distribution.
-
-        pmf : array_like
-            Probability masses corresponding to ``value``. The masses are
-            normalized internally.
-        """
-        super().__init__(
-            child_label="pmf_distribution",
-            child_type=DISTRIBUTION_PMF,
-            non_numba=[],
-        )
+    def __init__(self, value: ArrayLike, pmf: ArrayLike) -> None:
+        # MC/DC framework metadata
+        super().__init__("pmf_distribution", DISTRIBUTION_PMF, [])
 
         self.value = np.asarray(value, dtype=float64)
         pmf_array = np.asarray(pmf, dtype=float64)
@@ -184,8 +87,8 @@ def __init__(
         self.pmf, self.cmf = cmf_from_pmf(pmf_array)
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the PMF."""
         text = super().__repr__()
+
         text += f"  - value {print_1d_array(self.value)}\n"
         text += f"  - pmf {print_1d_array(self.pmf)}\n"
         return text
@@ -197,17 +100,6 @@ def __repr__(self) -> str:
 
 
 class DistributionTabulated(DistributionBase):
-    """One-dimensional tabulated probability distribution.
-
-    The distribution is stored as a :class:`DataTable` whose independent
-    variable contains sample values and whose dependent variable contains the
-    normalized probability density. The cumulative distribution is stored as
-    auxiliary table data for sampling.
-
-    A PDF input is treated as piecewise linear. A CDF input is treated as
-    piecewise linear, producing a histogram PDF.
-    """
-
     pdf: DataTable
 
     def __init__(
@@ -216,30 +108,8 @@ def __init__(
         pdf: ArrayLike | None = None,
         cdf: ArrayLike | None = None,
     ) -> None:
-        """Create a tabulated distribution from either a PDF or CDF.
-
-        Parameters
-        ----------
-        value : array_like
-            Sample values.
-
-        pdf : array_like, optional
-            Probability densities at the sample values. The PDF is normalized
-            and its CDF is calculated by trapezoidal integration.
-
-        cdf : array_like, optional
-            Cumulative probabilities at the sample values. The CDF is
-            normalized and a histogram PDF is derived from it.
-
-        Notes
-        -----
-        Exactly one of ``pdf`` or ``cdf`` must be provided.
-        """
-        super().__init__(
-            child_label="tabulated_distribution",
-            child_type=DISTRIBUTION_TABULATED,
-            non_numba=[],
-        )
+        # MC/DC framework metadata
+        super().__init__("tabulated_distribution", DISTRIBUTION_TABULATED, [])
 
         if (pdf is None) == (cdf is None):
             print_error("Exactly one of pdf or cdf must be provided.")
@@ -286,8 +156,8 @@ def __init__(
         )
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
+
         text += f"  - value {print_1d_array(self.pdf.x)}\n"
         text += f"  - probability density {print_1d_array(self.pdf.y)}\n"
         text += "  - cumulative distribution " f"{print_1d_array(self.pdf.aux[0])}\n"
@@ -300,12 +170,6 @@ def __repr__(self) -> str:
 
 
 class DistributionMultiTable(DistributionBase):
-    """Distribution represented by tabulated distributions on a grid.
-
-    Each grid point owns one :class:`DistributionTabulated`. The flattened
-    ``value`` array is divided into individual tables using ``offset``.
-    """
-
     grid: NDArray[float64]
     tables: list[DistributionTabulated]
 
@@ -317,34 +181,8 @@ def __init__(
         pdf: ArrayLike | None = None,
         cdf: ArrayLike | None = None,
     ) -> None:
-        """Create a multi-table distribution.
-
-        Parameters
-        ----------
-        grid : array_like
-            Grid values associated with the tabulated distributions.
-
-        offset : array_like
-            Starting index of each table in the flattened arrays.
-
-        value : array_like
-            Flattened sample values for all tables.
-
-        pdf : array_like, optional
-            Flattened PDF values.
-
-        cdf : array_like, optional
-            Flattened CDF values.
-
-        Notes
-        -----
-        Exactly one of ``pdf`` or ``cdf`` must be provided.
-        """
-        super().__init__(
-            child_label="multi_table_distribution",
-            child_type=DISTRIBUTION_MULTITABLE,
-            non_numba=[],
-        )
+        # MC/DC framework metadata
+        super().__init__("multi_table_distribution", DISTRIBUTION_MULTITABLE, [])
 
         if (pdf is None) == (cdf is None):
             print_error("Exactly one of pdf or cdf must be provided.")
@@ -407,17 +245,19 @@ def __init__(
                     value_array[start_i:stop_i],
                     pdf=pdf_array[start_i:stop_i],
                 )
-            else:
+            elif cdf_array is not None:
                 table = DistributionTabulated(
                     value_array[start_i:stop_i],
                     cdf=cdf_array[start_i:stop_i],
                 )
+            else:
+                table = DistributionTabulated([])  # Unachievable
 
             self.tables.append(table)
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
+
         text += f"  - grid: {print_1d_array(self.grid)}\n"
         text += f"  - tables: {len(self.tables)}\n"
 
@@ -433,25 +273,23 @@ def __repr__(self) -> str:
 
 
 class DistributionLevelScattering(DistributionBase):
-    """Level-scattering energy distribution."""
-
     C1: float
     C2: float
 
     def __init__(self, C1: float, C2: float) -> None:
-        """Create a level-scattering distribution."""
+        # MC/DC framework metadata
         super().__init__(
-            child_label="level_scattering_distribution",
-            child_type=DISTRIBUTION_LEVEL_SCATTERING,
-            non_numba=[],
+            "level_scattering_distribution",
+            DISTRIBUTION_LEVEL_SCATTERING,
+            [],
         )
 
         self.C1 = C1
         self.C2 = C2
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
+
         text += f"  - C1: {self.C1} [/eV^l]\n"
         text += f"  - C2: {self.C2}\n"
         return text
@@ -463,25 +301,19 @@ def __repr__(self) -> str:
 
 
 class DistributionEvaporation(DistributionBase):
-    """Evaporation energy distribution."""
-
     nuclear_temperature: DataTable
     restriction_energy: float
 
     def __init__(
         self,
-        nuclear_temperature_energy_grid: ArrayLike,
-        nuclear_temperature_value: ArrayLike,
+        nuclear_temperature_energy_grid: NDArray[float64],
+        nuclear_temperature_value: NDArray[float64],
         restriction_energy: float,
         temperature_interpolations: int | Sequence[int],
         interpolation_boundaries: Sequence[int] | None,
     ) -> None:
-        """Create an evaporation distribution."""
-        super().__init__(
-            child_label="evaporation_distribution",
-            child_type=DISTRIBUTION_EVAPORATION,
-            non_numba=[],
-        )
+        # MC/DC framework metadata
+        super().__init__("evaporation_distribution", DISTRIBUTION_EVAPORATION, [])
 
         self.restriction_energy = restriction_energy
         self.nuclear_temperature = DataTable(
@@ -492,8 +324,8 @@ def __init__(
         )
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
+
         text += f"  - Restriction energy: {self.restriction_energy} [eV]\n"
         text += (
             "  - Nuclear temperature "
@@ -512,25 +344,19 @@ def __repr__(self) -> str:
 
 
 class DistributionMaxwellian(DistributionBase):
-    """Maxwellian energy distribution."""
-
     nuclear_temperature: DataTable
     restriction_energy: float
 
     def __init__(
         self,
-        nuclear_temperature_energy_grid: ArrayLike,
-        nuclear_temperature_value: ArrayLike,
+        nuclear_temperature_energy_grid: NDArray[float64],
+        nuclear_temperature_value: NDArray[float64],
         restriction_energy: float,
         temperature_interpolations: int | Sequence[int],
         interpolation_boundaries: Sequence[int] | None,
     ) -> None:
-        """Create a Maxwellian distribution."""
-        super().__init__(
-            child_label="maxwellian_distribution",
-            child_type=DISTRIBUTION_MAXWELLIAN,
-            non_numba=[],
-        )
+        # MC/DC framework metadata
+        super().__init__("maxwellian_distribution", DISTRIBUTION_MAXWELLIAN, [])
 
         self.restriction_energy = restriction_energy
         self.nuclear_temperature = DataTable(
@@ -541,8 +367,8 @@ def __init__(
         )
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
+
         text += f"  - Restriction energy: {self.restriction_energy} [eV]\n"
         text += (
             "  - Nuclear temperature "
@@ -561,8 +387,6 @@ def __repr__(self) -> str:
 
 
 class DistributionKalbachMann(DistributionBase):
-    """Kalbach-Mann correlated energy-angle distribution."""
-
     energy: NDArray[float64]
     offset: NDArray[int64]
     energy_out: NDArray[float64]
@@ -580,12 +404,8 @@ def __init__(
         precompound_factor: ArrayLike,
         angular_slope: ArrayLike,
     ) -> None:
-        """Create a Kalbach-Mann distribution."""
-        super().__init__(
-            child_label="kalbach_mann_distribution",
-            child_type=DISTRIBUTION_KALBACH_MANN,
-            non_numba=[],
-        )
+        # MC/DC framework metadata
+        super().__init__("kalbach_mann_distribution", DISTRIBUTION_KALBACH_MANN, [])
 
         self.energy = np.asarray(energy, dtype=float64)
         self.offset = np.asarray(offset, dtype=int64)
@@ -604,8 +424,8 @@ def __init__(
         )
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
+
         text += f"  - grid {print_1d_array(self.energy)} [eV]\n"
         text += f"  - offset {print_1d_array(self.offset)}\n"
         text += f"  - energy {print_1d_array(self.energy_out)} [eV]\n"
@@ -621,8 +441,6 @@ def __repr__(self) -> str:
 
 
 class DistributionTabulatedEnergyAngle(DistributionBase):
-    """Tabulated correlated energy-angle distribution."""
-
     energy: NDArray[float64]
     offset: NDArray[int64]
     energy_out: NDArray[float64]
@@ -643,7 +461,7 @@ def __init__(
         cosine: ArrayLike,
         cosine_pdf: ArrayLike,
     ) -> None:
-        """Create a tabulated correlated energy-angle distribution."""
+        # MC/DC framework metadata
         super().__init__(
             child_label="tabulated_energy_angle_distribution",
             child_type=DISTRIBUTION_TABULATED_ENERGY_ANGLE,
@@ -702,8 +520,8 @@ def __init__(
             )
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
+
         text += f"  - grid {print_1d_array(self.energy)} [eV]\n"
         text += f"  - offset {print_1d_array(self.offset)}\n"
         text += f"  - energy {print_1d_array(self.energy_out)} [eV]\n"
@@ -720,12 +538,6 @@ def __repr__(self) -> str:
 
 
 class DistributionNBody(DistributionBase):
-    """N-body energy distribution represented by a tabulated PDF and CDF.
-
-    The input probability density is normalized internally, and the
-    corresponding cumulative distribution is generated for sampling.
-    """
-
     pdf: DataTable
 
     def __init__(
@@ -733,22 +545,8 @@ def __init__(
         values: ArrayLike,
         probabilities: ArrayLike,
     ) -> None:
-        """Create an N-body distribution.
-
-        Parameters
-        ----------
-        values : array_like
-            Tabulated sample values.
-
-        probabilities : array_like
-            Probability densities at the sample values. The values do not need
-            to be normalized.
-        """
-        super().__init__(
-            child_label="nbody_distribution",
-            child_type=DISTRIBUTION_N_BODY,
-            non_numba=[],
-        )
+        # MC/DC framework metadata
+        super().__init__("nbody_distribution", DISTRIBUTION_N_BODY, [])
 
         value_array = np.asarray(values, dtype=float64)
         probability_array = np.asarray(probabilities, dtype=float64)
@@ -773,8 +571,8 @@ def __init__(
         )
 
     def __repr__(self) -> str:
-        """Return a human-readable summary of the distribution."""
         text = super().__repr__()
+
         text += f"  - value {print_1d_array(self.pdf.x)}\n"
         text += f"  - pdf {print_1d_array(self.pdf.y)}\n"
         return text
diff --git a/mcdc/object_/electron_reaction.py b/mcdc/object_/electron_reaction.py
index 452dfa3c4..0b102b70c 100644
--- a/mcdc/object_/electron_reaction.py
+++ b/mcdc/object_/electron_reaction.py
@@ -42,8 +42,8 @@ def __init__(self, type_, MT, xs, xs_offset, reference_frame):
         self.reference_frame = reference_frame
 
     def __repr__(self):
-        text = "\n"
-        text += f"{decode_type(self.type)}\n"
+        text = super().__repr__()
+
         text += f"  - ID: {self.ID}\n"
         text += f"  - MT: {self.MT}\n"
         text += f"  - XS {print_1d_array(self.xs)} barn\n"
@@ -51,17 +51,6 @@ def __repr__(self):
         return text
 
 
-def decode_type(type_):
-    if type_ == ELECTRON_REACTION_IONIZATION:
-        return "Electron ionization"
-    elif type_ == ELECTRON_REACTION_ELASTIC_SCATTERING:
-        return "Electron elastic scattering"
-    elif type_ == ELECTRON_REACTION_BREMSSTRAHLUNG:
-        return "Electron bremsstrahlung"
-    elif type_ == ELECTRON_REACTION_EXCITATION:
-        return "Electron excitation"
-
-
 def decode_reference_frame(type_):
     if type_ == REFERENCE_FRAME_LAB:
         return "Laboratory"
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 5b7878f08..af6b4d171 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -31,75 +31,29 @@ def __init__(
         child_type: int,
         non_numba: list[str],
     ) -> None:
-        """Initialize material base framework metadata."""
-        super().__init__(
-            label="material",
-            child_label=child_label,
-            child_type=child_type,
-            non_numba=non_numba,
-        )
-
-        # Set name
-        if name == "":
-            self.name = "(Unnamed material)"
-        else:
-            self.name = name
+        # MC/DC framework metadata
+        super().__init__("material", child_label, child_type, non_numba)
 
+        self.name = name or "(Unnamed material)"
         self.fissionable = False
 
     def __repr__(self):
-        text = "\n"
-        text += f"{decode_type(self.child_type)}\n"
+        text = super().__repr__()
+
         text += f"  - Name: {self.name}\n"
         text += f"  - Fissionable: {self.fissionable}\n"
         return text
 
 
-def decode_type(type_):
-    if type_ == MATERIAL:
-        return "Material"
-    elif type_ == MATERIAL_MG:
-        return "Multigroup material"
-
-
 # ======================================================================================
 # Native material
 # ======================================================================================
 
 
 class Material(MaterialBase):
-    """
-    Define a continuous-energy material from a nuclide composition.
-
-    Parameters
-    ----------
-    name : str, optional
-        User label.
-    nuclide_composition : dict
-        Dictionary mapping nuclide names (str) to atom densities (float).
-    element_composition : dict
-        Dictionary mapping element names (str) to atom densities (float).
-    temperature : float, optional
-        Temperature in Kelvin (default 293.6 K).
-
-    Returns
-    -------
-    Material
-        The material object.
-
-    Notes
-    -----
-    Requires the ``MCDC_LIB`` environment variable to point to the nuclear
-    data library directory.
-
-    See Also
-    --------
-    mcdc.MaterialMG : Creates a multigroup material.
-    """
-
-    nuclide_composition: dict[Nuclide, float]
-    element_composition: dict[Element, float]
-    #
+    nuclide_composition: dict[Nuclide, float]  # Non-numba
+    element_composition: dict[Element, float]  # Non-numba
+
     nuclides: list[Nuclide]
     elements: list[Element]
     nuclide_densities: NDArray[float64]
@@ -112,11 +66,12 @@ def __init__(
         element_composition: dict[str, float] = {},
         temperature: float = 293.6,
     ):
+        # MC/DC framework metadata
         super().__init__(
             name,
-            child_label="native_material",
-            child_type=MATERIAL,
-            non_numba=["nuclide_composition", "element_composition"],
+            "native_material",
+            MATERIAL,
+            ["nuclide_composition", "element_composition"],
         )
 
         # Temperature
@@ -213,6 +168,7 @@ def __init__(
 
     def __repr__(self):
         text = super().__repr__()
+
         text += f"  - Temperature: {self.temperature} K\n"
         if len(self.nuclide_composition) > 0:
             text += f"  - Nuclide composition [atoms/barn-cm]\n"
@@ -239,47 +195,6 @@ def __repr__(self):
 
 
 class MaterialMG(MaterialBase):
-    """
-    Define a multigroup material.
-
-    Cross-section arrays are provided as NumPy arrays of length ``G`` (number
-    of energy groups). Scatter and fission matrices are ``(G, G)``.
-
-    Parameters
-    ----------
-    name : str, optional
-        User label.
-    capture : ndarray, optional
-        Capture cross section for each group.
-    scatter : ndarray, optional
-        Scattering matrix ``(G, G)``.
-    fission : ndarray, optional
-        Fission cross section for each group.
-    nu_s : ndarray, optional
-        Average scattering multiplicity.
-    nu_p : ndarray, optional
-        Average prompt fission neutron yield.
-    nu_d : ndarray, optional
-        Average delayed fission neutron yield.
-    chi_p : ndarray, optional
-        Prompt fission spectrum.
-    chi_d : ndarray, optional
-        Delayed fission spectrum.
-    speed : ndarray, optional
-        Neutron speeds for each group (cm/s).
-    decay_rate : ndarray, optional
-        Delayed neutron precursor decay rates (1/s).
-
-    Returns
-    -------
-    MaterialMG
-        The multigroup material object.
-
-    See Also
-    --------
-    mcdc.Material : Creates a continuous-energy material.
-    """
-
     G: int
     J: int
     mgxs_speed: Annotated[NDArray[float64], ("G",)]
@@ -311,12 +226,8 @@ def __init__(
         speed: NDArray[float64] | NoneType = None,
         decay_rate: NDArray[float64] | NoneType = None,
     ):
-        super().__init__(
-            name,
-            child_label="multigroup_material",
-            child_type=MATERIAL_MG,
-            non_numba=[],
-        )
+        # MC/DC framework metadata
+        super().__init__(name, "multigroup_material", MATERIAL_MG, [])
 
         # Energy group size
         if capture is not None:
@@ -326,6 +237,7 @@ def __init__(
         elif fission is not None:
             G = len(fission)
         else:
+            G = 0
             print_error("Need to supply capture, scatter, or fission for MaterialMG")
         self.G = G
 
@@ -429,8 +341,9 @@ def __init__(
             else:
                 if chi_d is None:
                     print_error("Need to supply chi_d if nu_d is provided and G > 1")
-                # Transpose: [gout, dg] -> [dg, gout]
-                self.mgxs_chi_d = np.swapaxes(chi_d, 0, 1)[:, :]
+                else:
+                    # Transpose: [gout, dg] -> [dg, gout]
+                    self.mgxs_chi_d = np.swapaxes(chi_d, 0, 1)[:, :]
             # Normalize
             for dg in range(J):
                 if np.sum(self.mgxs_chi_d[dg, :]) > 0.0:
@@ -438,6 +351,7 @@ def __init__(
 
     def __repr__(self):
         text = super().__repr__()
+
         text += f"  - Multigroup data\n"
         text += f"    - G: {self.G}\n"
         text += f"    - J: {self.J}\n"
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index 9e97f4ecf..8212ea09d 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -46,20 +46,13 @@ def __init__(
         self.N_bin = 0
 
     def __repr__(self):
-        text = "\n"
-        text += f"{decode_type(self.type)}\n"
+        text = super().__repr__()
+
         text += f"  - Name: {self.name}\n"
         text += f"  - # of bins: {self.N_bin}\n"
         return text
 
 
-def decode_type(type_):
-    if type_ == MESH_UNIFORM:
-        return "Uniform mesh"
-    elif type_ == MESH_STRUCTURED:
-        return "Structured mesh"
-
-
 # ======================================================================================
 # Uniform mesh
 # ======================================================================================
diff --git a/mcdc/object_/neutron_reaction.py b/mcdc/object_/neutron_reaction.py
index 54313009d..08ca364fd 100644
--- a/mcdc/object_/neutron_reaction.py
+++ b/mcdc/object_/neutron_reaction.py
@@ -55,8 +55,8 @@ def __init__(self, type_, MT, xs, xs_offset, reference_frame, q_value):
         self.q_value = q_value
 
     def __repr__(self):
-        text = "\n"
-        text += f"{decode_type(self.type)}\n"
+        text = super().__repr__()
+
         text += f"  - ID: {self.ID}\n"
         text += f"  - MT: {self.MT}\n"
         text += f"  - XS {print_1d_array(self.xs)} barn\n"
@@ -65,17 +65,6 @@ def __repr__(self):
         return text
 
 
-def decode_type(type_):
-    if type_ == NEUTRON_REACTION_ELASTIC_SCATTERING:
-        return "Neutron elastic scattering"
-    elif type_ == NEUTRON_REACTION_CAPTURE:
-        return "Neutron capture"
-    elif type_ == NEUTRON_REACTION_INELASTIC_SCATTERING:
-        return "Neutron inelastic scattering"
-    elif type_ == NEUTRON_REACTION_FISSION:
-        return "Neutron fission"
-
-
 def decode_reference_frame(type_):
     if type_ == REFERENCE_FRAME_LAB:
         return "Laboratory"
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index a47d96366..1278db863 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -46,25 +46,6 @@
 
 
 class Simulation(MCDCBase):
-    """MC/DC transport simulation.
-
-    A ``Simulation`` represents a complete transport calculation. It combines
-    the physical model, source definitions, simulation settings, tally
-    definitions, and transport techniques required to execute a Monte Carlo
-    simulation.
-
-    A simulation is first constructed using Python objects. Before execution,
-    the model is compiled into an execution-ready representation optimized for
-    MC/DC's transport engine.
-
-    Notes
-    -----
-    The Python object graph is independent of the compiled representation used
-    during transport. Compilation traverses the object graph, assigns internal
-    identifiers, validates the model, and generates the data structures used by
-    the execution backend.
-    """
-
     _next_compile_ID: int = 1  # Non-Numba
 
     # Basic parameters
@@ -161,14 +142,7 @@ class Simulation(MCDCBase):
     source_seed: int
 
     def __init__(self, name: str = "") -> None:
-        """Create a simulation.
-
-        Parameters
-        ----------
-        name : str, optional
-            User-defined simulation name. If omitted, an unnamed simulation is
-            created.
-        """
+        # MC/DC framework metadata
         super().__init__(
             label="simulation",
             non_numba=[
@@ -190,8 +164,12 @@ def __init__(self, name: str = "") -> None:
         self.name = name or "(Unnamed simulation)"
         self.root_universe = Universe("Root Universe")
 
-        # Initialize with empty object lists
-        self._reset_object_lists()
+        # Initialize with empty model objects
+        self._reset_model()
+
+        # Also empty sources and tallies
+        self.sources = []
+        self.tallies = []
 
         # ==============================================================================
         # Simulation settings and techniques
@@ -269,7 +247,7 @@ def __init__(self, name: str = "") -> None:
         self.gpu_meta = GPUMeta()
         self.source_seed = 0
 
-    def _reset_object_lists(self) -> None:
+    def _reset_model(self) -> None:
         # Physics
         self.data = []
         self.distributions = []
@@ -278,7 +256,6 @@ def _reset_object_lists(self) -> None:
         self.nuclides = []
         self.elements = []
         self.materials = []
-        self.sources = []
 
         # Geometry
         self.surfaces = []
@@ -288,58 +265,19 @@ def _reset_object_lists(self) -> None:
         self.lattices = []
         self.meshes = []
 
-        # Tallies
-        self.tallies = []
-
     # ==================================================================================
     # Simulation object setters
     # ==================================================================================
 
     def set_model(self, cells: Sequence[Cell]) -> None:
-        """Set the simulation model.
-
-        Parameters
-        ----------
-        cells : Sequence[Cell]
-            Cells that define the root universe of the model.
-
-        Notes
-        -----
-        Only the root cells are stored. Connected geometry and physics objects are
-        discovered automatically during compilation.
-        """
         self.root_universe.cells = list(cells)
         self.compiled = False
 
     def set_sources(self, sources: Sequence[Source]) -> None:
-        """Set the simulation source definitions.
-
-        Parameters
-        ----------
-        sources : Sequence[Source]
-            Source definitions used to initialize particles.
-
-        Notes
-        -----
-        Connected distributions and supporting objects are collected during
-        compilation.
-        """
         self.sources = list(sources)
         self.compiled = False
 
     def set_tallies(self, tallies: Sequence[Tally]) -> None:
-        """Set the simulation tally definitions.
-
-        Parameters
-        ----------
-        tallies : Sequence[Tally]
-            Tallies used to score transport quantities.
-
-        Notes
-        -----
-        Connected meshes, filters, and other referenced objects are collected
-        during compilation.
-        """
         self.tallies = list(tallies)
         self.compiled = False
 
@@ -348,18 +286,6 @@ def set_tallies(self, tallies: Sequence[Tally]) -> None:
     # ==================================================================================
 
     def compile(self) -> None:
-        """Compile the simulation.
-
-        Compilation validates the simulation, discovers all connected objects,
-        assigns internal identifiers, and generates the execution-ready data
-        structures used by the transport engine.
-
-        Notes
-        -----
-        Compilation does not perform particle transport. It only prepares the
-        simulation for execution or other operations that require the compiled
-        representation.
-        """
         from mcdc.code_factory.python_objects_compiler import compile_simulation
 
         self.compile_ID = type(self)._next_compile_ID
@@ -379,47 +305,6 @@ def visualize_model(
         time,
         save_as,
     ) -> None:
-        """Visualize the simulation model.
-
-        Generate two-dimensional slices of the simulation geometry at one or more
-        times. If necessary, the simulation is compiled automatically before
-        visualization.
-
-        Parameters
-        ----------
-        vis_plane : {'xy', 'xz', 'yz', 'yx', 'zx', 'zy'}
-            Coordinate plane to visualize.
-
-        x : float or array_like
-            Plane x-coordinate for ``'yz'`` visualization, or x-axis range for
-            ``'xy'`` and ``'xz'`` visualizations.
-
-        y : float or array_like
-            Plane y-coordinate for ``'xz'`` visualization, or y-axis range for
-            ``'xy'`` and ``'yz'`` visualizations.
-
-        z : float or array_like
-            Plane z-coordinate for ``'xy'`` visualization, or z-axis range for
-            ``'xz'`` and ``'yz'`` visualizations.
-
-        pixels : array_like
-            Number of pixels along the two visualization axes.
-
-        colors : array_like
-            Sequence of ``(material, color)`` pairs used to render the model.
-
-        time : float or array_like
-            Time or times at which geometry snapshots are generated.
-
-        save_as : str, optional
-            Output filename. If omitted, the visualization is displayed without
-            saving.
-
-        Notes
-        -----
-        Visualization uses the compiled model representation but does not perform
-        particle transport or modify the compiled simulation state.
-        """
         if not self.compiled:
             self.compile()
 
@@ -428,17 +313,6 @@ def visualize_model(
         visualize_model(self, vis_plane, x, y, z, pixels, colors, time, save_as)
 
     def run(self) -> None:
-        """Execute the transport simulation.
-
-        If necessary, the simulation is compiled automatically before execution.
-
-        Notes
-        -----
-        Compilation is invalidated after execution because transport updates the
-        internal simulation state. If the Python model is modified directly without
-        using the public simulation interface, users are responsible for ensuring
-        the simulation is recompiled before subsequent operations.
-        """
         from mcdc.main import run_simulation
 
         if not self.compiled:
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index d4d8920fe..b815d7a3c 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -7,10 +7,7 @@
 
 ####
 
-import mcdc.object_.distribution as distribution
-
 from mcdc.constant import (
-    INTERPOLATION_LINEAR,
     PARTICLE_NEUTRON,
     PARTICLE_ELECTRON,
     PARTICLE_PROTON,
@@ -165,12 +162,14 @@ class Source(MCDCObject):
     """
 
     name: str
+
     # Position
     point_source: bool
     point: Annotated[NDArray[float64], (3,)]
     x: Annotated[NDArray[float64], (2,)]
     y: Annotated[NDArray[float64], (2,)]
     z: Annotated[NDArray[float64], (2,)]
+
     # Direction
     isotropic_direction: bool
     mono_direction: bool
@@ -178,19 +177,24 @@ class Source(MCDCObject):
     direction: Annotated[NDArray[float64], (3,)]
     polar_cosine: Annotated[NDArray[float64], (2,)]
     azimuthal: Annotated[NDArray[float64], (2,)]
+
     # Energy
     mono_energetic: bool
     energy_group: int
     energy: float
     energy_group_pmf: DistributionPMF
     energy_pdf: DistributionTabulated
+
     # Time
     discrete_time: bool
     time: float
     time_range: Annotated[NDArray[float64], (2,)]
-    #
+
+    # Misc.
     particle_type: int
     probability: float
+
+    # Movement
     moving: bool
     N_move: int
     N_move_grid: int
@@ -222,14 +226,10 @@ def __init__(
         #
         probability: float = 1.0,
     ):
+        # MC/DC framework metadata
+        super().__init__("source", [])
 
-        super().__init__(label="source", non_numba=[])
-
-        # Set name
-        if name == "":
-            self.name = "(Unnamed source)"
-        else:
-            self.name = name
+        self.name = name or "(Unnamed source)"
 
         # ==============================================================================
         # Default attributes
@@ -314,7 +314,7 @@ def __init__(
         if energy_group is not None:
             if type(energy_group) == int:
                 self.energy_group = energy_group
-            else:
+            elif isinstance(energy_group, Sequence):
                 self.mono_energetic = False
                 self.energy_group_pmf = DistributionPMF(
                     energy_group[0], energy_group[1]
@@ -322,7 +322,7 @@ def __init__(
         elif energy is not None:
             if type(energy) == float:
                 self.energy = energy
-            else:
+            elif isinstance(energy, Sequence):
                 self.mono_energetic = False
                 self.energy_pdf = DistributionTabulated(
                     np.array(energy[0]), np.array(energy[1])
@@ -354,9 +354,20 @@ def __init__(
         self.move_time_grid = np.array([0.0, INF])
         self.move_translations = np.zeros((2, 3))
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        # Already compiled?
+        if not super()._compile_into_simulation(simulation):
+            return False
+
+        # Compile distributions
+        self.energy_group_pmf._compile_into_simulation(simulation)
+        self.energy_pdf._compile_into_simulation(simulation)
+
+        return True
+
     def __repr__(self):
-        text = "\n"
-        text += f"Source\n"
+        text = super().__repr__()
+
         text += f"  - Name: {self.name}\n"
         text += f"  - Particle: {decode_particle_type(self.particle_type)}\n"
         text += f"  - Probability: {self.probability * 100}%\n"
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 533749836..55968c1d9 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -41,66 +41,6 @@
 
 
 class Surface(MCDCObject):
-    """
-    Geometric surface primitive with optional boundary condition and motion.
-
-    Surfaces are registered non-singletons and receive a stable ``ID``. Factory
-    constructors (:meth:`PlaneX`, :meth:`CylinderZ`, etc.) set the quadric
-    coefficients (A..J) and linearity flag. Motion segments can be defined with
-    :meth:`move`.
-
-    Parameters
-    ----------
-    type\\_ : int
-        One of ``SURFACE_*`` constants (e.g., ``SURFACE_PLANE_X``).
-    name : str
-        Optional label for reporting.
-    boundary_condition : str
-        Boundary behavior at the surface (``"none"``, ``"vacuum"``, or ``"reflective"``).
-
-    Attributes
-    ----------
-    ID : int
-        Index in the global registry (assigned on construction).
-    type\\_ : int
-        Surface type code (``SURFACE_*``).
-    name : str
-        User label.
-    boundary_condition : int
-        One of ``BC_NONE``, ``BC_VACUUM``, ``BC_REFLECTIVE``.
-    A,B,C,D,E,F,G,H,I,J : float
-        Quadric coefficients defining the implicit surface.
-    linear : bool
-        True for linear (plane) surfaces.
-    quadric : bool
-        True for quadric (e.g.,cylinder) surfaces.
-    quartic : bool
-        True for quartic (e.g., torus) surfaces.
-    nx, ny, nz : float
-        Outward normal components for linear planes.
-    moving : bool
-        True if :meth:`move` has been called.
-    N_move : int
-        Number of motion segments plus the final static segment.
-    move_velocities : (N_move, 3) ndarray
-        Per-segment velocity vectors.
-    move_durations : (N_move,) ndarray
-        Per-segment durations (s).
-    move_time_grid : (N_move+1,) ndarray
-        Cumulative time breakpoints.
-    move_translations : (N_move+1, 3) ndarray
-        Cumulative translations at each breakpoint.
-
-    See Also
-    --------
-    Region
-        Use unary ``+`` / ``-`` to form half-spaces: ``+surface`` or ``-surface``.
-    decode_type
-        Human-readable surface type.
-    decode_BC_type
-        Human-readable boundary condition name.
-    """
-
     type: int
     name: str
     boundary_condition: int
@@ -132,8 +72,8 @@ class Surface(MCDCObject):
     tallies: list[TallySurfaceCrossing]
 
     def __init__(self, type_, name, boundary_condition):
-        """Initialize surface framework metadata."""
-        super().__init__(label="surface", non_numba=[])
+        # MC/DC framework metadata
+        super().__init__("surface", [])
 
         # Type and name
         self.type = type_
@@ -190,17 +130,16 @@ def __init__(self, type_, name, boundary_condition):
         # Surface tallies
         self.tallies = []
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        # Already compiled?
+        if not super()._compile_into_simulation(simulation):
+            return False
+
+        return True
+
     def __repr__(self):
-        """
-        Return a human-readable description including type-specific parameters.
-
-        Returns
-        -------
-        str
-            Multi-line formatted string with ID, name, BC, and geometry details.
-        """
-        text = "\n"
-        text += f"{decode_type(self.type)}\n"
+        text = super().__repr__()
+
         text += f"  - Name: {self.name}\n"
         text += f"  - Boundary condition: {decode_BC_type(self.boundary_condition)}\n"
 
@@ -303,23 +242,6 @@ def PlaneX(
         x: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create a plane perpendicular to +x at x = constant.
-
-        Parameters
-        ----------
-        name : str, optional
-            User label.
-        x : float, default 0.0
-            Plane location (cm).
-        boundary_condition : str, optional
-            Boundary type (``"none"``, ``"vacuum"``, or ``"reflective"``).
-
-        Returns
-        -------
-        Surface
-            Linear plane with normal ``(+1, 0, 0)``.
-        """
         type_ = SURFACE_PLANE_X
         surface = cls(type_, name, boundary_condition)
 
@@ -340,23 +262,6 @@ def PlaneY(
         y: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create a plane perpendicular to +y at y = constant.
-
-        Parameters
-        ----------
-        name : str, optional
-            User label.
-        y : float, default 0.0
-            Plane location (cm).
-        boundary_condition : str, optional
-            Boundary type (``"none"``, ``"vacuum"``, or ``"reflective"``).
-
-        Returns
-        -------
-        Surface
-            Linear plane with normal ``(0, +1, 0)``.
-        """
         type_ = SURFACE_PLANE_Y
         surface = cls(type_, name, boundary_condition)
 
@@ -377,23 +282,6 @@ def PlaneZ(
         z: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create a plane perpendicular to +z at z = constant.
-
-        Parameters
-        ----------
-        name : str, optional
-            User label.
-        z : float, default 0.0
-            Plane location (cm).
-        boundary_condition : str, optional
-            Boundary type (``"none"``, ``"vacuum"``, or ``"reflective"``).
-
-        Returns
-        -------
-        Surface
-            Linear plane with normal ``(0, 0, +1)``.
-        """
         type_ = SURFACE_PLANE_Z
         surface = cls(type_, name, boundary_condition)
 
@@ -417,25 +305,6 @@ def Plane(
         D: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create a general plane defined by A x + B y + C z + D = 0.
-
-        The normal is normalized to unit length and stored in ``(nx, ny, nz)``.
-
-        Parameters
-        ----------
-        name : str, optional
-            User label.
-        A, B, C, D : float
-            Plane coefficients.
-        boundary_condition : str, optional
-            Boundary type (``"none"``, ``"vacuum"``, or ``"reflective"``).
-
-        Returns
-        -------
-        Surface
-            Linear plane with normalized normal vector.
-        """
         type_ = SURFACE_PLANE
         surface = cls(type_, name, boundary_condition)
 
@@ -470,25 +339,6 @@ def CylinderX(
         radius: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create an infinite cylinder aligned with the x-axis.
-
-        Parameters
-        ----------
-        name : str, optional
-            User label.
-        center : (2,) array_like of float, default (0, 0)
-            Cylinder center in (y, z) (cm).
-        radius : float, default 1.0
-            Cylinder radius (cm).
-        boundary_condition : str, optional
-            Boundary type (``"none"``, ``"vacuum"``, or ``"reflective"``).
-
-        Returns
-        -------
-        Surface
-            Quadratic cylinder surface.
-        """
         type_ = SURFACE_CYLINDER_X
         surface = cls(type_, name, boundary_condition)
 
@@ -516,25 +366,6 @@ def CylinderY(
         radius: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create an infinite cylinder aligned with the y-axis.
-
-        Parameters
-        ----------
-        name : str, optional
-            User label.
-        center : (2,) array_like of float
-            Cylinder center in (x, z) (cm).
-        radius : float
-            Cylinder radius (cm).
-        boundary_condition : str, optional
-            Boundary type (``"none"``, ``"vacuum"``, or ``"reflective"``).
-
-        Returns
-        -------
-        Surface
-            Quadratic cylinder surface.
-        """
         type_ = SURFACE_CYLINDER_Y
         surface = cls(type_, name, boundary_condition)
 
@@ -562,25 +393,6 @@ def CylinderZ(
         radius: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create an infinite cylinder aligned with the z-axis.
-
-        Parameters
-        ----------
-        name : str, optional
-            User label.
-        center : (2,) array_like of float
-            Cylinder center in (x, y) (cm).
-        radius : float
-            Cylinder radius (cm).
-        boundary_condition : str, optional
-            Boundary type (``"none"``, ``"vacuum"``, or ``"reflective"``).
-
-        Returns
-        -------
-        Surface
-            Quadratic cylinder surface.
-        """
         type_ = SURFACE_CYLINDER_Z
         surface = cls(type_, name, boundary_condition)
 
@@ -610,25 +422,6 @@ def Cylinder(
         point: Sequence[float] = [0.0, 0.0, 0.0],
         boundary_condition: str = "none",
     ):
-        """
-        Create a general infinite cylinder with an arbitrary axis.
-
-        Parameters
-        ----------
-        name : str, optional
-        radius : float
-            Cylinder radius (cm).
-        axis : (3,) array_like of float
-            Direction vector of the cylinder axis (normalized automatically).
-        point : (3,) array_like of float
-            A point on the cylinder axis (cm).
-        boundary_condition : {"none","vacuum","reflective"}, optional
-
-        Returns
-        -------
-        Surface
-            General cylinder surface.
-        """
         type_ = SURFACE_CYLINDER
         surface = cls(type_, name, boundary_condition)
 
@@ -669,25 +462,6 @@ def Sphere(
         radius: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create a sphere.
-
-        Parameters
-        ----------
-        name : str, optional
-            User label.
-        center : (3,) array_like of float
-            Sphere center (x, y, z) in cm.
-        radius : float
-            Radius (cm).
-        boundary_condition : str, optional
-            Boundary type (``"none"``, ``"vacuum"``, or ``"reflective"``).
-
-        Returns
-        -------
-        Surface
-            Quadratic spherical surface.
-        """
         type_ = SURFACE_SPHERE
         surface = cls(type_, name, boundary_condition)
 
@@ -717,26 +491,6 @@ def ConeX(
         t_sq: float = 1.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create an infinite cone with axis along the x-axis.
-
-        Equation: (y - y0)^2 + (z - z0)^2 - t_sq * (x - x0)^2 = 0
-
-        Parameters
-        ----------
-        name : str, optional
-        apex : (3,) array_like of float
-            Cone apex (x0, y0, z0) in cm.
-        t_sq : float
-            Squared tangent of the half-angle: t_sq = tan^2(theta).
-            For a 45-degree half-angle use t_sq = 1.0.
-        boundary_condition : {"none","vacuum","reflective"}, optional
-
-        Returns
-        -------
-        Surface
-            Cone-X surface.
-        """
         type_ = SURFACE_CONE_X
         surface = cls(type_, name, boundary_condition)
 
@@ -764,25 +518,6 @@ def ConeY(
         t_sq: float = 1.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create an infinite cone with axis along the y-axis.
-
-        Equation: (x - x0)^2 + (z - z0)^2 - t_sq * (y - y0)^2 = 0
-
-        Parameters
-        ----------
-        name : str, optional
-        apex : (3,) array_like of float
-            Cone apex (x0, y0, z0) in cm.
-        t_sq : float
-            Squared tangent of the half-angle: t_sq = tan^2(theta).
-        boundary_condition : {"none","vacuum","reflective"}, optional
-
-        Returns
-        -------
-        Surface
-            Cone-Y surface.
-        """
         type_ = SURFACE_CONE_Y
         surface = cls(type_, name, boundary_condition)
 
@@ -810,25 +545,6 @@ def ConeZ(
         t_sq: float = 1.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create an infinite cone with axis along the z-axis.
-
-        Equation: (x - x0)^2 + (y - y0)^2 - t_sq * (z - z0)^2 = 0
-
-        Parameters
-        ----------
-        name : str, optional
-        apex : (3,) array_like of float
-            Cone apex (x0, y0, z0) in cm.
-        t_sq : float
-            Squared tangent of the half-angle: t_sq = tan^2(theta).
-        boundary_condition : {"none","vacuum","reflective"}, optional
-
-        Returns
-        -------
-        Surface
-            Cone surface.
-        """
         type_ = SURFACE_CONE_Z
         surface = cls(type_, name, boundary_condition)
 
@@ -864,24 +580,6 @@ def Quadric(
         J: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create a general quadric:
-            A x^2 + B y^2 + C z^2 + D xy + E yz + F zx + G x + H y + I z + J = 0
-
-        Parameters
-        ----------
-        name : str, optional
-            User label.
-        A,B,C,D,E,F,G,H,I,J : float
-            Quadric coefficients.
-        boundary_condition : str, optional
-            Boundary type (``"none"``, ``"vacuum"``, or ``"reflective"``).
-
-        Returns
-        -------
-        Surface
-            General quadratic surface.
-        """
         type_ = SURFACE_QUADRIC
         surface = cls(type_, name, boundary_condition)
 
@@ -913,24 +611,6 @@ def TorusX(
         r: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create a torus on the y-z plane radially symmetric around the x axis:
-            f(x, y, z) = ( sqrt[(y - B)^2 + (z - C)^2] - R )^2 + (x - A)^2 - r^2
-
-        Parameters
-        ----------
-        name : str, optional
-        A,B,C,R,r : float
-            A, B, C are displacement values for the torus in the x, y, z directions respectively
-            R is the radius around which a circle is revolved about the axis of revolution (parallel with the x-axis)
-            r is the radius of the circle that is being revolved
-        boundary_condition : {"none","vacuum","reflective"}, optional
-
-        Returns
-        -------
-        Surface
-            Torus surface.
-        """
         type_ = SURFACE_TORUS_X
         surface = cls(type_, name, boundary_condition)
 
@@ -958,24 +638,6 @@ def TorusY(
         r: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create a torus on the x-z plane radially symmetric around the y axis:
-            f(x, y, z) = ( sqrt[(x - A)^2 + (z - C)^2] - R )^2 + (y - B)^2 - r^2
-
-        Parameters
-        ----------
-        name : str, optional
-        A,B,C,R,r : float
-            A, B, C are displacement values for the torus in the x, y, z directions respectively
-            R is the radius around which a circle is revolved about the axis of revolution (parallel with the y-axis)
-            r is the radius of the circle that is being revolved
-        boundary_condition : {"none","vacuum","reflective"}, optional
-
-        Returns
-        -------
-        Surface
-            Torus surface.
-        """
         type_ = SURFACE_TORUS_Y
         surface = cls(type_, name, boundary_condition)
 
@@ -1003,24 +665,6 @@ def TorusZ(
         r: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create a torus on the x-y plane radially symmetric around the z axis:
-            f(x, y, z) = ( sqrt[(x - A)^2 + (y - B)^2] - R )^2 + (z - C)^2 - r^2
-
-        Parameters
-        ----------
-        name : str, optional
-        A,B,C,R,r : float
-            A, B, C are displacement values for the torus in the x, y, z directions respectively
-            R is the radius around which a circle is revolved about the axis of revolution (parallel with the z-axis)
-            r is the radius of the circle that is being revolved
-        boundary_condition : {"none","vacuum","reflective"}, optional
-
-        Returns
-        -------
-        Surface
-            Torus surface.
-        """
         type_ = SURFACE_TORUS_Z
         surface = cls(type_, name, boundary_condition)
 
@@ -1047,27 +691,6 @@ def Torus(
         r: float = 0.0,
         boundary_condition: str = "none",
     ):
-        """
-        Create a general torus with an arbitrary axis.
-
-        Parameters
-        ----------
-        name : str, optional
-        center : (3,) array_like of float
-            Torus center (cm).
-        axis : (3,) array_like of float
-            Direction vector of the torus axis (normalized automatically).
-        R : float
-            Major radius.
-        r : float
-            Minor radius of the tube.
-        boundary_condition : {"none","vacuum","reflective"}, optional
-
-        Returns
-        -------
-        Surface
-            General torus surface.
-        """
         x, y, z = center
         ax, ay, az = axis
         norm = (ax**2 + ay**2 + az**2) ** 0.5
@@ -1099,25 +722,9 @@ def Torus(
     # ==================================================================================
 
     def __pos__(self):
-        """
-        Half-space on the **outward** side of the surface.
-
-        Returns
-        -------
-        Region
-            Region representing ``n · r + J >= 0`` (sign convention per type).
-        """
         return Region.make_halfspace(self, +1)
 
     def __neg__(self):
-        """
-        Half-space on the **inward** side of the surface.
-
-        Returns
-        -------
-        Region
-            Region representing the complement half-space.
-        """
         return Region.make_halfspace(self, -1)
 
     # ==================================================================================
@@ -1125,77 +732,9 @@ def __neg__(self):
     # ==================================================================================
 
     def move(self, velocities, durations):
-        """
-        Define piecewise-constant motion for the surface.
-
-        Appends a final static segment (zero velocity, infinite duration) so that
-        the motion covers the whole simulation time.
-
-        Parameters
-        ----------
-        velocities : array_like, shape (N, 3) or list
-            Per-segment velocity vectors [cm/s].
-        durations : array_like, shape (N,) or list
-            Per-segment durations [s].
-
-        Notes
-        -----
-        - Internally converts lists to arrays and constructs
-          ``move_time_grid`` and cumulative ``move_translations``.
-        - Sets ``moving=True`` and ``N_move = len(durations) + 1``.
-
-        Examples
-        --------
-        >>> s = Surface.PlaneZ(z=0.0)
-        >>> s.move(velocities=[[0,0,1.0]], durations=[0.5])  # 0.5 s upward, then static
-        >>> s.N_move
-        2
-        """
         move_object(self, velocities, durations)
 
 
-# ======================================================================================
-# Type decoder
-# ======================================================================================
-
-
-def decode_type(type_):
-    if type_ == SURFACE_PLANE_X:
-        return "Plane-X surface"
-    elif type_ == SURFACE_PLANE_Y:
-        return "Plane-Y surface"
-    elif type_ == SURFACE_PLANE_Z:
-        return "Plane-Z surface"
-    elif type_ == SURFACE_PLANE:
-        return "Plane surface"
-    elif type_ == SURFACE_CYLINDER_X:
-        return "Infinite cylinder-X surface"
-    elif type_ == SURFACE_CYLINDER_Y:
-        return "Infinite cylinder-Y surface"
-    elif type_ == SURFACE_CYLINDER_Z:
-        return "Infinite cylinder-Z surface"
-    elif type_ == SURFACE_CYLINDER:
-        return "General cylinder surface"
-    elif type_ == SURFACE_SPHERE:
-        return "Sphere surface"
-    elif type_ == SURFACE_CONE_X:
-        return "Infinite cone-X surface"
-    elif type_ == SURFACE_CONE_Y:
-        return "Infinite cone-Y surface"
-    elif type_ == SURFACE_CONE_Z:
-        return "Infinite cone-Z surface"
-    elif type_ == SURFACE_QUADRIC:
-        return "Quadric surface"
-    elif type_ == SURFACE_TORUS_X:
-        return "Torus-X surface"
-    elif type_ == SURFACE_TORUS_Y:
-        return "Torus-Y surface"
-    elif type_ == SURFACE_TORUS_Z:
-        return "Torus-Z surface"
-    elif type_ == SURFACE_TORUS:
-        return "General torus surface"
-
-
 def decode_BC_type(type_):
     if type_ == BC_NONE:
         return "None"
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 7c1d4bc99..f41def64c 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -18,8 +18,6 @@
 
 ####
 
-import mcdc.object_.mesh as mesh_module
-
 from mcdc.constant import (
     INF,
     MESH_STRUCTURED,
@@ -48,9 +46,6 @@
 
 
 class Tally(MCDCPolymorphic):
-    # Annotations for Numba mode
-    label: str = "tally"
-
     # Basic properties
     name: str
     scores: list[int]
@@ -150,6 +145,7 @@ def __init__(
         time: Sequence[float] | NoneType = None,
         spatial_shape: tuple[int, ...] | NoneType = None,
     ):
+
         # Set name
         if name == "":
             self.name = "(Unnamed tally)"
@@ -196,12 +192,13 @@ def __init__(
             self.azi = np.array(azi)
             self.filter_direction = True
         if polar_reference is not None:
-            polar_reference = np.array(polar_reference)
-            self.polar_reference /= polar_reference / np.linalg.norm(polar_reference)
+            polar_reference_arr = np.array(polar_reference)
+            self.polar_reference /= polar_reference_arr / np.linalg.norm(
+                polar_reference_arr
+            )
         if energy is not None:
             if type(energy) == str and energy == "all_groups":
-                G = simulation.materials[0].G
-                self.energy = np.linspace(0, G, G + 1) - 0.5
+                self.energy = np.array([0])  # A placeholder
             else:
                 self.energy = np.array(energy)
             self.filter_energy = True
@@ -224,7 +221,7 @@ def __init__(
         # Set bins and strides
         self._set_bin_shape_and_strides(shape)
 
-    def _set_bin_shape_and_strides(self, shape):
+    def _set_bin_shape_and_strides(self, shape: tuple):
         # Set bins
         self.bin_shape = list(shape)
 
@@ -234,7 +231,7 @@ def _set_bin_shape_and_strides(self, shape):
         self.stride_azi = reduce(operator.mul, shape[2:])
         self.stride_mu = reduce(operator.mul, shape[1:])
 
-    def _use_census_based_tally(self, frequency):
+    def _use_census_based_tally(self, frequency: int, simulation):
         first_census = simulation.settings.census_time[0]
         self.time = np.linspace(0.0, first_census, frequency + 1)
 
@@ -256,13 +253,18 @@ def _use_census_based_tally(self, frequency):
 
     def _phasespace_filter_text(self):
         text = ""
-        text += f"  - Scores: {[decode_score_type(x) for x in self.scores]}\n"
+        text += (
+            f"  - Scores: {", ".join([decode_score_type(x) for x in self.scores])}\n"
+        )
         if self.filter_time or self.filter_energy or self.filter_direction:
             text += f"  - Phase-space filters\n"
         if self.filter_time:
             text += f"    - Time {print_1d_array(self.time)} s\n"
         if self.filter_energy:
-            text += f"    - Energy {print_1d_array(self.energy)} eV\n"
+            if len(self.energy) == 1:
+                text += f"    - Energy: All groups\n"
+            else:
+                text += f"    - Energy {print_1d_array(self.energy)} eV\n"
         if self.filter_direction:
             text += f"    - Direction\n"
             text += f"    -   Polar reference: {self.polar_reference}\n"
@@ -270,22 +272,25 @@ def _phasespace_filter_text(self):
             text += f"    -   Azimuthal angle {print_1d_array(self.azi)}\n"
         return text
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        # Already compiled?
+        if not super()._compile_into_simulation(simulation):
+            return False
+
+        # Set "all_group" energy filter
+        if len(self.energy) == 1:
+            G = simulation.materials[0].G
+            self.energy = np.linspace(0, G, G + 1) - 0.5
+
+        return True
+
     def __repr__(self):
-        text = "\n"
-        text += f"{decode_type(self.type)}\n"
+        text = super().__repr__()
+
         text += f"  - Name: {self.name}\n"
         return text
 
 
-def decode_type(type_):
-    if type_ == TALLY_TRACKLENGTH:
-        return "Tracklength tally"
-    elif type_ == TALLY_SURFACE_CROSSING:
-        return "Surface crossing tally"
-    elif type_ == TALLY_COLLISION:
-        return "Collision tally"
-
-
 def decode_score_type(type_, lower_case=False):
     if type_ == SCORE_FLUX:
         return "Flux" if not lower_case else "flux"
@@ -305,6 +310,9 @@ def decode_score_type(type_, lower_case=False):
         return "Current out" if not lower_case else "current-out"
     elif type_ == SCORE_ENERGY_DEPOSITION:
         return "Energy deposition" if not lower_case else "energy_deposition"
+    else:
+        print_error(f"Unknown tally score code: {type_}")
+        return "Unknown score"
 
 
 # ======================================================================================
@@ -313,11 +321,11 @@ def decode_score_type(type_, lower_case=False):
 
 
 class TallySurfaceCrossing(Tally):
-    # Spatial filters
-    surface: Surface | NoneType
+    surface: Surface | NoneType  # Non-numba
     surface_filtered: bool
     surface_filter_ID: int
-    cell: Cell | NoneType
+
+    cell: Cell | NoneType  # Non-numba
     cell_filtered: bool
     cell_filter_ID: int
 
@@ -333,12 +341,14 @@ def __init__(
         energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
+        # MC/DC framework metadata
         super(Tally, self).__init__(
             label="tally",
             child_label="surface_crossing_tally",
             child_type=TALLY_SURFACE_CROSSING,
             non_numba=["surface", "cell"],
         )
+
         super().__init__(
             name,
             scores,
@@ -380,8 +390,16 @@ def __init__(
                 for boundary_surface in cell.surfaces:
                     boundary_surface.tallies.append(self)
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        # Already compiled?
+        if not super()._compile_into_simulation(simulation):
+            return False
+
+        return True
+
     def __repr__(self):
         text = super().__repr__()
+
         if isinstance(self.surface, Surface):
             text += f"  - Surface filter: {self.surface.name}\n"
         if isinstance(self.cell, Cell):
@@ -427,6 +445,7 @@ def __init__(
         if mesh is not None:
             spatial_shape = (mesh.Nx, mesh.Ny, mesh.Nz)
 
+        # MC/DC framework metadata
         super(Tally, self).__init__(
             label="tally",
             child_label="collision_tally",
@@ -487,17 +506,24 @@ def __init__(
             self.mesh_stride_y = N_score * mesh.Nz
             self.mesh_stride_x = N_score * mesh.Nz * mesh.Ny
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        # Already compiled?
+        if not super()._compile_into_simulation(simulation):
+            return False
+
         # Attach to all cells if cell filter is not specified
-        if cell is None:
-            for cell_ in simulation.cells:
-                cell_.collision_tallies.append(self)
+        if not self.cell:
+            for cell in simulation.cells:
+                cell.collision_tallies.append(self)
+
+        return True
 
     def __repr__(self):
         text = super().__repr__()
-        if isinstance(self.cell, Cell):
+        if self.cell:
             text += f"  - Cell filter: {self.cell.name}\n"
-        if isinstance(self.mesh, MeshBase):
-            text += f"  - Mesh: {mesh_module.decode_type(self.mesh.type)}\n"
+        if self.mesh:
+            text += f"  - Mesh: {self.mesh.name}\n"
         text += super()._phasespace_filter_text()
         text += f"  - Bin shape [mu, azi, energy, time, score]: {self.bin_shape} \n"
         return text
@@ -539,6 +565,7 @@ def __init__(
         if mesh is not None:
             spatial_shape = (mesh.Nx, mesh.Ny, mesh.Nz)
 
+        # MC/DC framework metadata
         super(Tally, self).__init__(
             label="tally",
             child_label="tracklength_tally",
@@ -599,22 +626,25 @@ def __init__(
             self.mesh_stride_y = N_score * mesh.Nz
             self.mesh_stride_x = N_score * mesh.Nz * mesh.Ny
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        # Already compiled?
+        if not super()._compile_into_simulation(simulation):
+            return False
+
         # Attach to all cells if cell filter is not specified
-        # TODO
-        """
-        if cell is None:
-            for cell_ in simulation.cells:
-                cell_.tracklength_tallies.append(self)
-        """
+        if not self.cell:
+            for cell in simulation.cells:
+                cell.collision_tallies.append(self)
 
-    def __repr__(self):
-        from mcdc.object_.cell import Cell
+        return True
 
+    def __repr__(self):
         text = super().__repr__()
-        if isinstance(self.cell, Cell):
+
+        if self.cell:
             text += f"  - Cell filter: {self.cell.name}\n"
-        if isinstance(self.mesh, MeshBase):
-            text += f"  - Mesh: {mesh_module.decode_type(self.mesh.type)}\n"
+        if self.mesh:
+            text += f"  - Mesh: {self.mesh.name}\n"
         text += super()._phasespace_filter_text()
         text += f"  - Bin shape [mu, azi, energy, time, score]: {self.bin_shape} \n"
         return text
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index e1b9556dd..2bd1e39bb 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -24,53 +24,32 @@
 
 
 class Universe(MCDCObject):
-    """
-    Define a list of cells as a universe.
-
-    Parameters
-    ----------
-    name : str, optional
-        User label.
-    cells : list of Cell
-        List of cells that comprise the universe.
-    root : bool, optional
-        Flag to set as the root universe (ID = 0).
-
-    Returns
-    -------
-    Universe
-        The universe object.
-
-    See Also
-    --------
-    mcdc.Cell : Creates a cell that can be used to define a universe.
-    """
-
-    # Annotations for Numba mode
     name: str
     cells: list[Cell]
 
     def __init__(self, name: str = "", cells: list[Cell] = []):
-        # Custom treatment for root universe
-        super().__init__(label="universe", non_numba=[])
-
-        # Set name
-        if name == "":
-            self.name = "(Unnamed universe)"
-        else:
-            self.name = name
+        # MC/DC framework metadata
+        super().__init__("universe", [])
 
+        self.name = name or "(Unnamed universe)"
         self.cells = cells
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        # Already compiled?
+        if not super()._compile_into_simulation(simulation):
+            return False
+
+        # Compile cells
+        for cell in self.cells:
+            cell._compile_into_simulation(simulation)
+
+        return True
+
     def __repr__(self):
-        text = "\n"
-        text += f"Universe\n"
-        if self.ID == 0:
-            text += f"  - ID: {self.ID} (root)\n"
-        else:
-            text += f"  - ID: {self.ID}\n"
+        text = super().__repr__()
+
         text += f"  - Name: {self.name}\n"
-        text += f"Cells: {[x.ID for x in self.cells]}"
+        text += f"  - Cells: {", ".join([x.name for x in self.cells])}\n"
         return text
 
 
@@ -80,45 +59,21 @@ def __repr__(self):
 
 
 class Lattice(MCDCObject):
-    """
-    Define a regular lattice of universes.
-
-    Parameters
-    ----------
-    name : str, optional
-        User label.
-    x : tuple of (float, float, int), optional
-        Lattice specification along x: ``(x0, dx, Nx)``.
-    y : tuple of (float, float, int), optional
-        Lattice specification along y: ``(y0, dy, Ny)``.
-    z : tuple of (float, float, int), optional
-        Lattice specification along z: ``(z0, dz, Nz)``.
-    universes : list of Universe
-        Array of universes filling each lattice cell.
-
-    Returns
-    -------
-    Lattice
-        The lattice object.
-
-    See Also
-    --------
-    mcdc.Universe : Creates a universe to place in a lattice.
-    """
-
-    # Annotations for Numba mode
-    label: str = "lattice"
-    #
     name: str
+
     x0: float
     dx: float
     Nx: int
+
     y0: float
     dy: float
     Ny: int
+
     z0: float
     dz: float
     Nz: int
+
+    universes: list[Universe]  # Non-numba
     universe_IDs: Annotated[NDArray[int64], ("Nx", "Ny", "Nz")]
 
     def __init__(
@@ -127,15 +82,12 @@ def __init__(
         x: tuple[float, float, int] | NoneType = None,
         y: tuple[float, float, int] | NoneType = None,
         z: tuple[float, float, int] | NoneType = None,
-        universes: list[Universe] = None,
+        universes: list[Universe] = [],
     ):
-        super().__init__()
+        super().__init__("lattice", ["universes"])
 
-        # Set name
-        if name == "":
-            self.name = "(Unnamed lattice)"
-        else:
-            self.name = name
+        self.name = name or "(Unnamed lattice)"
+        self.universes = universes
 
         # Default uniform grids
         self.x0 = -INF
@@ -185,12 +137,11 @@ def __init__(
         self.universe_IDs = np.array(universe_IDs)
 
     def __repr__(self):
-        text = "\n"
-        text += f"Lattice\n"
-        text += f"  - ID: {self.ID}\n"
+        text = super().__repr__()
+
         text += f"  - Name: {self.name}\n"
         text += f"  - (x0, dx, Nx): ({self.x0}, {self.dx}, {self.Nx})\n"
         text += f"  - (y0, dy, Ny): ({self.y0}, {self.dy}, {self.Ny})\n"
         text += f"  - (z0, dz, Nz): ({self.z0}, {self.dz}, {self.Nz})\n"
-        text += f"Universes: {set([x.ID for x in list(flatten(self.universes))])}"
+        text += f"Universes: {set([x.name for x in list(flatten(self.universes))])}"
         return text

From 0e18649892b66acddbe3d0d51f6d17bf702ff8b8 Mon Sep 17 00:00:00 2001
From: Massimo Larsen <larsemas@oregonstate.edu>
Date: Wed, 1 Jul 2026 09:46:24 -0700
Subject: [PATCH 020/202] Moved regression tests to pytest

---
 .github/workflows/docker.yml              |  10 +-
 .github/workflows/regression_test-gpu.yml |   3 +-
 .github/workflows/regression_test.yml     |  11 +-
 CHANGELOG.md                              |   2 +
 docs/source/contribution_guide/index.rst  |  21 +-
 pyproject.toml                            |  17 ++
 test/conftest.py                          |  35 +++
 test/regression/README.md                 |  33 ---
 test/regression/conftest.py               | 221 ++++++++++++++++++
 test/regression/run.py                    | 259 ----------------------
 test/regression/test_regression.py        |   2 +
 test/unit/conftest.py                     |   9 -
 12 files changed, 304 insertions(+), 319 deletions(-)
 create mode 100644 test/conftest.py
 delete mode 100644 test/regression/README.md
 create mode 100644 test/regression/conftest.py
 delete mode 100644 test/regression/run.py
 create mode 100644 test/regression/test_regression.py

diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml
index d6ec36f4d..04a2e952c 100644
--- a/.github/workflows/docker.yml
+++ b/.github/workflows/docker.yml
@@ -145,18 +145,18 @@ jobs:
       matrix:
         include:
           - mode: Python-Serial
-            run_cmd: "python run.py"
+            run_cmd: "python -m pytest test/regression"
             timeout: 10
           - mode: Python-MPI
             run_cmd: |
-              python run.py --mpiexec=2
+              python -m pytest test/regression --mpiexec=2
             timeout: 20
           - mode: Numba-Serial
-            run_cmd: "python run.py --mode numba"
+            run_cmd: "python -m pytest test/regression --mode numba"
             timeout: 120
           - mode: Numba-MPI
             run_cmd: |
-              python run.py --mode numba --mpiexec=2
+              python -m pytest test/regression --mode numba --mpiexec=2
             timeout: 120
 
     steps:
@@ -183,7 +183,7 @@ jobs:
         run: |
           docker run --rm \
             -v ${{ github.workspace }}:/opt/mcdc \
-            -w /opt/mcdc/test/regression \
+            -w /opt/mcdc \
             mcdc:${{ needs.build.outputs.image_tag }} bash -lc '
               git config --global --add safe.directory /opt/mcdc
               git config --global --add safe.directory /opt/mcdc/test/regression/mcdc-regression_test_data
diff --git a/.github/workflows/regression_test-gpu.yml b/.github/workflows/regression_test-gpu.yml
index caab59018..4ffa831bf 100644
--- a/.github/workflows/regression_test-gpu.yml
+++ b/.github/workflows/regression_test-gpu.yml
@@ -35,5 +35,4 @@ jobs:
       run: |
           pwd
           source ../ci_testing/bin/activate
-          cd test/regression
-          python run.py --mode=numba --target=gpu
+          python -m pytest test/regression --mode=numba --target=gpu
diff --git a/.github/workflows/regression_test.yml b/.github/workflows/regression_test.yml
index c34b5657a..06d5232db 100644
--- a/.github/workflows/regression_test.yml
+++ b/.github/workflows/regression_test.yml
@@ -34,24 +34,22 @@ jobs:
           # Python modes:
           - mode: Python-Serial
             python-version: '3.13'
-            run_cmd: "python run.py"
+            run_cmd: "python -m pytest test/regression"
             timeout: 10
           - mode: Python-MPI
             python-version: '3.13'
             run_cmd: |
-              python run.py --mpiexec=4
-              python run.py --mpiexec=16 --name=slab_reed_dd_3d
+              python -m pytest test/regression --mpiexec=4
             timeout: 30
           # Numba modes:
           - mode: Numba-Serial
             python-version: '3.13'
-            run_cmd: "python run.py --mode numba"
+            run_cmd: "python -m pytest test/regression --mode numba"
             timeout: 120
           - mode: Numba-MPI
             python-version: '3.13'
             run_cmd: |
-              python run.py --mode numba --mpiexec=4
-              python run.py --mode numba --mpiexec=16 --name=slab_reed_dd_3d
+              python -m pytest test/regression --mode numba --mpiexec=4
             timeout: 120
 
     steps:
@@ -79,5 +77,4 @@ jobs:
           python -c "import mpi4py; print(f'mpi4py {mpi4py.__version__} from {mpi4py.__file__}')"
 
       - name: Run regression tests (${{ matrix.mode }})
-        working-directory: test/regression
         run: ${{ matrix.run_cmd }}
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 4ba30aee5..1515c1663 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -10,6 +10,8 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/2.0.0/),
 
 ### Changed
 
+- Move regression tests from the custom `run.py` harness to pytest-based collection and reporting from [@massimolarsen]
+
 ### Deprecated
 
 ### Removed
diff --git a/docs/source/contribution_guide/index.rst b/docs/source/contribution_guide/index.rst
index 00c6b7c2a..7597598c4 100644
--- a/docs/source/contribution_guide/index.rst
+++ b/docs/source/contribution_guide/index.rst
@@ -141,19 +141,33 @@ Our github based CI runs for,
 
 while we do not have continuous integration we have validated MC/DC on other systems.
 
-To run the regression tests locally, navigate to ``MCDC/test/regression`` and run,
+To run the default fast unit-test suite locally, run,
 
 .. code-block:: sh
 
+    python -m pytest
 
-    python run.py <OPTION_FLAG(s)>
+To run the full unit-test suite in both Python and Numba mode, run,
+
+.. code-block:: sh
+
+    python -m pytest test/unit
+
+To run the regression tests locally, run,
+
+.. code-block:: sh
+
+    python -m pytest test/regression <OPTION_FLAG(s)>
 
 
 and all the tests will run. Various option ``OPTION_FLAG`` are accepted to control the tests ran,
 
-* Run a specific test (with wildcard ``*`` support): ``--name=<test_name>`` 
+* Run a specific test (with wildcard ``*`` support): ``--name=<test_name>``
+* Skip a specific test (with wildcard ``*`` support): ``--skip=<test_name>``
 * Run in Numba mode: ``--mode=numba``
+* Run against the GPU target: ``--target=gpu``
 * Run in multiple MPI ranks (currently support ``mpiexec`` and ``srun``): ``--mpiexec=<number of ranks>``
+* Run with Slurm ``srun`` instead of ``mpiexec``: ``--srun=<number of ranks>``
 
 Note that flags can be combined. To add a new test:
 
@@ -170,7 +184,6 @@ See the (``.github/workflows``) for examples.
 If a new simulation type is added (e.g. quasi montecarlo w/ davidson's method, residual monte carlo, intrusive uq) more regression tests should be added with your PR.
 If you are wondering accommodations.
 
-
 --------------------
 Adding Documentation
 --------------------
diff --git a/pyproject.toml b/pyproject.toml
index 0ad749218..6fe3b703a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -108,3 +108,20 @@ force-exclude = '''
   | mcdc/mcdc_set/
 )
 '''
+
+[tool.pytest.ini_options]
+testpaths = ["test/unit"]
+# The slow suite is selected by path (`pytest test/regression`); keep the cloned
+# regression data out of pytest's collection without replacing pytest's defaults.
+norecursedirs = [
+  "*.egg",
+  ".*",
+  "_darcs",
+  "build",
+  "CVS",
+  "dist",
+  "node_modules",
+  "venv",
+  "{arch}",
+  "mcdc-regression_test_data",
+]
diff --git a/test/conftest.py b/test/conftest.py
new file mode 100644
index 000000000..d3a634aab
--- /dev/null
+++ b/test/conftest.py
@@ -0,0 +1,35 @@
+def pytest_addoption(parser):
+    parser.addoption(
+        "--mode",
+        choices=["python", "numba"],
+        default="python",
+        help="MCDC execution mode.",
+    )
+    parser.addoption(
+        "--target",
+        choices=["cpu", "gpu"],
+        default="cpu",
+        help="MCDC regression target.",
+    )
+    parser.addoption(
+        "--mpiexec",
+        type=int,
+        default=0,
+        help="Run regression cases with mpiexec and the given number of ranks.",
+    )
+    parser.addoption(
+        "--srun",
+        type=int,
+        default=0,
+        help="Run regression cases with srun and the given number of ranks.",
+    )
+    parser.addoption(
+        "--name",
+        default="ALL",
+        help="Regression case name pattern to run.",
+    )
+    parser.addoption(
+        "--skip",
+        default="NONE",
+        help="Regression case name pattern to skip.",
+    )
diff --git a/test/regression/README.md b/test/regression/README.md
deleted file mode 100644
index b9f5e4436..000000000
--- a/test/regression/README.md
+++ /dev/null
@@ -1,33 +0,0 @@
-# MC/DC - Regression Test
-
-To run all tests:
-
-```bash
-python run.py
-```
-
-To run a specific test (with wildcard `*` support):
-
-```bash
-python run.py --name=<test_name>
-```
-
-To run in Numba mode:
-
-```bash
-python run.py --mode=numba
-```
-
-To run in multiple MPI ranks (currently support `mpiexec` and `srun`):
-
-```bash
-python run.py --mpiexec=<number of ranks>
-```
-
-To add a new test:
-
-1. Create a folder. The name of the folder will be the test name.
-2. Add the input file named `input.py`.
-3. Add the answer key file named `answer.h5`.
-4. Make sure that the number of particles run is large enough for a good test.
-5. If the test runs longer than 10 seconds in serial Python mode, consider decreasing the number of particles.
diff --git a/test/regression/conftest.py b/test/regression/conftest.py
new file mode 100644
index 000000000..707d0f4ca
--- /dev/null
+++ b/test/regression/conftest.py
@@ -0,0 +1,221 @@
+import fnmatch
+import subprocess
+import sys
+import warnings
+from pathlib import Path
+
+import h5py
+import numpy as np
+import pytest
+
+REGRESSION_DIR = Path(__file__).parent
+REGRESSION_DATA_NAME = "mcdc-regression_test_data"
+RELATIVE_TOLERANCE = 1e-6
+ABSOLUTE_TOLERANCE = 1e-14
+NON_TEST_DIRS = {"__pycache__", REGRESSION_DATA_NAME}
+
+
+def regression_cases():
+    return sorted(
+        path
+        for path in REGRESSION_DIR.iterdir()
+        if path.is_dir() and path.name not in NON_TEST_DIRS
+    )
+
+
+def selected_cases(config):
+    name_pattern = config.getoption("--name")
+    skip_pattern = config.getoption("--skip")
+    target = config.getoption("--target")
+
+    cases = []
+    for case in regression_cases():
+        if name_pattern != "ALL" and not fnmatch.fnmatch(case.name, name_pattern):
+            continue
+        if skip_pattern != "NONE" and fnmatch.fnmatch(case.name, skip_pattern):
+            continue
+        if target == "gpu" and ("iqmc" in case.name or "eigenvalue" in case.name):
+            continue
+        cases.append(case)
+    return cases
+
+
+def pytest_configure(config):
+    name_pattern = config.getoption("--name")
+    if name_pattern == "ALL":
+        return
+    if not any(fnmatch.fnmatch(case.name, name_pattern) for case in regression_cases()):
+        raise pytest.UsageError(
+            f"--name={name_pattern} did not match any regression case"
+        )
+
+
+def pytest_generate_tests(metafunc):
+    if "case_path" in metafunc.fixturenames:
+        cases = selected_cases(metafunc.config)
+        metafunc.parametrize("case_path", cases, ids=[case.name for case in cases])
+
+
+@pytest.fixture(scope="session")
+def regression_data():
+    data_path = REGRESSION_DIR / REGRESSION_DATA_NAME
+    if data_path.is_dir():
+        result = subprocess.run(
+            ["git", "pull"],
+            cwd=data_path,
+            capture_output=True,
+            text=True,
+        )
+        # An out-of-date clone is still usable (e.g. when running offline), so warn
+        # rather than skip.
+        if result.returncode != 0:
+            warnings.warn(
+                "Could not update regression data repository.\n"
+                + format_subprocess_output(result.stdout, result.stderr)
+            )
+        return data_path
+
+    result = subprocess.run(
+        ["git", "clone", f"https://github.com/mcdc-project/{REGRESSION_DATA_NAME}.git"],
+        cwd=REGRESSION_DIR,
+        capture_output=True,
+        text=True,
+    )
+    if result.returncode != 0:
+        pytest.skip(
+            "Could not clone regression data repository.\n"
+            + format_subprocess_output(result.stdout, result.stderr)
+        )
+    return data_path
+
+
+@pytest.fixture
+def run_regression_case(pytestconfig, regression_data):
+    def run(case_path):
+        run_case(pytestconfig, case_path)
+
+    return run
+
+
+def run_case(config, case_path):
+    input_path = case_path / "input.py"
+    answer_path = case_path / "answer.h5"
+    output_path = case_path / "output.h5"
+
+    if not input_path.exists():
+        pytest.fail("input.py is missing")
+    if not answer_path.exists():
+        pytest.fail("answer.h5 is missing")
+
+    if output_path.exists():
+        output_path.unlink()
+
+    result = subprocess.run(
+        build_command(config),
+        cwd=case_path,
+        capture_output=True,
+        text=True,
+    )
+    if result.returncode != 0:
+        pytest.fail(
+            f"Run failed with return code {result.returncode}.\n"
+            + format_subprocess_output(result.stdout, result.stderr)
+        )
+
+    if not output_path.exists():
+        pytest.fail(
+            "Run did not produce output.h5.\n"
+            + format_subprocess_output(result.stdout, result.stderr)
+        )
+
+    compare_outputs(output_path, answer_path, config.getoption("--target"))
+
+
+def build_command(config):
+    mode = config.getoption("--mode")
+    target = config.getoption("--target")
+    mpiexec = config.getoption("--mpiexec")
+    srun = config.getoption("--srun")
+    command = [
+        sys.executable,
+        "input.py",
+        f"--mode={mode}",
+        f"--target={target}",
+        "--output=output",
+        "--no-progress-bar",
+    ]
+
+    if mpiexec > 1:
+        prefix = ["mpiexec", "-n", str(mpiexec)]
+        if target == "gpu":
+            prefix.append("--gpus-per-task=1")
+        return [*prefix, *command]
+
+    if srun > 1:
+        prefix = ["srun", "-n", str(srun)]
+        if target == "gpu":
+            prefix.append("--gpus-per-task=1")
+        return [*prefix, *command]
+
+    return command
+
+
+def compare_outputs(output_path, answer_path, target):
+    errors = []
+    with h5py.File(output_path, "r") as output, h5py.File(answer_path, "r") as answer:
+        if "iqmc" in output.keys():
+            compare_iqmc(output, answer, errors)
+        else:
+            compare_tallies(output, answer, target, errors)
+            compare_k_results(output, answer, errors)
+
+    if errors:
+        pytest.fail("\n\n".join(errors))
+
+
+def compare_tallies(output, answer, target, errors):
+    name_root = "tallies"
+    for tally in answer[name_root].keys():
+        name_tally = f"{name_root}/{tally}"
+        for score in answer[name_tally].keys():
+            if score == "grid":
+                continue
+            name_score = f"{name_tally}/{score}"
+            for result in answer[name_score].keys():
+                if "uq_var" in result and target == "gpu":
+                    continue
+                name = f"{name_score}/{result}"
+                assert_allclose(output[name][()], answer[name][()], name, errors)
+
+
+def compare_k_results(output, answer, errors):
+    for name in ["k_mean", "k_sdev", "k_cycle", "k_eff"]:
+        if name in output.keys():
+            assert_allclose(output[name][()], answer[name][()], name, errors)
+
+
+def compare_iqmc(output, answer, errors):
+    for score in output["iqmc/tally/"].keys():
+        name = f"iqmc/tally/{score}/mean"
+        assert_allclose(
+            np.squeeze(output[name][()]),
+            np.squeeze(answer[name][()]),
+            name,
+            errors,
+        )
+
+
+def assert_allclose(actual, expected, name, errors):
+    try:
+        np.testing.assert_allclose(
+            actual,
+            expected,
+            rtol=RELATIVE_TOLERANCE,
+            atol=ABSOLUTE_TOLERANCE,
+        )
+    except AssertionError as error:
+        errors.append(f"Differences in {name}\n{error}")
+
+
+def format_subprocess_output(stdout, stderr):
+    return f"stdout:\n{stdout}\n\nstderr:\n{stderr}"
diff --git a/test/regression/run.py b/test/regression/run.py
deleted file mode 100644
index 9602c11d6..000000000
--- a/test/regression/run.py
+++ /dev/null
@@ -1,259 +0,0 @@
-import h5py, os, sys, argparse, fnmatch
-import numpy as np
-from colorama import Fore, Style
-
-RELATIVE_TOLERANCE = 1e-6
-
-# Option parser
-parser = argparse.ArgumentParser(description="MC/DC regression test")
-parser.add_argument("--mode", type=str, choices=["python", "numba"], default="python")
-parser.add_argument("--target", type=str, choices=["cpu", "gpu"], default="cpu")
-parser.add_argument("--mpiexec", type=int, default=0)
-parser.add_argument("--srun", type=int, default=0)
-parser.add_argument("--name", type=str, default="ALL")
-parser.add_argument("--skip", type=str, default="NONE")
-args, unargs = parser.parse_known_args()
-
-# Parse
-mode = args.mode
-target = args.target
-mpiexec = args.mpiexec
-srun = args.srun
-name = args.name
-skip = args.skip
-
-regtest_data_name = "mcdc-regression_test_data"
-non_test_files = ["__pycache__", regtest_data_name, "tmp"]
-
-# Clone and update regression test data if needed
-if not os.path.isdir(regtest_data_name):
-    os.system(f"git clone https://github.com/mcdc-project/{regtest_data_name}.git")
-else:
-    os.chdir(regtest_data_name)
-    os.system("git pull")
-    os.chdir("..")
-
-# Get test names
-if name == "ALL":
-    names = []
-    for item in os.listdir():
-        if os.path.isdir(item) and item not in non_test_files:
-            names.append(item)
-else:
-    names = [item for item in os.listdir() if fnmatch.fnmatch(item, name)]
-names.sort()
-
-# Remove skipped if specified
-if skip != "NONE":
-    skips = [item for item in os.listdir() if fnmatch.fnmatch(item, skip)]
-    for name in skips:
-        print(Fore.YELLOW + "Note: Skipping %s" % name + Style.RESET_ALL)
-        names.remove(name)
-
-# Skip domain decomp tests unless there are 4 MPI processes
-temp = names.copy()
-parallel_run = mpiexec > 0 or srun > 0
-for name in names:
-    if name == "slab_reed_dd" and (
-        not parallel_run or not (mpiexec % 4 == 0 and srun % 4 == 0)
-    ):
-        temp.remove(name)
-        print(
-            Fore.YELLOW
-            + "Note: Skipping %s (require multiple of 4 MPI ranks)" % name
-            + Style.RESET_ALL
-        )
-    elif name == "slab_reed_dd_3d" and (
-        not parallel_run or not (mpiexec % 16 == 0 and srun % 16 == 0)
-    ):
-        temp.remove(name)
-        print(
-            Fore.YELLOW
-            + "Note: Skipping %s (require multiple of 16 MPI ranks)" % name
-            + Style.RESET_ALL
-        )
-
-names = temp
-
-# Skip iqmc if GPU run
-if target == "gpu":
-    temp = names.copy()
-    for name in names:
-        if ("iqmc" in name) or ("eigenvalue" in name):
-            temp.remove(name)
-            print(
-                Fore.YELLOW + "Note: Skipping %s (GPU target)" % name + Style.RESET_ALL
-            )
-names = temp
-
-# Data for each test
-printouts = []
-runtimes = []
-flags = []
-error_msgs = []
-crashes = []
-all_pass = True
-
-# Run all tests
-for i, name in enumerate(names):
-    print("\n[%i/%i] " % (i + 1, len(names)) + name)
-    error_msgs.append([])
-    crashes.append(False)
-    runtimes.append([0])
-
-    # Change directory
-    os.chdir(name)
-
-    # Check test setup
-    if not os.path.exists("input.py"):
-        print(Fore.RED + "  input.py is missing\n" + Style.RESET_ALL)
-        sys.exit()
-    if not os.path.exists("answer.h5"):
-        print(Fore.RED + "  answer.h5 is missing\n" + Style.RESET_ALL)
-        sys.exit()
-
-    # Delete output if exists
-    if os.path.exists("output.h5"):
-        os.remove("output.h5")
-
-    # Run the test problem (redirect the stdout)
-    if mpiexec > 1:
-        gpus_per_task = ""
-        if target == "gpu":
-            gpus_per_task = f"--gpus-per-task=1 "
-        os.system(
-            "mpiexec -n %i %s python input.py --mode=%s --target=%s --output=output --no-progress-bar> tmp 2>&1"
-            % (mpiexec, gpus_per_task, mode, target)
-        )
-    elif srun > 1:
-        gpus_per_task = ""
-        if target == "gpu":
-            gpus_per_task = f"--gpus-per-task=1 "
-        os.system(
-            "srun -n %i %s python input.py --mode=%s --target=%s --output=output --no-progress-bar> tmp 2>&1"
-            % (srun, gpus_per_task, mode, target)
-        )
-    else:
-        os.system(
-            "python input.py --mode=%s --target=%s --output=output --no-progress-bar > tmp 2>&1"
-            % (mode, target)
-        )
-    with open("tmp") as f:
-        printouts.append(f.read())
-    os.remove("tmp")
-
-    # Check if crashed
-    if not os.path.exists("output.h5"):
-        print(Fore.RED + "  Failed: Run crashed" + Style.RESET_ALL)
-        all_pass = False
-        crashes[-1] = True
-        os.chdir("..")
-        continue
-
-    # Get the output and the answer key
-    output = h5py.File("output.h5", "r")
-    answer = h5py.File("answer.h5", "r")
-
-    runtimes[-1] = output["runtime/total"][()]
-    print("  (%.2f seconds)" % runtimes[-1][0])
-
-    # Compare mean, sdev, and uq_var (if available)
-    if "iqmc" not in output.keys():
-        name_root = "tallies"
-        for tally in [key for key in answer[name_root].keys()]:
-            name_tally = name_root + "/" + tally
-            for score in [key for key in answer[name_tally].keys()]:
-                if score in ["grid"]:
-                    continue
-                name_score = name_tally + "/" + score
-                for result in [key for key in answer[name_score].keys()]:
-                    name = name_score + "/" + result
-                    a = output[name][()]
-                    b = answer[name][()]
-
-                    # if (("sdev" in result) or ("uq_var" in result)) and (
-                    if ("uq_var" in result) and (args.target == "gpu"):
-                        continue
-                    # Passed?
-                    try:
-                        np.testing.assert_allclose(a, b, rtol=RELATIVE_TOLERANCE)
-                        print(
-                            Fore.GREEN + "  {}: Passed".format(name) + Style.RESET_ALL
-                        )
-                    except AssertionError as error:
-                        all_pass = False
-                        error_msgs[-1].append(
-                            "Differences in %s"
-                            % (name + "/" + result + "\n" + "{}\n".format(error))
-                        )
-                        print(Fore.RED + "  {}: Failed".format(name) + Style.RESET_ALL)
-
-        # Other quantities
-        for result_name in ["k_mean", "k_sdev", "k_cycle", "k_eff"]:
-            if result_name not in output.keys():
-                continue
-
-            a = output[result_name][()]
-            b = answer[result_name][()]
-
-            # Passed?
-            try:
-                np.testing.assert_allclose(a, b, rtol=RELATIVE_TOLERANCE)
-                print(Fore.GREEN + "  {}: Passed".format(result_name) + Style.RESET_ALL)
-            except AssertionError as error:
-                all_pass = False
-                error_msgs[-1].append(
-                    "Differences in {}\n{}".format(result_name, error)
-                )
-                print(Fore.RED + "  {}: Failed".format(result_name) + Style.RESET_ALL)
-
-    # iQMC flux
-    if "iqmc" in output.keys():
-        for score in [key for key in output["iqmc/tally/"].keys()]:
-            name = f"iqmc/tally/{score}/mean"
-            a = np.squeeze(output[name][()])
-            b = np.squeeze(answer[name][()])
-            # Passed?
-            try:
-                np.testing.assert_allclose(a, b, rtol=RELATIVE_TOLERANCE)
-                print(Fore.GREEN + "  {}: Passed".format(score) + Style.RESET_ALL)
-            except AssertionError as error:
-                all_pass = False
-                error_msgs[-1].append("Differences in {}\n{}".format(score, a - b))
-                print(Fore.RED + "  {}: Failed".format(score) + Style.RESET_ALL)
-
-    # Close files
-    output.close()
-    answer.close()
-
-    # Move back up
-    os.chdir("..")
-
-# Report test results
-N_fails = 0
-for i in range(len(names)):
-    if crashes[i] or len(error_msgs[i]) > 0:
-        N_fails += 1
-
-print(
-    "\nTests passed: "
-    + Fore.GREEN
-    + "%i/%i" % (len(names) - N_fails, len(names))
-    + Style.RESET_ALL
-)
-print("Tests failed: " + Fore.RED + "%i/%i" % (N_fails, len(names)) + Style.RESET_ALL)
-print("  (%.2f seconds)\n" % np.sum(np.array(runtimes)))
-for i in range(len(names)):
-    if crashes[i]:
-        print("\n" + "=" * 80)
-        print("\n## {} crashed:".format(names[i]))
-        print(printouts[i])
-    if len(error_msgs[i]) > 0:
-        print("\n" + "=" * 80)
-        print("\n## {} failed:".format(names[i]))
-        print(printouts[i])
-        print("\n===\n")
-        for msg in error_msgs[i]:
-            print("\n# " + msg + "\n")
-
-assert all_pass
diff --git a/test/regression/test_regression.py b/test/regression/test_regression.py
new file mode 100644
index 000000000..1064fbef4
--- /dev/null
+++ b/test/regression/test_regression.py
@@ -0,0 +1,2 @@
+def test_regression(case_path, run_regression_case):
+    run_regression_case(case_path)
diff --git a/test/unit/conftest.py b/test/unit/conftest.py
index 339f2e7f9..4624d29c6 100644
--- a/test/unit/conftest.py
+++ b/test/unit/conftest.py
@@ -5,15 +5,6 @@
 import pytest
 
 
-def pytest_addoption(parser):
-    parser.addoption(
-        "--mode",
-        choices=["python", "numba"],
-        default="python",
-        help="MCDC execution mode for unit tests.",
-    )
-
-
 @pytest.hookimpl(tryfirst=True)
 def pytest_cmdline_main(config):
     # Outer invocation: `pytest test/unit` should run python+numba automatically.

From f5aef481c9cc35748cbc8bebd7efcad84582dd48 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 21 Jul 2026 10:05:58 +0700
Subject: [PATCH 021/202] update settings

---
 mcdc/code_factory/python_objects_compiler.py |  8 +++++++-
 mcdc/object_/settings.py                     | 10 ++--------
 mcdc/object_/universe.py                     |  1 +
 3 files changed, 10 insertions(+), 9 deletions(-)

diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index 33f5ae759..751e62786 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -1,3 +1,5 @@
+import numpy as np
+
 from mcdc.object_.base import MCDCObject, MCDCPolymorphic
 from mcdc.object_.cell import Region, Cell
 from mcdc.object_.data import DataBase, DataNone
@@ -48,7 +50,11 @@ def compile_simulation(simulation: Simulation):
         tally._compile_into_simulation(simulation)
     print(simulation.tallies)
 
-    # Compile settings
+    # Apply settings as needed
+    settings = simulation.settings
+    if simulation.settings.neutron_eigenvalue_mode:
+        simulation.k_cycle = np.zeros(settings.N_cycle)
+        simulation.gyration_radius = np.zeros(settings.N_cycle)
 
 
 def register_object(object_: MCDCObject, simulation: Simulation) -> bool:
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index d650fc4eb..71d7c6c14 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -70,8 +70,8 @@ class Settings(MCDCBase):
     gpu_storage: int = GPU_STORAGE_SEPARATE
 
     def __post_init__(self):
-        """Initialize settings framework metadata."""
-        super().__init__(label="settings", non_numba=[])
+        # MC/DC framework metadata
+        super().__init__("settings", [])
 
     def set_time_census(self, time, tally_frequency=None):
         # Make sure that the time grid points are sorted
@@ -131,12 +131,6 @@ def set_eigenmode(
             else:
                 print_error("Unknown gyration radius type")
 
-        # Allocate cycle-wise quantities
-        from mcdc.object_.simulation import simulation
-
-        simulation.k_cycle = np.zeros(self.N_cycle)
-        simulation.gyration_radius = np.zeros(self.N_cycle)
-
     def set_source_file(self, source_file_name):
         self.use_source_file = True
         self.source_file_name = source_file_name
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index 2bd1e39bb..464ad2604 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -84,6 +84,7 @@ def __init__(
         z: tuple[float, float, int] | NoneType = None,
         universes: list[Universe] = [],
     ):
+        # MC/DC framework metadata
         super().__init__("lattice", ["universes"])
 
         self.name = name or "(Unnamed lattice)"

From 86dd3f51809cf296457d55df46701dd089391483 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 21 Jul 2026 13:33:15 +0700
Subject: [PATCH 022/202] update objects

---
 mcdc/code_factory/numba_objects_generator.py |  1 -
 mcdc/code_factory/python_objects_compiler.py |  2 --
 mcdc/object_/gpu_tools.py                    |  7 ++---
 mcdc/object_/particle.py                     | 21 +++++++++++----
 mcdc/object_/settings.py                     |  1 -
 mcdc/object_/technique.py                    | 27 +++++++++++---------
 6 files changed, 35 insertions(+), 24 deletions(-)

diff --git a/mcdc/code_factory/numba_objects_generator.py b/mcdc/code_factory/numba_objects_generator.py
index b7fee5bd0..a5ad8efba 100644
--- a/mcdc/code_factory/numba_objects_generator.py
+++ b/mcdc/code_factory/numba_objects_generator.py
@@ -23,7 +23,6 @@
     MCDCBase,
     MCDCObject,
     MCDCPolymorphic,
-    ObjectSingleton,
 )
 from mcdc.object_.particle import Particle, ParticleBank, ParticleData
 from mcdc.object_.tally import Tally
diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index 751e62786..f19c7799e 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -45,10 +45,8 @@ def compile_simulation(simulation: Simulation):
     # Compile tally
     tallies = simulation.tallies
     simulation.tallies = []
-    print(tallies)
     for tally in tallies:
         tally._compile_into_simulation(simulation)
-    print(simulation.tallies)
 
     # Apply settings as needed
     settings = simulation.settings
diff --git a/mcdc/object_/gpu_tools.py b/mcdc/object_/gpu_tools.py
index 6715367ee..6e31ba5b5 100644
--- a/mcdc/object_/gpu_tools.py
+++ b/mcdc/object_/gpu_tools.py
@@ -8,12 +8,13 @@
 
 @dataclass
 class GPUMeta(MCDCBase):
-    # Annotations for Numba mode
-    label: str = "gpu_meta"
-    #
     state_pointer: uintp = uintp(0)
     program_pointer: uintp = uintp(0)
     simulation_pointer: uintp = uintp(0)
     data_pointer: uintp = uintp(0)
 
     # Note that the uintp is manually overriden in code_factory.
+
+    def __init__(self):
+        # MC/DC framework metadata
+        super().__init__("gpu_meta", [])
diff --git a/mcdc/object_/particle.py b/mcdc/object_/particle.py
index 5fd7f3fb9..2d570c456 100644
--- a/mcdc/object_/particle.py
+++ b/mcdc/object_/particle.py
@@ -13,7 +13,6 @@
 
 @dataclass
 class ParticleData(MCDCBase):
-    label: str = "particle_data"
     x: float = 0.0
     y: float = 0.0
     z: float = 0.0
@@ -27,16 +26,22 @@ class ParticleData(MCDCBase):
     particle_type: int = PARTICLE_NEUTRON
     rng_seed: uint64 = uint64(1)
 
+    def __post_init__(self):
+        # MC/DC framework metadata
+        super().__init__("particle_data", [])
+
 
 @dataclass
 class CollisionData(MCDCBase):
-    label: str = "collision_data"
     energy_deposition: float = 0.0
 
+    def __post_init__(self):
+        # MC/DC framework metadata
+        super().__init__("collision_data", [])
+
 
 @dataclass
 class Particle(ParticleData):
-    label: str = "particle"
     cell_ID: int = -1
     material_ID: int = -1
     surface_ID: int = -1
@@ -44,14 +49,20 @@ class Particle(ParticleData):
     fresh: bool = False
     event: int = -1
 
+    def __post_init__(self):
+        # MC/DC framework metadata
+        super(ParticleData, self).__init__("particle", [])
+
 
 class ParticleBank(MCDCBase):
-    particles: list[ParticleData] = []
+    particles: list[ParticleData] = []  # Non-numba
     size: Annotated[NDArray[int64], (1,)]
     tag: str = ""
 
     def __init__(self, tag):
+        # MC/DC framework metadata
         """Initialize particle bank framework metadata."""
-        super().__init__(label="particle_bank", non_numba=["particles"])
+        super().__init__("particle_bank", ["particles"])
+
         self.tag = tag
         self.size = np.zeros(1, dtype=int64)
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index 71d7c6c14..41b3f192e 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -1,6 +1,5 @@
 from typing import List
 import h5py
-from h5py._hl.dataset import sel
 import numpy as np
 
 from dataclasses import dataclass, field
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index a54e60806..8a91ef280 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -13,11 +13,12 @@
 
 
 class ImplicitCapture(MCDCBase):
-    # Annotations for Numba mode
-    label: str = "implicit_capture"
     active: bool
 
     def __init__(self):
+        # MC/DC framework metadata
+        super().__init__("implicit_capture", [])
+
         self.active = False
 
     def __call__(self, active: bool = True):
@@ -30,13 +31,13 @@ def __call__(self, active: bool = True):
 
 
 class WeightedEmission(MCDCBase):
-    # Annotations for Numba mode
-    label: str = "weighted_emission"
-
     active: bool
     weight_target: float
 
     def __init__(self):
+        # MC/DC framework metadata
+        super().__init__("weighted_emission", [])
+
         self.active = False
         self.weight_target = 0.0
 
@@ -51,14 +52,14 @@ def __call__(self, active: bool = True, weight_target: float = 1.0):
 
 
 class GlobalWeightRoulette(MCDCBase):
-    # Annotations for Numba mode
-    label: str = "global_weight_roulette"
-
     active: bool
     weight_threshold: float
     weight_target: float
 
     def __init__(self):
+        # MC/DC framework metadata
+        super().__init__("global_weight_roulette", [])
+
         self.active = False
         self.weight_threshold = 0.0
         self.weight_target = 1.0
@@ -79,8 +80,6 @@ def __call__(self, weight_threshold: float = 0.0, weight_target: float = 1.0):
 
 
 class WeightWindows(MCDCBase):
-    label: str = "weight_windows"
-
     active: bool
 
     # energy
@@ -98,6 +97,9 @@ class WeightWindows(MCDCBase):
     upper_weights: Annotated[NDArray[np.float64], ("Ne", "Nx", "Ny", "Nz")]
 
     def __init__(self):
+        # MC/DC framework metadata
+        super().__init__("weight_windows", [])
+
         self.active = False
         self.energy_bounds = np.array([0.0, 1.0])
         self.Ne = 1
@@ -181,11 +183,12 @@ def __call__(self, weight_windows, mesh=None, energy=None):
 
 
 class PopulationControl(MCDCBase):
-    # Annotations for Numba mode
-    label: str = "population_control"
     active: bool
 
     def __init__(self):
+        # MC/DC framework metadata
+        super().__init__("population_control", [])
+
         self.active = False
 
     def __call__(self, active: bool = True):

From f1a766020ab72859df078ba788e1cf3b4836c2fb Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 22 Jul 2026 10:11:04 +0700
Subject: [PATCH 023/202] update objects

---
 mcdc/code_factory/numba_objects_generator.py |  3 +
 mcdc/object_/base.py                         | 64 ++++++++------
 mcdc/object_/cell.py                         | 13 +--
 mcdc/object_/data.py                         | 31 ++++---
 mcdc/object_/distribution.py                 | 88 ++++++++++----------
 mcdc/object_/electron_reaction.py            | 51 ++++++------
 mcdc/object_/element.py                      |  6 +-
 mcdc/object_/gpu_tools.py                    |  7 +-
 mcdc/object_/material.py                     | 30 +++----
 mcdc/object_/mesh.py                         | 88 +++-----------------
 mcdc/object_/neutron_reaction.py             | 48 +++++------
 mcdc/object_/nuclide.py                      |  3 +
 mcdc/object_/particle.py                     | 29 +++----
 mcdc/object_/settings.py                     |  7 +-
 mcdc/object_/simulation.py                   | 31 ++++---
 mcdc/object_/source.py                       |  6 +-
 mcdc/object_/surface.py                      | 14 +---
 mcdc/object_/tally.py                        | 48 +++++------
 mcdc/object_/technique.py                    | 30 +++----
 mcdc/object_/universe.py                     |  9 +-
 20 files changed, 268 insertions(+), 338 deletions(-)

diff --git a/mcdc/code_factory/numba_objects_generator.py b/mcdc/code_factory/numba_objects_generator.py
index a5ad8efba..5a47246de 100644
--- a/mcdc/code_factory/numba_objects_generator.py
+++ b/mcdc/code_factory/numba_objects_generator.py
@@ -106,6 +106,9 @@ def generate_numba_objects(simulation):
     accessor_targets = {}
 
     for mcdc_class in mcdc_classes:
+        print(mcdc_class.label)
+        print(mcdc_class.non_numba)
+        exit()
         annotations[mcdc_class.label] = {}
         structures[mcdc_class.label] = []
         accessor_targets[mcdc_class.label] = []
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index 5176769b5..aa0284361 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -5,9 +5,16 @@ class MCDCBase:
     label: str
     non_numba: list[str]
 
-    def __init__(self, label: str, non_numba: list[str]):
-        self.label = label
-        self.non_numba = ["label", "non_numba"] + non_numba
+    def __init_subclass__(cls):
+        if not hasattr(cls, "label"):
+            raise NotImplementedError(
+                f"MC/DC class '{cls.__name__}' must have 'label' class attribute."
+            )
+
+        if not hasattr(cls, "non_numba"):
+            cls.non_numba = ["label", "non_numba"]
+        else:
+            cls.non_numba += ["label", "non_numba"]
 
     def __setattr__(self, key, value):
         hints = getattr(self.__class__, "__annotations__", {})
@@ -17,15 +24,20 @@ def __setattr__(self, key, value):
 
 
 class MCDCObject(MCDCBase):
+    # MC/DC framework metadata
+    label = "object"
+
     ID: int
     compile_ID: int
 
-    def __init__(self, label: str, non_numba: list[str]):
-        super().__init__(label, non_numba)
+    def __init_subclass__(cls):
+        super().__init_subclass__()
 
+        cls.non_numba += ["compile_ID"]
+
+    def __init__(self):
         self.ID = -1
         self.compile_ID = 0
-        self.non_numba += ["compile_ID"]
 
     def __repr__(self) -> str:
         nice_label = self.label.replace("_", " ").title()
@@ -43,31 +55,31 @@ def _compile_into_simulation(self, simulation) -> bool:
 
 
 class MCDCPolymorphic(MCDCObject):
-    child_label: str
-    child_type: int
-    child_ID: int
-
-    def __init__(
-        self,
-        label: str,
-        child_label: str,
-        child_type: int,
-        non_numba: list[str],
-    ):
-        super().__init__(label, non_numba)
-
-        self.child_label = child_label
-        self.child_type = child_type
-        self.child_ID = -1
-        self.non_numba += ["child_label"]
+    # MC/DC framework metadata
+    label = "polymorphic"
+
+    sub_type: int
+    sub_ID: int
+
+    def __init_subclass__(cls):
+        super().__init_subclass__()
+
+        if not hasattr(cls, "sub_type"):
+            raise NotImplementedError(
+                f"MC/DC class '{cls.__name__}' must have 'sub_type' class attribute."
+            )
+
+    def __init__(self):
+        super().__init__()
+
+        self.sub_ID = -1
 
     def __repr__(self) -> str:
         nice_label = self.label.replace("_", " ").title()
-        nice_sublabel = self.child_label.replace("_", " ").title()
         text = "\n"
-        text += f"{nice_label} - {nice_sublabel}\n"
+        text += f"{nice_label}\n"
         if self.compile_ID > 0:
-            text += f"  (compile_ID={self.compile_ID}, ID={self.ID})\n"
+            text += f"  (compile_ID={self.compile_ID}, ID={self.ID}, sub_ID={self.sub_ID})\n"
 
         return text
 
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index ec9a823b2..35e0bd6fd 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -40,14 +40,14 @@
 
 
 class Region(MCDCObject):
+    # MC/DC framework metadata
+    label = "region"
+
     type: str
     A: Surface | Region | NoneType
     B: Region | int | NoneType
 
     def __init__(self, type_, A, B):
-        # MC/DC framework metadata
-        super().__init__("region", [])
-
         self.type = type_
         self.A = A
         self.B = B
@@ -76,6 +76,10 @@ def __repr__(self):
 
 
 class Cell(MCDCObject):
+    # MC/DC framework metadata
+    label = "cell"
+    non_numba = ["region", "region_RPN", "fill"]
+
     name: str
 
     # Region definition
@@ -105,9 +109,6 @@ def __init__(
         translation: Sequence[float] = [0.0, 0.0, 0.0],
         rotation: Sequence[float] = [0.0, 0.0, 0.0],
     ):
-        # MC/DC framework metadata
-        super().__init__("cell", ["region", "region_RPN", "fill"])
-
         self.name = name or "(Unnamed cell)"
         self.region = region or Region("all", None, None)
         self.fill = fill
diff --git a/mcdc/object_/data.py b/mcdc/object_/data.py
index b33290293..fe72e06cc 100644
--- a/mcdc/object_/data.py
+++ b/mcdc/object_/data.py
@@ -25,14 +25,9 @@
 
 
 class DataBase(MCDCPolymorphic):
-    def __init__(
-        self,
-        child_label: str,
-        child_type: int,
-        non_numba: list[str],
-    ) -> None:
-        # MC/DC framework metadata
-        super().__init__("data", child_label, child_type, non_numba)
+    # MC/DC framework metadata
+    label = "data"
+    sub_type = -1
 
 
 # ======================================================================================
@@ -43,9 +38,9 @@ def __init__(
 
 
 class DataNone(DataBase):
-    def __init__(self) -> None:
-        # MC/DC framework metadata
-        super().__init__("none_data", DATA_NONE, [])
+    # MC/DC framework metadata
+    label = "none_data"
+    sub_type = DATA_NONE
 
 
 # ======================================================================================
@@ -54,6 +49,10 @@ def __init__(self) -> None:
 
 
 class DataTable(DataBase):
+    # MC/DC framework metadata
+    label = "table_data"
+    sub_type = DATA_TABLE
+
     # Main data
     N: int
     x: NDArray[float64]
@@ -75,9 +74,6 @@ def __init__(
         interpolation_boundaries: Sequence[int] | None = None,
         aux: NDArray[float64] | None = None,
     ) -> None:
-        # MC/DC framework metadata
-        super().__init__("table_data", DATA_TABLE, [])
-
         # Set primary data
         self.x = np.asarray(x, dtype=float64)
         self.y = np.asarray(y, dtype=float64)
@@ -237,12 +233,13 @@ def encode_interpolation(name: str) -> int:
 
 
 class DataPolynomial(DataBase):
+    # MC/DC framework metadata
+    label = "polynomial_data"
+    sub_type = DATA_POLYNOMIAL
+
     coefficients: NDArray[float64]
 
     def __init__(self, coefficients: NDArray[float64]) -> None:
-        # MC/DC framework metadata
-        super().__init__("polynomial_data", DATA_POLYNOMIAL, [])
-
         self.coefficients = np.asarray(coefficients, dtype=float64)
 
         if self.coefficients.ndim != 1:
diff --git a/mcdc/object_/distribution.py b/mcdc/object_/distribution.py
index 1fd63f99b..c27278591 100644
--- a/mcdc/object_/distribution.py
+++ b/mcdc/object_/distribution.py
@@ -34,14 +34,9 @@
 
 
 class DistributionBase(MCDCPolymorphic):
-    def __init__(
-        self,
-        child_label: str,
-        child_type: int,
-        non_numba: list[str],
-    ) -> None:
-        # MC/DC framework metadata
-        super().__init__("distribution", child_label, child_type, non_numba)
+    # MC/DC framework metadata
+    label = "distribution"
+    sub_type = -1
 
 
 # ======================================================================================
@@ -53,9 +48,9 @@ def __init__(
 
 
 class DistributionNone(DistributionBase):
-    def __init__(self) -> None:
-        # MC/DC framework metadata
-        super().__init__("none_distribution", DISTRIBUTION_NONE, [])
+    # MC/DC framework metadata
+    label = "none_distribution"
+    sub_type = DISTRIBUTION_NONE
 
 
 # ======================================================================================
@@ -64,14 +59,15 @@ def __init__(self) -> None:
 
 
 class DistributionPMF(DistributionBase):
+    # MC/DC framework metadata
+    label = "pmf_distribution"
+    sub_type = DISTRIBUTION_PMF
+
     value: NDArray[float64]
     pmf: NDArray[float64]
     cmf: NDArray[float64]
 
     def __init__(self, value: ArrayLike, pmf: ArrayLike) -> None:
-        # MC/DC framework metadata
-        super().__init__("pmf_distribution", DISTRIBUTION_PMF, [])
-
         self.value = np.asarray(value, dtype=float64)
         pmf_array = np.asarray(pmf, dtype=float64)
 
@@ -100,6 +96,10 @@ def __repr__(self) -> str:
 
 
 class DistributionTabulated(DistributionBase):
+    # MC/DC framework metadata
+    label = "tabulated_distribution"
+    sub_type = DISTRIBUTION_TABULATED
+
     pdf: DataTable
 
     def __init__(
@@ -108,9 +108,6 @@ def __init__(
         pdf: ArrayLike | None = None,
         cdf: ArrayLike | None = None,
     ) -> None:
-        # MC/DC framework metadata
-        super().__init__("tabulated_distribution", DISTRIBUTION_TABULATED, [])
-
         if (pdf is None) == (cdf is None):
             print_error("Exactly one of pdf or cdf must be provided.")
 
@@ -170,6 +167,10 @@ def __repr__(self) -> str:
 
 
 class DistributionMultiTable(DistributionBase):
+    # MC/DC framework metadata
+    label = "multi_table_distribution"
+    sub_type = DISTRIBUTION_MULTITABLE
+
     grid: NDArray[float64]
     tables: list[DistributionTabulated]
 
@@ -181,9 +182,6 @@ def __init__(
         pdf: ArrayLike | None = None,
         cdf: ArrayLike | None = None,
     ) -> None:
-        # MC/DC framework metadata
-        super().__init__("multi_table_distribution", DISTRIBUTION_MULTITABLE, [])
-
         if (pdf is None) == (cdf is None):
             print_error("Exactly one of pdf or cdf must be provided.")
 
@@ -273,17 +271,14 @@ def __repr__(self) -> str:
 
 
 class DistributionLevelScattering(DistributionBase):
+    # MC/DC framework metadata
+    label = "level_scattering_distribution"
+    sub_type = DISTRIBUTION_LEVEL_SCATTERING
+
     C1: float
     C2: float
 
     def __init__(self, C1: float, C2: float) -> None:
-        # MC/DC framework metadata
-        super().__init__(
-            "level_scattering_distribution",
-            DISTRIBUTION_LEVEL_SCATTERING,
-            [],
-        )
-
         self.C1 = C1
         self.C2 = C2
 
@@ -301,6 +296,10 @@ def __repr__(self) -> str:
 
 
 class DistributionEvaporation(DistributionBase):
+    # MC/DC framework metadata
+    label = "evaporation_distribution"
+    sub_type = DISTRIBUTION_EVAPORATION
+
     nuclear_temperature: DataTable
     restriction_energy: float
 
@@ -312,9 +311,6 @@ def __init__(
         temperature_interpolations: int | Sequence[int],
         interpolation_boundaries: Sequence[int] | None,
     ) -> None:
-        # MC/DC framework metadata
-        super().__init__("evaporation_distribution", DISTRIBUTION_EVAPORATION, [])
-
         self.restriction_energy = restriction_energy
         self.nuclear_temperature = DataTable(
             nuclear_temperature_energy_grid,
@@ -344,6 +340,10 @@ def __repr__(self) -> str:
 
 
 class DistributionMaxwellian(DistributionBase):
+    # MC/DC framework metadata
+    label = "maxwellian_distribution"
+    sub_type = DISTRIBUTION_MAXWELLIAN
+
     nuclear_temperature: DataTable
     restriction_energy: float
 
@@ -355,9 +355,6 @@ def __init__(
         temperature_interpolations: int | Sequence[int],
         interpolation_boundaries: Sequence[int] | None,
     ) -> None:
-        # MC/DC framework metadata
-        super().__init__("maxwellian_distribution", DISTRIBUTION_MAXWELLIAN, [])
-
         self.restriction_energy = restriction_energy
         self.nuclear_temperature = DataTable(
             nuclear_temperature_energy_grid,
@@ -387,6 +384,10 @@ def __repr__(self) -> str:
 
 
 class DistributionKalbachMann(DistributionBase):
+    # MC/DC framework metadata
+    label = "kalbach_mann_distribution"
+    sub_type = DISTRIBUTION_KALBACH_MANN
+
     energy: NDArray[float64]
     offset: NDArray[int64]
     energy_out: NDArray[float64]
@@ -404,9 +405,6 @@ def __init__(
         precompound_factor: ArrayLike,
         angular_slope: ArrayLike,
     ) -> None:
-        # MC/DC framework metadata
-        super().__init__("kalbach_mann_distribution", DISTRIBUTION_KALBACH_MANN, [])
-
         self.energy = np.asarray(energy, dtype=float64)
         self.offset = np.asarray(offset, dtype=int64)
         self.energy_out = np.asarray(energy_out, dtype=float64)
@@ -441,6 +439,10 @@ def __repr__(self) -> str:
 
 
 class DistributionTabulatedEnergyAngle(DistributionBase):
+    # MC/DC framework metadata
+    label = "tabulated_energy_angle_distribution"
+    sub_type = DISTRIBUTION_TABULATED_ENERGY_ANGLE
+
     energy: NDArray[float64]
     offset: NDArray[int64]
     energy_out: NDArray[float64]
@@ -461,13 +463,6 @@ def __init__(
         cosine: ArrayLike,
         cosine_pdf: ArrayLike,
     ) -> None:
-        # MC/DC framework metadata
-        super().__init__(
-            child_label="tabulated_energy_angle_distribution",
-            child_type=DISTRIBUTION_TABULATED_ENERGY_ANGLE,
-            non_numba=[],
-        )
-
         self.energy = np.asarray(energy, dtype=float64)
         self.offset = np.asarray(offset, dtype=int64)
         self.energy_out = np.asarray(energy_out, dtype=float64)
@@ -538,6 +533,10 @@ def __repr__(self) -> str:
 
 
 class DistributionNBody(DistributionBase):
+    # MC/DC framework metadata
+    label = "nbody_distribution"
+    sub_type = DISTRIBUTION_N_BODY
+
     pdf: DataTable
 
     def __init__(
@@ -545,9 +544,6 @@ def __init__(
         values: ArrayLike,
         probabilities: ArrayLike,
     ) -> None:
-        # MC/DC framework metadata
-        super().__init__("nbody_distribution", DISTRIBUTION_N_BODY, [])
-
         value_array = np.asarray(values, dtype=float64)
         probability_array = np.asarray(probabilities, dtype=float64)
 
diff --git a/mcdc/object_/electron_reaction.py b/mcdc/object_/electron_reaction.py
index 0b102b70c..3e5a3235d 100644
--- a/mcdc/object_/electron_reaction.py
+++ b/mcdc/object_/electron_reaction.py
@@ -26,16 +26,17 @@
 
 
 class ElectronReactionBase(MCDCPolymorphic):
-    # Annotations for Numba mode
-    label: str = "electron_reaction"
-    #
+    # MC/DC framework metadata
+    label = "electron_reaction"
+    sub_type = -1
+
     MT: int
     xs: NDArray[float64]
     xs_offset_: int  # "xs_offset" is reserved for "xs"
     reference_frame: int
 
-    def __init__(self, type_, MT, xs, xs_offset, reference_frame):
-        super().__init__(type_)
+    def __init__(self, MT, xs, xs_offset, reference_frame):
+        super().__init__()
         self.MT = MT
         self.xs = xs
         self.xs_offset_ = xs_offset
@@ -64,9 +65,10 @@ def decode_reference_frame(type_):
 
 
 class ElectronReactionIonization(ElectronReactionBase):
-    # Annotations for Numba mode
-    label: str = "electron_ionization_reaction"
-    #
+    # MC/DC framework metadata
+    label = "electron_ionization_reaction"
+    sub_type = ELECTRON_REACTION_IONIZATION
+
     N_subshell: int
     subshell_xs: list[DataBase]
     subshell_product: list[DistributionBase]
@@ -80,8 +82,7 @@ def __init__(
         subshell_xs,
         subshell_product,
     ):
-        type_ = ELECTRON_REACTION_IONIZATION
-        super().__init__(type_, MT, xs, xs_offset, reference_frame)
+        super().__init__(MT, xs, xs_offset, reference_frame)
 
         self.N_subshell = len(subshell_xs)
         self.subshell_xs = subshell_xs
@@ -156,9 +157,10 @@ def __repr__(self):
 
 
 class ElectronReactionElasticScattering(ElectronReactionBase):
-    # Annotations for Numba mode
-    label: str = "electron_elastic_scattering_reaction"
-    #
+    # MC/DC framework metadata
+    label = "electron_elastic_scattering_reaction"
+    sub_type = ELECTRON_REACTION_ELASTIC_SCATTERING
+
     mu_cut: float
     xs_large: DataBase
     mu: DistributionMultiTable
@@ -172,8 +174,7 @@ def __init__(
         xs_large,
         mu,
     ):
-        type_ = ELECTRON_REACTION_ELASTIC_SCATTERING
-        super().__init__(type_, MT, xs, xs_offset, reference_frame)
+        super().__init__(MT, xs, xs_offset, reference_frame)
         self.mu_cut = MU_CUTOFF
         self.xs_large = xs_large
         self.mu = mu
@@ -219,14 +220,14 @@ def __repr__(self):
 
 
 class ElectronReactionBremsstrahlung(ElectronReactionBase):
-    # Annotations for Numba mode
-    label: str = "electron_bremsstrahlung_reaction"
-    #
+    # MC/DC framework metadata
+    label = "electron_bremsstrahlung_reaction"
+    sub_type = ELECTRON_REACTION_BREMSSTRAHLUNG
+
     eloss: DataBase
 
     def __init__(self, MT, xs, xs_offset, reference_frame, eloss):
-        type_ = ELECTRON_REACTION_BREMSSTRAHLUNG
-        super().__init__(type_, MT, xs, xs_offset, reference_frame)
+        super().__init__(MT, xs, xs_offset, reference_frame)
         self.eloss = eloss
 
     @classmethod
@@ -250,14 +251,14 @@ def __repr__(self):
 
 
 class ElectronReactionExcitation(ElectronReactionBase):
-    # Annotations for Numba mode
-    label: str = "electron_excitation_reaction"
-    #
+    # MC/DC framework metadata
+    label = "electron_excitation_reaction"
+    sub_type = ELECTRON_REACTION_EXCITATION
+
     eloss: DataBase
 
     def __init__(self, MT, xs, xs_offset, reference_frame, eloss):
-        type_ = ELECTRON_REACTION_EXCITATION
-        super().__init__(type_, MT, xs, xs_offset, reference_frame)
+        super().__init__(MT, xs, xs_offset, reference_frame)
         self.eloss = eloss
 
     @classmethod
diff --git a/mcdc/object_/element.py b/mcdc/object_/element.py
index e3d317408..0efd92232 100644
--- a/mcdc/object_/element.py
+++ b/mcdc/object_/element.py
@@ -17,9 +17,9 @@
 
 
 class Element(MCDCObject):
-    # Annotations for Numba mode
-    label: str = "element"
-    #
+    # MC/DC framework metadata
+    label = "element"
+
     name: str
     atomic_weight_ratio: float
     atomic_number: int
diff --git a/mcdc/object_/gpu_tools.py b/mcdc/object_/gpu_tools.py
index 6e31ba5b5..1a97fa0e8 100644
--- a/mcdc/object_/gpu_tools.py
+++ b/mcdc/object_/gpu_tools.py
@@ -8,13 +8,12 @@
 
 @dataclass
 class GPUMeta(MCDCBase):
+    # MC/DC framework metadata
+    label = "gpu_meta"
+
     state_pointer: uintp = uintp(0)
     program_pointer: uintp = uintp(0)
     simulation_pointer: uintp = uintp(0)
     data_pointer: uintp = uintp(0)
 
     # Note that the uintp is manually overriden in code_factory.
-
-    def __init__(self):
-        # MC/DC framework metadata
-        super().__init__("gpu_meta", [])
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index af6b4d171..77425dbc7 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -21,19 +21,17 @@
 
 
 class MaterialBase(MCDCPolymorphic):
+    # MC/DC framework metadata
+    label = "material"
+    sub_type = -1
+
     name: str
     fissionable: bool
 
     def __init__(
         self,
         name: str,
-        child_label: str,
-        child_type: int,
-        non_numba: list[str],
     ) -> None:
-        # MC/DC framework metadata
-        super().__init__("material", child_label, child_type, non_numba)
-
         self.name = name or "(Unnamed material)"
         self.fissionable = False
 
@@ -51,6 +49,11 @@ def __repr__(self):
 
 
 class Material(MaterialBase):
+    # MC/DC framework metadata
+    label = "native_material"
+    sub_type = MATERIAL
+    non_numba = ["nuclide_composition", "element_composition"]
+
     nuclide_composition: dict[Nuclide, float]  # Non-numba
     element_composition: dict[Element, float]  # Non-numba
 
@@ -66,13 +69,7 @@ def __init__(
         element_composition: dict[str, float] = {},
         temperature: float = 293.6,
     ):
-        # MC/DC framework metadata
-        super().__init__(
-            name,
-            "native_material",
-            MATERIAL,
-            ["nuclide_composition", "element_composition"],
-        )
+        super().__init__(name)
 
         # Temperature
         self.temperature = temperature
@@ -195,6 +192,10 @@ def __repr__(self):
 
 
 class MaterialMG(MaterialBase):
+    # MC/DC framework metadata
+    label = "multigroup_material"
+    sub_type = MATERIAL_MG
+
     G: int
     J: int
     mgxs_speed: Annotated[NDArray[float64], ("G",)]
@@ -226,8 +227,7 @@ def __init__(
         speed: NDArray[float64] | NoneType = None,
         decay_rate: NDArray[float64] | NoneType = None,
     ):
-        # MC/DC framework metadata
-        super().__init__(name, "multigroup_material", MATERIAL_MG, [])
+        super().__init__(name)
 
         # Energy group size
         if capture is not None:
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index 8212ea09d..8cba7bfcd 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -16,6 +16,10 @@
 
 
 class MeshBase(MCDCPolymorphic):
+    # MC/DC framework metadata
+    label = "mesh"
+    sub_type = -1
+
     name: str
     N_bin: int
     Nx: int
@@ -25,24 +29,8 @@ class MeshBase(MCDCPolymorphic):
     def __init__(
         self,
         name: str,
-        child_label: str,
-        child_type: int,
-        non_numba: list[str],
     ) -> None:
-        """Initialize mesh base framework metadata."""
-        super().__init__(
-            label="mesh",
-            child_label=child_label,
-            child_type=child_type,
-            non_numba=non_numba,
-        )
-
-        # Set name
-        if name == "":
-            self.name = "(Unnamed mesh)"
-        else:
-            self.name = name
-
+        self.name = name or "(Unnamed mesh)"
         self.N_bin = 0
 
     def __repr__(self):
@@ -59,32 +47,9 @@ def __repr__(self):
 
 
 class MeshUniform(MeshBase):
-    """
-    Define a uniform rectilinear mesh.
-
-    Each axis is specified as ``(origin, width, N_bins)``.
-
-    Parameters
-    ----------
-    name : str, optional
-        User label.
-    x : tuple of (float, float, int), optional
-        ``(x0, dx, Nx)`` — origin, bin width, and number of bins along x.
-    y : tuple of (float, float, int), optional
-        ``(y0, dy, Ny)`` — origin, bin width, and number of bins along y.
-    z : tuple of (float, float, int), optional
-        ``(z0, dz, Nz)`` — origin, bin width, and number of bins along z.
-
-    Returns
-    -------
-    MeshUniform
-        The uniform mesh object.
-
-    See Also
-    --------
-    mcdc.MeshStructured : Creates a mesh with arbitrary bin edges.
-    mcdc.TallyMesh : Creates a tally on a mesh.
-    """
+    # MC/DC framework metadata
+    label = "uniform_mesh"
+    sub_type = MESH_UNIFORM
 
     x0: float
     dx: float
@@ -105,9 +70,6 @@ def __init__(
     ):
         super().__init__(
             name,
-            child_label="uniform mesh",
-            child_type=MESH_UNIFORM,
-            non_numba=[],
         )
 
         # Set the grid
@@ -138,30 +100,9 @@ def __repr__(self):
 
 
 class MeshStructured(MeshBase):
-    """
-    Define a structured rectilinear mesh with arbitrary bin edges.
-
-    Parameters
-    ----------
-    name : str, optional
-        User label.
-    x : array_like of float, optional
-        Bin edges along x (cm).
-    y : array_like of float, optional
-        Bin edges along y (cm).
-    z : array_like of float, optional
-        Bin edges along z (cm).
-
-    Returns
-    -------
-    MeshStructured
-        The structured mesh object.
-
-    See Also
-    --------
-    mcdc.MeshUniform : Creates a uniform mesh.
-    mcdc.TallyMesh : Creates a tally on a mesh.
-    """
+    # MC/DC framework metadata
+    label = "structured_mesh"
+    sub_type = MESH_STRUCTURED
 
     x: NDArray[float64]
     y: NDArray[float64]
@@ -174,12 +115,7 @@ def __init__(
         y: Sequence[float] | NDArray[float64] = np.array([-INF, INF]),
         z: Sequence[float] | NDArray[float64] = np.array([-INF, INF]),
     ):
-        super().__init__(
-            name,
-            child_label="structured mesh",
-            child_type=MESH_STRUCTURED,
-            non_numba=[],
-        )
+        super().__init__(name)
 
         # Set the grid
         self.x = np.array(x)
diff --git a/mcdc/object_/neutron_reaction.py b/mcdc/object_/neutron_reaction.py
index 08ca364fd..99b8464b4 100644
--- a/mcdc/object_/neutron_reaction.py
+++ b/mcdc/object_/neutron_reaction.py
@@ -37,17 +37,17 @@
 
 
 class NeutronReactionBase(MCDCPolymorphic):
-    # Annotations for Numba mode
-    label: str = "neutron_reaction"
-    #
+    # MC/DC framework metadata
+    label = "neutron_reaction"
+    sub_type = -1
+
     MT: int
     xs: NDArray[float64]
     xs_offset_: int  # "xs_offset" ir reserved for "xs"
     reference_frame: int
     q_value: float64
 
-    def __init__(self, type_, MT, xs, xs_offset, reference_frame, q_value):
-        super().__init__(type_)
+    def __init__(self, MT, xs, xs_offset, reference_frame, q_value):
         self.MT = MT
         self.xs = xs
         self.xs_offset_ = xs_offset
@@ -78,14 +78,14 @@ def decode_reference_frame(type_):
 
 
 class NeutronReactionElasticScattering(NeutronReactionBase):
-    # Annotations for Numba mode
-    label: str = "neutron_elastic_scattering_reaction"
-    #
+    # MC/DC framework metadata
+    label = "neutron_elastic_scattering_reaction"
+    sub_type = NEUTRON_REACTION_ELASTIC_SCATTERING
+
     mu_table: DistributionMultiTable
 
     def __init__(self, MT, xs, xs_offset, reference_frame, mu):
-        type_ = NEUTRON_REACTION_ELASTIC_SCATTERING
-        super().__init__(type_, MT, xs, xs_offset, reference_frame, 0.0)
+        super().__init__(MT, xs, xs_offset, reference_frame, 0.0)
         self.mu_table = mu
 
     @classmethod
@@ -106,12 +106,12 @@ def __repr__(self):
 
 
 class NeutronReactionCapture(NeutronReactionBase):
-    # Annotations for Numba mode
-    label: str = "neutron_capture_reaction"
+    # MC/DC framework metadata
+    label = "neutron_capture_reaction"
+    sub_type = NEUTRON_REACTION_CAPTURE
 
     def __init__(self, MT, xs, xs_offset, reference_frame, q_value):
-        type_ = NEUTRON_REACTION_CAPTURE
-        super().__init__(type_, MT, xs, xs_offset, reference_frame, q_value)
+        super().__init__(MT, xs, xs_offset, reference_frame, q_value)
 
     @classmethod
     def from_h5_group(cls, h5_group):
@@ -125,9 +125,10 @@ def from_h5_group(cls, h5_group):
 
 
 class NeutronReactionInelasticScattering(NeutronReactionBase):
-    # Annotations for Numba mode
-    label: str = "neutron_inelastic_scattering_reaction"
-    #
+    # MC/DC framework metadata
+    label = "neutron_inelastic_scattering_reaction"
+    sub_type = NEUTRON_REACTION_INELASTIC_SCATTERING
+
     multiplicity: int
     angle_type: int
     mu: DistributionBase
@@ -153,8 +154,7 @@ def __init__(
         spectrum_probability,
         energy_spectra,
     ):
-        type_ = NEUTRON_REACTION_INELASTIC_SCATTERING
-        super().__init__(type_, MT, xs, xs_offset, reference_frame, q_value)
+        super().__init__(MT, xs, xs_offset, reference_frame, q_value)
 
         self.multiplicity = multiplicity
         self.angle_type = angle_type
@@ -219,9 +219,10 @@ def __repr__(self):
 
 
 class NeutronReactionFission(NeutronReactionBase):
-    # Annotations for Numba mode
-    label: str = "neutron_fission_reaction"
-    #
+    # MC/DC framework metadata
+    label = "neutron_fission_reaction"
+    sub_type = NEUTRON_REACTION_FISSION
+
     angle_type: int
     mu: DistributionBase
     spectrum: DistributionBase
@@ -237,8 +238,7 @@ def __init__(
         mu,
         spectrum,
     ):
-        type_ = NEUTRON_REACTION_FISSION
-        super().__init__(type_, MT, xs, xs_offset, reference_frame, q_value)
+        super().__init__(MT, xs, xs_offset, reference_frame, q_value)
         self.angle_type = angle_type
         self.mu = mu
         self.spectrum = spectrum
diff --git a/mcdc/object_/nuclide.py b/mcdc/object_/nuclide.py
index 72a9e195f..089e8c8e6 100644
--- a/mcdc/object_/nuclide.py
+++ b/mcdc/object_/nuclide.py
@@ -26,6 +26,9 @@
 
 
 class Nuclide(MCDCObject):
+    # MC/DC framework metadata
+    label = "nuclide"
+
     # Annotations for Numba mode
     label: str = "nuclide"
     #
diff --git a/mcdc/object_/particle.py b/mcdc/object_/particle.py
index 2d570c456..56ef818d8 100644
--- a/mcdc/object_/particle.py
+++ b/mcdc/object_/particle.py
@@ -13,6 +13,9 @@
 
 @dataclass
 class ParticleData(MCDCBase):
+    # MC/DC framework metadata
+    label = "particle_data"
+
     x: float = 0.0
     y: float = 0.0
     z: float = 0.0
@@ -26,22 +29,20 @@ class ParticleData(MCDCBase):
     particle_type: int = PARTICLE_NEUTRON
     rng_seed: uint64 = uint64(1)
 
-    def __post_init__(self):
-        # MC/DC framework metadata
-        super().__init__("particle_data", [])
-
 
 @dataclass
 class CollisionData(MCDCBase):
-    energy_deposition: float = 0.0
+    # MC/DC framework metadata
+    label = "collision_data"
 
-    def __post_init__(self):
-        # MC/DC framework metadata
-        super().__init__("collision_data", [])
+    energy_deposition: float = 0.0
 
 
 @dataclass
 class Particle(ParticleData):
+    # MC/DC framework metadata
+    label = "particle"
+
     cell_ID: int = -1
     material_ID: int = -1
     surface_ID: int = -1
@@ -49,20 +50,16 @@ class Particle(ParticleData):
     fresh: bool = False
     event: int = -1
 
-    def __post_init__(self):
-        # MC/DC framework metadata
-        super(ParticleData, self).__init__("particle", [])
-
 
 class ParticleBank(MCDCBase):
+    # MC/DC framework metadata
+    label = "particle_bank"
+    non_numba = ["particles"]
+
     particles: list[ParticleData] = []  # Non-numba
     size: Annotated[NDArray[int64], (1,)]
     tag: str = ""
 
     def __init__(self, tag):
-        # MC/DC framework metadata
-        """Initialize particle bank framework metadata."""
-        super().__init__("particle_bank", ["particles"])
-
         self.tag = tag
         self.size = np.zeros(1, dtype=int64)
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index 41b3f192e..063f6e5bb 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -19,6 +19,9 @@
 
 @dataclass
 class Settings(MCDCBase):
+    # MC/DC framework metadata
+    label = "settings"
+
     # Basic
     N_particle: int = 0
     N_batch: int = 1
@@ -68,10 +71,6 @@ class Settings(MCDCBase):
     gpu_async_type: int = GPU_ASYNC_SIMPLE
     gpu_storage: int = GPU_STORAGE_SEPARATE
 
-    def __post_init__(self):
-        # MC/DC framework metadata
-        super().__init__("settings", [])
-
     def set_time_census(self, time, tally_frequency=None):
         # Make sure that the time grid points are sorted
         if not is_sorted(time):
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 1278db863..daff000fd 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -46,6 +46,19 @@
 
 
 class Simulation(MCDCBase):
+    # MC/DC framework metadata
+    label = "simulation"
+    non_numba = [
+        "_next_compile_ID",
+        "compiled",
+        "compile_ID",
+        "regions",
+        "root_universe",
+        "bank_active",
+        "bank_census",
+        "bank_source",
+        "bank_future",
+    ]
     _next_compile_ID: int = 1  # Non-Numba
 
     # Basic parameters
@@ -68,7 +81,7 @@ class Simulation(MCDCBase):
     regions: list[Region]  # Non-Numba
     cells: list[Cell]
     universes: list[Universe]
-    root_universe: Universe
+    root_universe: Universe  # Non-Numba
     lattices: list[Lattice]
     meshes: list[MeshBase]
 
@@ -142,22 +155,6 @@ class Simulation(MCDCBase):
     source_seed: int
 
     def __init__(self, name: str = "") -> None:
-        # MC/DC framework metadata
-        super().__init__(
-            label="simulation",
-            non_numba=[
-                "regions",
-                "root_universe",
-                "bank_active",
-                "bank_census",
-                "bank_source",
-                "bank_future",
-                "_next_compile_ID",
-                "compiled",
-                "compile_ID",
-            ],
-        )
-
         self.compile_ID = 0
         self.compiled = False
 
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index b815d7a3c..8b1e90573 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -35,6 +35,9 @@ def decode_particle_type(type_):
 
 
 class Source(MCDCObject):
+    # MC/DC framework metadata
+    label = "source"
+
     """
     Define a particle source.
 
@@ -226,9 +229,6 @@ def __init__(
         #
         probability: float = 1.0,
     ):
-        # MC/DC framework metadata
-        super().__init__("source", [])
-
         self.name = name or "(Unnamed source)"
 
         # ==============================================================================
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 55968c1d9..5bb112ba0 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -41,6 +41,9 @@
 
 
 class Surface(MCDCObject):
+    # MC/DC framework metadata
+    label = "surface"
+
     type: int
     name: str
     boundary_condition: int
@@ -72,17 +75,8 @@ class Surface(MCDCObject):
     tallies: list[TallySurfaceCrossing]
 
     def __init__(self, type_, name, boundary_condition):
-        # MC/DC framework metadata
-        super().__init__("surface", [])
-
-        # Type and name
         self.type = type_
-
-        # Set name
-        if name == "":
-            self.name = "(Unnamed surface)"
-        else:
-            self.name = name
+        self.name = name or "(Unnamed surface)"
 
         # Boundary condition
         if boundary_condition == "none":
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index f41def64c..e14079b9c 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -46,6 +46,10 @@
 
 
 class Tally(MCDCPolymorphic):
+    # MC/DC framework metadata
+    label = "tally"
+    sub_type = -1
+
     # Basic properties
     name: str
     scores: list[int]
@@ -147,10 +151,7 @@ def __init__(
     ):
 
         # Set name
-        if name == "":
-            self.name = "(Unnamed tally)"
-        else:
-            self.name = name
+        self.name = name or "(Unnamed tally)"
 
         # Set scores
         self.scores = []
@@ -321,6 +322,11 @@ def decode_score_type(type_, lower_case=False):
 
 
 class TallySurfaceCrossing(Tally):
+    # MC/DC framework metadata
+    label = "surface_crossing_tally"
+    sub_type = TALLY_SURFACE_CROSSING
+    non_numba = ["surface", "cell"]
+
     surface: Surface | NoneType  # Non-numba
     surface_filtered: bool
     surface_filter_ID: int
@@ -341,14 +347,6 @@ def __init__(
         energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
-        # MC/DC framework metadata
-        super(Tally, self).__init__(
-            label="tally",
-            child_label="surface_crossing_tally",
-            child_type=TALLY_SURFACE_CROSSING,
-            non_numba=["surface", "cell"],
-        )
-
         super().__init__(
             name,
             scores,
@@ -415,6 +413,11 @@ def __repr__(self):
 
 
 class TallyCollision(Tally):
+    # MC/DC framework metadata
+    label = "collision_tally"
+    sub_type = TALLY_COLLISION
+    non_numba = ["cell", "mesh"]
+
     # Spatial filters
     cell: Cell | NoneType
     cell_filtered: bool
@@ -445,14 +448,6 @@ def __init__(
         if mesh is not None:
             spatial_shape = (mesh.Nx, mesh.Ny, mesh.Nz)
 
-        # MC/DC framework metadata
-        super(Tally, self).__init__(
-            label="tally",
-            child_label="collision_tally",
-            child_type=TALLY_COLLISION,
-            non_numba=["cell", "mesh"],
-        )
-
         super().__init__(
             name,
             scores,
@@ -535,6 +530,11 @@ def __repr__(self):
 
 
 class TallyTracklength(Tally):
+    # MC/DC framework metadata
+    label = "tracklength_tally"
+    sub_type = TALLY_TRACKLENGTH
+    non_numba = ["cell", "mesh"]
+
     # Spatial filters
     cell: Cell | NoneType
     cell_filtered: bool
@@ -565,14 +565,6 @@ def __init__(
         if mesh is not None:
             spatial_shape = (mesh.Nx, mesh.Ny, mesh.Nz)
 
-        # MC/DC framework metadata
-        super(Tally, self).__init__(
-            label="tally",
-            child_label="tracklength_tally",
-            child_type=TALLY_TRACKLENGTH,
-            non_numba=["cell", "mesh"],
-        )
-
         super().__init__(
             name,
             scores,
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index 8a91ef280..d3bd8fe6e 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -13,12 +13,12 @@
 
 
 class ImplicitCapture(MCDCBase):
+    # MC/DC framework metadata
+    label = "implicit_capture"
+
     active: bool
 
     def __init__(self):
-        # MC/DC framework metadata
-        super().__init__("implicit_capture", [])
-
         self.active = False
 
     def __call__(self, active: bool = True):
@@ -31,13 +31,13 @@ def __call__(self, active: bool = True):
 
 
 class WeightedEmission(MCDCBase):
+    # MC/DC framework metadata
+    label = "weighted_emission"
+
     active: bool
     weight_target: float
 
     def __init__(self):
-        # MC/DC framework metadata
-        super().__init__("weighted_emission", [])
-
         self.active = False
         self.weight_target = 0.0
 
@@ -52,14 +52,14 @@ def __call__(self, active: bool = True, weight_target: float = 1.0):
 
 
 class GlobalWeightRoulette(MCDCBase):
+    # MC/DC framework metadata
+    label = "global_weight_roulette"
+
     active: bool
     weight_threshold: float
     weight_target: float
 
     def __init__(self):
-        # MC/DC framework metadata
-        super().__init__("global_weight_roulette", [])
-
         self.active = False
         self.weight_threshold = 0.0
         self.weight_target = 1.0
@@ -80,6 +80,9 @@ def __call__(self, weight_threshold: float = 0.0, weight_target: float = 1.0):
 
 
 class WeightWindows(MCDCBase):
+    # MC/DC framework metadata
+    label = "weight_windows"
+
     active: bool
 
     # energy
@@ -97,9 +100,6 @@ class WeightWindows(MCDCBase):
     upper_weights: Annotated[NDArray[np.float64], ("Ne", "Nx", "Ny", "Nz")]
 
     def __init__(self):
-        # MC/DC framework metadata
-        super().__init__("weight_windows", [])
-
         self.active = False
         self.energy_bounds = np.array([0.0, 1.0])
         self.Ne = 1
@@ -183,12 +183,12 @@ def __call__(self, weight_windows, mesh=None, energy=None):
 
 
 class PopulationControl(MCDCBase):
+    # MC/DC framework metadata
+    label = "population_control"
+
     active: bool
 
     def __init__(self):
-        # MC/DC framework metadata
-        super().__init__("population_control", [])
-
         self.active = False
 
     def __call__(self, active: bool = True):
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index 464ad2604..f43b5e00e 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -24,13 +24,13 @@
 
 
 class Universe(MCDCObject):
+    # MC/DC framework metadata
+    label = "particle_bank"
+
     name: str
     cells: list[Cell]
 
     def __init__(self, name: str = "", cells: list[Cell] = []):
-        # MC/DC framework metadata
-        super().__init__("universe", [])
-
         self.name = name or "(Unnamed universe)"
         self.cells = cells
 
@@ -59,6 +59,9 @@ def __repr__(self):
 
 
 class Lattice(MCDCObject):
+    # MC/DC framework metadata
+    label = "particle_bank"
+
     name: str
 
     x0: float

From 69f9c24fe19cdb4873b02dd670f54f608cafa855 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 22 Jul 2026 10:44:55 +0700
Subject: [PATCH 024/202] update objects

---
 mcdc/code_factory/numba_objects_generator.py |  8 +++++---
 mcdc/code_factory/python_objects_compiler.py |  4 ++--
 mcdc/object_/base.py                         | 11 -----------
 mcdc/object_/cell.py                         |  2 ++
 mcdc/object_/distribution.py                 | 18 ++++++++++++++++++
 mcdc/object_/material.py                     |  7 +++----
 mcdc/object_/mesh.py                         |  7 +++----
 mcdc/object_/source.py                       |  2 ++
 mcdc/object_/surface.py                      |  2 ++
 mcdc/object_/tally.py                        |  1 +
 mcdc/object_/universe.py                     |  8 +++++---
 11 files changed, 43 insertions(+), 27 deletions(-)

diff --git a/mcdc/code_factory/numba_objects_generator.py b/mcdc/code_factory/numba_objects_generator.py
index 5a47246de..97c82cf71 100644
--- a/mcdc/code_factory/numba_objects_generator.py
+++ b/mcdc/code_factory/numba_objects_generator.py
@@ -106,9 +106,6 @@ def generate_numba_objects(simulation):
     accessor_targets = {}
 
     for mcdc_class in mcdc_classes:
-        print(mcdc_class.label)
-        print(mcdc_class.non_numba)
-        exit()
         annotations[mcdc_class.label] = {}
         structures[mcdc_class.label] = []
         accessor_targets[mcdc_class.label] = []
@@ -165,6 +162,11 @@ def generate_numba_objects(simulation):
 
             annotations[mcdc_class.label].update(new_annotations)
 
+        print(mcdc_class.label)
+        print(mcdc_class.__annotations__)
+        print(annotations[mcdc_class.label])
+        input()
+
     # Particle banks
     for name in bank_names:
         annotations[name] = {
diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index f19c7799e..634f73b37 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -98,9 +98,9 @@ def register_object(object_: MCDCObject, simulation: Simulation) -> bool:
     # Assign IDs
     object_.ID = len(object_list)
     if isinstance(object_, MCDCPolymorphic):
-        object_.child_ID = sum(
+        object_.sub_ID = sum(
             [
-                x.child_type == object_.child_type
+                x.sub_type == object_.sub_type
                 for x in object_list
                 if isinstance(x, MCDCPolymorphic)
             ]
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index aa0284361..062137518 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -3,7 +3,6 @@
 
 class MCDCBase:
     label: str
-    non_numba: list[str]
 
     def __init_subclass__(cls):
         if not hasattr(cls, "label"):
@@ -11,11 +10,6 @@ def __init_subclass__(cls):
                 f"MC/DC class '{cls.__name__}' must have 'label' class attribute."
             )
 
-        if not hasattr(cls, "non_numba"):
-            cls.non_numba = ["label", "non_numba"]
-        else:
-            cls.non_numba += ["label", "non_numba"]
-
     def __setattr__(self, key, value):
         hints = getattr(self.__class__, "__annotations__", {})
         if key in hints and not check_type(value, hints[key], self.__class__, self):
@@ -30,11 +24,6 @@ class MCDCObject(MCDCBase):
     ID: int
     compile_ID: int
 
-    def __init_subclass__(cls):
-        super().__init_subclass__()
-
-        cls.non_numba += ["compile_ID"]
-
     def __init__(self):
         self.ID = -1
         self.compile_ID = 0
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 35e0bd6fd..1f0f57832 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -109,6 +109,8 @@ def __init__(
         translation: Sequence[float] = [0.0, 0.0, 0.0],
         rotation: Sequence[float] = [0.0, 0.0, 0.0],
     ):
+        super().__init__()
+
         self.name = name or "(Unnamed cell)"
         self.region = region or Region("all", None, None)
         self.fill = fill
diff --git a/mcdc/object_/distribution.py b/mcdc/object_/distribution.py
index c27278591..2cd295986 100644
--- a/mcdc/object_/distribution.py
+++ b/mcdc/object_/distribution.py
@@ -68,6 +68,8 @@ class DistributionPMF(DistributionBase):
     cmf: NDArray[float64]
 
     def __init__(self, value: ArrayLike, pmf: ArrayLike) -> None:
+        super().__init__()
+
         self.value = np.asarray(value, dtype=float64)
         pmf_array = np.asarray(pmf, dtype=float64)
 
@@ -108,6 +110,8 @@ def __init__(
         pdf: ArrayLike | None = None,
         cdf: ArrayLike | None = None,
     ) -> None:
+        super().__init__()
+
         if (pdf is None) == (cdf is None):
             print_error("Exactly one of pdf or cdf must be provided.")
 
@@ -182,6 +186,8 @@ def __init__(
         pdf: ArrayLike | None = None,
         cdf: ArrayLike | None = None,
     ) -> None:
+        super().__init__()
+
         if (pdf is None) == (cdf is None):
             print_error("Exactly one of pdf or cdf must be provided.")
 
@@ -279,6 +285,8 @@ class DistributionLevelScattering(DistributionBase):
     C2: float
 
     def __init__(self, C1: float, C2: float) -> None:
+        super().__init__()
+
         self.C1 = C1
         self.C2 = C2
 
@@ -311,6 +319,8 @@ def __init__(
         temperature_interpolations: int | Sequence[int],
         interpolation_boundaries: Sequence[int] | None,
     ) -> None:
+        super().__init__()
+
         self.restriction_energy = restriction_energy
         self.nuclear_temperature = DataTable(
             nuclear_temperature_energy_grid,
@@ -355,6 +365,8 @@ def __init__(
         temperature_interpolations: int | Sequence[int],
         interpolation_boundaries: Sequence[int] | None,
     ) -> None:
+        super().__init__()
+
         self.restriction_energy = restriction_energy
         self.nuclear_temperature = DataTable(
             nuclear_temperature_energy_grid,
@@ -405,6 +417,8 @@ def __init__(
         precompound_factor: ArrayLike,
         angular_slope: ArrayLike,
     ) -> None:
+        super().__init__()
+
         self.energy = np.asarray(energy, dtype=float64)
         self.offset = np.asarray(offset, dtype=int64)
         self.energy_out = np.asarray(energy_out, dtype=float64)
@@ -463,6 +477,8 @@ def __init__(
         cosine: ArrayLike,
         cosine_pdf: ArrayLike,
     ) -> None:
+        super().__init__()
+
         self.energy = np.asarray(energy, dtype=float64)
         self.offset = np.asarray(offset, dtype=int64)
         self.energy_out = np.asarray(energy_out, dtype=float64)
@@ -544,6 +560,8 @@ def __init__(
         values: ArrayLike,
         probabilities: ArrayLike,
     ) -> None:
+        super().__init__()
+
         value_array = np.asarray(values, dtype=float64)
         probability_array = np.asarray(probabilities, dtype=float64)
 
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 77425dbc7..1d10032d3 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -28,10 +28,9 @@ class MaterialBase(MCDCPolymorphic):
     name: str
     fissionable: bool
 
-    def __init__(
-        self,
-        name: str,
-    ) -> None:
+    def __init__(self, name: str) -> None:
+        super().__init__()
+
         self.name = name or "(Unnamed material)"
         self.fissionable = False
 
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index 8cba7bfcd..6511a1016 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -26,10 +26,9 @@ class MeshBase(MCDCPolymorphic):
     Ny: int
     Nz: int
 
-    def __init__(
-        self,
-        name: str,
-    ) -> None:
+    def __init__(self, name: str) -> None:
+        super().__init__()
+
         self.name = name or "(Unnamed mesh)"
         self.N_bin = 0
 
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 8b1e90573..b565a685f 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -229,6 +229,8 @@ def __init__(
         #
         probability: float = 1.0,
     ):
+        super().__init__()
+
         self.name = name or "(Unnamed source)"
 
         # ==============================================================================
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 5bb112ba0..8031a0385 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -75,6 +75,8 @@ class Surface(MCDCObject):
     tallies: list[TallySurfaceCrossing]
 
     def __init__(self, type_, name, boundary_condition):
+        super().__init__()
+
         self.type = type_
         self.name = name or "(Unnamed surface)"
 
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index e14079b9c..9606b6ca8 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -149,6 +149,7 @@ def __init__(
         time: Sequence[float] | NoneType = None,
         spatial_shape: tuple[int, ...] | NoneType = None,
     ):
+        super().__init__()
 
         # Set name
         self.name = name or "(Unnamed tally)"
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index f43b5e00e..535997d8d 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -31,6 +31,8 @@ class Universe(MCDCObject):
     cells: list[Cell]
 
     def __init__(self, name: str = "", cells: list[Cell] = []):
+        super().__init__()
+
         self.name = name or "(Unnamed universe)"
         self.cells = cells
 
@@ -60,7 +62,8 @@ def __repr__(self):
 
 class Lattice(MCDCObject):
     # MC/DC framework metadata
-    label = "particle_bank"
+    label = "lattice"
+    non_numba = ["universes"]
 
     name: str
 
@@ -87,8 +90,7 @@ def __init__(
         z: tuple[float, float, int] | NoneType = None,
         universes: list[Universe] = [],
     ):
-        # MC/DC framework metadata
-        super().__init__("lattice", ["universes"])
+        super().__init__()
 
         self.name = name or "(Unnamed lattice)"
         self.universes = universes

From 5e8bc8c9803fb621f6e089ee87a6e712c50303d9 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 22 Jul 2026 13:31:15 +0700
Subject: [PATCH 025/202] running

---
 mcdc/code_factory/numba_objects_generator.py | 36 ++++----
 mcdc/code_factory/python_objects_compiler.py |  8 ++
 mcdc/main.py                                 |  2 +-
 mcdc/numba_types.py                          | 97 ++++++++++----------
 mcdc/object_/cell.py                         |  5 +-
 mcdc/object_/data.py                         |  4 +
 mcdc/object_/universe.py                     |  2 +-
 mcdc/output.py                               | 24 ++---
 mcdc/transport/data.py                       |  4 +-
 mcdc/transport/distribution.py               |  8 +-
 mcdc/transport/mesh/interface.py             | 16 ++--
 mcdc/transport/physics/electron/native.py    | 10 +-
 mcdc/transport/physics/neutron/native.py     | 32 +++----
 mcdc/transport/tally/score.py                |  6 +-
 14 files changed, 130 insertions(+), 124 deletions(-)

diff --git a/mcdc/code_factory/numba_objects_generator.py b/mcdc/code_factory/numba_objects_generator.py
index 97c82cf71..f64730e8d 100644
--- a/mcdc/code_factory/numba_objects_generator.py
+++ b/mcdc/code_factory/numba_objects_generator.py
@@ -26,7 +26,7 @@
 )
 from mcdc.object_.particle import Particle, ParticleBank, ParticleData
 from mcdc.object_.tally import Tally
-from mcdc.print_ import print_error
+from mcdc.print_ import print_error, print_structure
 from mcdc.util import flatten
 
 type_map = {
@@ -162,11 +162,6 @@ def generate_numba_objects(simulation):
 
             annotations[mcdc_class.label].update(new_annotations)
 
-        print(mcdc_class.label)
-        print(mcdc_class.__annotations__)
-        print(annotations[mcdc_class.label])
-        input()
-
     # Particle banks
     for name in bank_names:
         annotations[name] = {
@@ -187,6 +182,7 @@ def generate_numba_objects(simulation):
 
     # Temporary simulation object structure
     simulation_object_structure = []
+    included_classes = []
     for field in annotations["simulation"]:
         hint = annotations["simulation"][field]
         hint_origin = get_origin(hint)
@@ -194,9 +190,11 @@ def generate_numba_objects(simulation):
 
         if hint in all_classes:
             simulation_object_structure.append((field, hint))
+            included_classes.append(hint)
             continue
         if hint_origin == list and hint_args[0] in all_classes:
             simulation_object_structure.append((field, list, hint_args[0]))
+            included_classes.append(hint_args[0])
             continue
 
     # Set the structures and accessor targets
@@ -214,10 +212,10 @@ def generate_numba_objects(simulation):
         # Set parent and child ID and type if polymorphic
         if issubclass(class_, MCDCPolymorphic):
             if class_.__name__[-4:] == "Base" or class_.__name__ == "Tally":
-                structures[class_.label].append(("child_type", type_map[int]))
-                structures[class_.label].append(("child_ID", type_map[int]))
+                structures[class_.label].append(("sub_type", type_map[int]))
+                structures[class_.label].append(("sub_ID", type_map[int]))
             else:
-                structures[class_.label].append(("parent_ID", type_map[int]))
+                structures[class_.label].append(("base_ID", type_map[int]))
 
     # Add particle data to particle banks and add particle banks to the simulation
     for name in bank_names:
@@ -304,7 +302,7 @@ def generate_numba_objects(simulation):
                         record[f"N_{class_.label}"] = N
 
         # Singleton
-        elif item[1] in mcdc_classes and issubclass(item[1], ObjectSingleton):
+        elif item[1] in mcdc_classes and issubclass(item[1], MCDCBase):
             new_structure.append((field, into_dtype(structures[item[1].label])))
 
         else:
@@ -647,7 +645,7 @@ def set_object(
             ):
                 record[f"{attribute_name}_ID"] = attribute.ID
             else:
-                record[f"{attribute_name}_ID"] = attribute.child_ID
+                record[f"{attribute_name}_ID"] = attribute.sub_ID
 
         # List of Non-singleton objects
         elif type(attribute) == list:
@@ -675,7 +673,7 @@ def set_object(
                 else:
                     data["array"][
                         data["size"] : data["size"] + len(attribute_flatten)
-                    ] = [x.child_ID for x in attribute_flatten]
+                    ] = [x.sub_ID for x in attribute_flatten]
             data["size"] += len(attribute_flatten)
 
     # Complete for simulation object
@@ -692,12 +690,12 @@ def set_object(
             # Parent
             if class_ in polymorphic_bases:
                 record["ID"] = object_.ID
-                record["child_ID"] = object_.child_ID
-                record["child_type"] = object_.type
+                record["sub_ID"] = object_.sub_ID
+                record["sub_type"] = object_.sub_type
             # Child
             else:
-                record["ID"] = object_.child_ID
-                record["parent_ID"] = object_.ID
+                record["ID"] = object_.sub_ID
+                record["base_ID"] = object_.ID
 
     # Set tally bins
     if class_ == Tally:
@@ -716,10 +714,10 @@ def set_object(
         print_error(f"Missing structure keys in record for {class_.label}: {missing}")
 
     # Register the record
-    if isinstance(object_, ObjectSingleton):
-        records[class_.label] = record
-    elif isinstance(object_, MCDCObject):
+    if isinstance(object_, MCDCObject):
         records[class_.label].append(record)
+    elif isinstance(object_, MCDCBase):
+        records[class_.label] = record
 
 
 # =============================================================================
diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index 634f73b37..874ac1ca1 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -107,6 +107,14 @@ def register_object(object_: MCDCObject, simulation: Simulation) -> bool:
         )
     object_.compile_ID = simulation.compile_ID
 
+    # Assign name if needed
+    if hasattr(object_, "name") and object_.name.startswith("(Unnamed"):
+        if isinstance(object_, MCDCPolymorphic):
+            ID = object_.sub_ID
+        else:
+            ID = object_.ID
+        object_.name = object_.label + f"_{ID}"
+
     # Register to simulation (TODO: Resolve IDE error message)
     object_list.append(object_)
 
diff --git a/mcdc/main.py b/mcdc/main.py
index 9a5afc84b..27feac275 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -79,7 +79,7 @@ def run_simulation(simulationPy: Simulation):
     time_output_start = MPI.Wtime()
 
     # Generate hdf5 output file
-    output_module.generate_output(simulation, data)
+    output_module.generate_output(simulation, data, simulationPy)
 
     # TIMER: output
     time_output_end = MPI.Wtime()
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index 5b5646971..c523ca920 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -48,20 +48,20 @@
 
 cell = into_dtype([
     ('name', 'U32'),
-    ('fill_translated', bool),
-    ('fill_rotated', bool),
-    ('translation', float64, (3,)),
-    ('rotation', float64, (3,)),
     ('region_RPN_tokens_offset', int64),
     ('region_RPN_tokens_length', int64),
     ('N_surface', int64),
     ('surface_IDs_offset', int64),
+    ('fill_type', int64),
+    ('fill_ID', int64),
+    ('fill_translated', bool),
+    ('fill_rotated', bool),
+    ('translation', float64, (3,)),
+    ('rotation', float64, (3,)),
     ('N_collision_tally', int64),
     ('collision_tally_IDs_offset', int64),
     ('N_tracklength_tally', int64),
     ('tracklength_tally_IDs_offset', int64),
-    ('fill_type', int64),
-    ('fill_ID', int64),
     ('ID', int64),
 ])
 
@@ -85,8 +85,8 @@
     ('name', 'U32'),
     ('fissionable', bool),
     ('ID', int64),
-    ('child_type', int64),
-    ('child_ID', int64),
+    ('sub_type', int64),
+    ('sub_ID', int64),
 ])
 
 collision_tally = into_dtype([
@@ -99,7 +99,7 @@
     ('mesh_stride_y', int64),
     ('mesh_stride_x', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 tracklength_tally = into_dtype([
@@ -112,7 +112,7 @@
     ('mesh_stride_y', int64),
     ('mesh_stride_x', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 universe = into_dtype([
@@ -124,20 +124,20 @@
 
 data = into_dtype([
     ('ID', int64),
-    ('child_type', int64),
-    ('child_ID', int64),
+    ('sub_type', int64),
+    ('sub_ID', int64),
 ])
 
 none_data = into_dtype([
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 polynomial_data = into_dtype([
     ('coefficients_offset', int64),
     ('coefficients_length', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 table_data = into_dtype([
@@ -154,20 +154,20 @@
     ('aux_offset', int64),
     ('aux_length', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 distribution = into_dtype([
     ('ID', int64),
-    ('child_type', int64),
-    ('child_ID', int64),
+    ('sub_type', int64),
+    ('sub_ID', int64),
 ])
 
 evaporation_distribution = into_dtype([
     ('nuclear_temperature_ID', int64),
     ('restriction_energy', float64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 kalbach_mann_distribution = into_dtype([
@@ -186,21 +186,21 @@
     ('angular_slope_offset', int64),
     ('angular_slope_length', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 level_scattering_distribution = into_dtype([
     ('C1', float64),
     ('C2', float64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 maxwellian_distribution = into_dtype([
     ('nuclear_temperature_ID', int64),
     ('restriction_energy', float64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 multi_table_distribution = into_dtype([
@@ -209,18 +209,18 @@
     ('N_table', int64),
     ('table_IDs_offset', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 nbody_distribution = into_dtype([
     ('pdf_ID', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 none_distribution = into_dtype([
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 pmf_distribution = into_dtype([
@@ -231,13 +231,13 @@
     ('cmf_offset', int64),
     ('cmf_length', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 tabulated_distribution = into_dtype([
     ('pdf_ID', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 tabulated_energy_angle_distribution = into_dtype([
@@ -260,7 +260,7 @@
     ('cosine_cdf_offset', int64),
     ('cosine_cdf_length', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 electron_reaction = into_dtype([
@@ -270,14 +270,14 @@
     ('xs_offset_', int64),
     ('reference_frame', int64),
     ('ID', int64),
-    ('child_type', int64),
-    ('child_ID', int64),
+    ('sub_type', int64),
+    ('sub_ID', int64),
 ])
 
 electron_bremsstrahlung_reaction = into_dtype([
     ('eloss_ID', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 electron_elastic_scattering_reaction = into_dtype([
@@ -285,13 +285,13 @@
     ('xs_large_ID', int64),
     ('mu_ID', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 electron_excitation_reaction = into_dtype([
     ('eloss_ID', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 electron_ionization_reaction = into_dtype([
@@ -301,7 +301,7 @@
     ('N_subshell_product', int64),
     ('subshell_product_IDs_offset', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 element = into_dtype([
@@ -343,7 +343,7 @@
     ('element_densities_offset', int64),
     ('element_densities_length', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 multigroup_material = into_dtype([
@@ -378,7 +378,7 @@
     ('mgxs_chi_d_offset', int64),
     ('mgxs_chi_d_length', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 nuclide = into_dtype([
@@ -428,8 +428,8 @@
     ('Ny', int64),
     ('Nz', int64),
     ('ID', int64),
-    ('child_type', int64),
-    ('child_ID', int64),
+    ('sub_type', int64),
+    ('sub_ID', int64),
 ])
 
 structured_mesh = into_dtype([
@@ -440,7 +440,7 @@
     ('z_offset', int64),
     ('z_length', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 uniform_mesh = into_dtype([
@@ -454,7 +454,7 @@
     ('dz', float64),
     ('Nz', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 neutron_reaction = into_dtype([
@@ -465,19 +465,19 @@
     ('reference_frame', int64),
     ('q_value', float64),
     ('ID', int64),
-    ('child_type', int64),
-    ('child_ID', int64),
+    ('sub_type', int64),
+    ('sub_ID', int64),
 ])
 
 neutron_capture_reaction = into_dtype([
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 neutron_elastic_scattering_reaction = into_dtype([
     ('mu_table_ID', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 neutron_fission_reaction = into_dtype([
@@ -485,7 +485,7 @@
     ('mu_ID', int64),
     ('spectrum_ID', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 neutron_inelastic_scattering_reaction = into_dtype([
@@ -501,7 +501,7 @@
     ('N_energy_spectrum', int64),
     ('energy_spectrum_IDs_offset', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 collision_data = into_dtype([
@@ -665,7 +665,7 @@
     ('cell_filtered', bool),
     ('cell_filter_ID', int64),
     ('ID', int64),
-    ('parent_ID', int64),
+    ('base_ID', int64),
 ])
 
 tally = into_dtype([
@@ -697,8 +697,8 @@
     ('stride_energy', int64),
     ('stride_time', int64),
     ('ID', int64),
-    ('child_type', int64),
-    ('child_ID', int64),
+    ('sub_type', int64),
+    ('sub_ID', int64),
 ])
 
 gpu_meta = into_dtype([
@@ -844,7 +844,6 @@ def set_simulation(N: dict):
         ('bank_census', bank_census),
         ('bank_active', bank_active),
         ('name', 'U32'),
-        ('compile_ID', int64),
         ('idx_work', int64),
         ('idx_cycle', int64),
         ('idx_census', int64),
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 1f0f57832..bac77724a 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -39,10 +39,7 @@
 # ======================================================================================
 
 
-class Region(MCDCObject):
-    # MC/DC framework metadata
-    label = "region"
-
+class Region:
     type: str
     A: Surface | Region | NoneType
     B: Region | int | NoneType
diff --git a/mcdc/object_/data.py b/mcdc/object_/data.py
index fe72e06cc..4b96cfe75 100644
--- a/mcdc/object_/data.py
+++ b/mcdc/object_/data.py
@@ -74,6 +74,8 @@ def __init__(
         interpolation_boundaries: Sequence[int] | None = None,
         aux: NDArray[float64] | None = None,
     ) -> None:
+        super().__init__()
+
         # Set primary data
         self.x = np.asarray(x, dtype=float64)
         self.y = np.asarray(y, dtype=float64)
@@ -240,6 +242,8 @@ class DataPolynomial(DataBase):
     coefficients: NDArray[float64]
 
     def __init__(self, coefficients: NDArray[float64]) -> None:
+        super().__init__()
+
         self.coefficients = np.asarray(coefficients, dtype=float64)
 
         if self.coefficients.ndim != 1:
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index 535997d8d..b9c0ee0fd 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -25,7 +25,7 @@
 
 class Universe(MCDCObject):
     # MC/DC framework metadata
-    label = "particle_bank"
+    label = "universe"
 
     name: str
     cells: list[Cell]
diff --git a/mcdc/output.py b/mcdc/output.py
index a911b18cb..1cf52f5da 100644
--- a/mcdc/output.py
+++ b/mcdc/output.py
@@ -17,9 +17,7 @@
 # ======================================================================================
 
 
-def generate_output(mcdc, data):
-    from mcdc import simulation
-
+def generate_output(mcdc, data, simulationPy):
     if not mcdc["mpi_master"]:
         return
 
@@ -37,7 +35,7 @@ def generate_output(mcdc, data):
     file["version"] = importlib.metadata.version("mcdc")
 
     # Settings
-    create_object_dataset(file, "settings", simulation.settings)
+    create_object_dataset(file, "settings", simulationPy.settings)
 
     # No need to output tally if time census-based tally is used
     if mcdc["settings"]["use_census_based_tally"]:
@@ -50,7 +48,7 @@ def generate_output(mcdc, data):
     if mcdc["settings"]["neutron_eigenvalue_mode"]:
         N_cycle = mcdc["settings"]["N_cycle"]
         file.create_dataset(
-            "k_cycle", data=mcdc_get.simulation.k_cycle_chunk(0, N_cycle, mcdc, data)
+            "k_cycle", data=mcdc_get.simulationPy.k_cycle_chunk(0, N_cycle, mcdc, data)
         )
         file.create_dataset("k_mean", data=mcdc["k_avg_running"])
         file.create_dataset("k_sdev", data=mcdc["k_sdv_running"])
@@ -63,7 +61,9 @@ def generate_output(mcdc, data):
         if mcdc["settings"]["use_gyration_radius"]:
             file.create_dataset(
                 "gyration_radius",
-                data=mcdc_get.simulation.gyration_radius_chunk(0, N_cycle, mcdc, data),
+                data=mcdc_get.simulationPy.gyration_radius_chunk(
+                    0, N_cycle, mcdc, data
+                ),
             )
 
     # Save particle?
@@ -166,15 +166,15 @@ def create_tally_dataset(file, mcdc, data):
 
         # Mesh grid (TODO: Make mesh dataset in a separate group)
         mesh_filtered_tally = None
-        if tally["child_type"] == TALLY_TRACKLENGTH:
-            mesh_filtered_tally = mcdc["tracklength_tallies"][tally["child_ID"]]
-        elif tally["child_type"] == TALLY_COLLISION:
-            mesh_filtered_tally = mcdc["collision_tallies"][tally["child_ID"]]
+        if tally["sub_type"] == TALLY_TRACKLENGTH:
+            mesh_filtered_tally = mcdc["tracklength_tallies"][tally["sub_ID"]]
+        elif tally["sub_type"] == TALLY_COLLISION:
+            mesh_filtered_tally = mcdc["collision_tallies"][tally["sub_ID"]]
 
         if mesh_filtered_tally is not None and mesh_filtered_tally["mesh_filtered"]:
             mesh_base = mcdc["meshes"][mesh_filtered_tally["mesh_filter_ID"]]
-            mesh_type = mesh_base["child_type"]
-            mesh_ID = mesh_base["child_ID"]
+            mesh_type = mesh_base["sub_type"]
+            mesh_ID = mesh_base["sub_ID"]
             if mesh_type == MESH_UNIFORM:
                 mesh = mcdc["uniform_meshes"][mesh_ID]
                 x = np.linspace(
diff --git a/mcdc/transport/data.py b/mcdc/transport/data.py
index 84e8f63d2..abd9a205b 100644
--- a/mcdc/transport/data.py
+++ b/mcdc/transport/data.py
@@ -25,8 +25,8 @@
 
 @njit
 def evaluate_data(x, data_base, simulation, data):
-    data_type = data_base["child_type"]
-    ID = data_base["child_ID"]
+    data_type = data_base["sub_type"]
+    ID = data_base["sub_ID"]
     if data_type == DATA_TABLE:
         table = simulation["table_data"][ID]
         return evaluate_table(x, table, data)
diff --git a/mcdc/transport/distribution.py b/mcdc/transport/distribution.py
index 7c36cdd51..230f7e95e 100644
--- a/mcdc/transport/distribution.py
+++ b/mcdc/transport/distribution.py
@@ -44,8 +44,8 @@ def sample_distribution_with_scale(E, distribution, rng_state, simulation, data)
 
 @njit
 def _sample_distribution(E, distribution, rng_state, simulation, data, scale):
-    distribution_type = distribution["child_type"]
-    ID = distribution["child_ID"]
+    distribution_type = distribution["sub_type"]
+    ID = distribution["sub_ID"]
 
     if distribution_type == DISTRIBUTION_TABULATED:
         table = simulation["tabulated_distributions"][ID]
@@ -92,8 +92,8 @@ def sample_correlated_distribution_with_scale(
 def _sample_correlated_distribution(
     E, distribution, rng_state, simulation, data, scale
 ):
-    distribution_type = distribution["child_type"]
-    ID = distribution["child_ID"]
+    distribution_type = distribution["sub_type"]
+    ID = distribution["sub_ID"]
 
     if distribution_type == DISTRIBUTION_KALBACH_MANN:
         kalbach_mann = simulation["kalbach_mann_distributions"][ID]
diff --git a/mcdc/transport/mesh/interface.py b/mcdc/transport/mesh/interface.py
index 2e4fda69f..f395ae35c 100644
--- a/mcdc/transport/mesh/interface.py
+++ b/mcdc/transport/mesh/interface.py
@@ -8,8 +8,8 @@
 
 @njit
 def get_indices(particle_container, mesh_base, simulation, data):
-    mesh_type = mesh_base["child_type"]
-    mesh_ID = mesh_base["child_ID"]
+    mesh_type = mesh_base["sub_type"]
+    mesh_ID = mesh_base["sub_ID"]
 
     if mesh_type == MESH_UNIFORM:
         mesh = simulation["uniform_meshes"][mesh_ID]
@@ -23,8 +23,8 @@ def get_indices(particle_container, mesh_base, simulation, data):
 
 @njit
 def get_x(index, mesh_base, simulation, data):
-    mesh_type = mesh_base["child_type"]
-    mesh_ID = mesh_base["child_ID"]
+    mesh_type = mesh_base["sub_type"]
+    mesh_ID = mesh_base["sub_ID"]
 
     if mesh_type == MESH_UNIFORM:
         mesh = simulation["uniform_meshes"][mesh_ID]
@@ -37,8 +37,8 @@ def get_x(index, mesh_base, simulation, data):
 
 @njit
 def get_y(index, mesh_base, simulation, data):
-    mesh_type = mesh_base["child_type"]
-    mesh_ID = mesh_base["child_ID"]
+    mesh_type = mesh_base["sub_type"]
+    mesh_ID = mesh_base["sub_ID"]
 
     if mesh_type == MESH_UNIFORM:
         mesh = simulation["uniform_meshes"][mesh_ID]
@@ -51,8 +51,8 @@ def get_y(index, mesh_base, simulation, data):
 
 @njit
 def get_z(index, mesh_base, simulation, data):
-    mesh_type = mesh_base["child_type"]
-    mesh_ID = mesh_base["child_ID"]
+    mesh_type = mesh_base["sub_type"]
+    mesh_ID = mesh_base["sub_ID"]
 
     if mesh_type == MESH_UNIFORM:
         mesh = simulation["uniform_meshes"][mesh_ID]
diff --git a/mcdc/transport/physics/electron/native.py b/mcdc/transport/physics/electron/native.py
index f975865a2..2865d4cc7 100644
--- a/mcdc/transport/physics/electron/native.py
+++ b/mcdc/transport/physics/electron/native.py
@@ -173,7 +173,7 @@ def collision(particle_container, collision_data_container, program, data):
                 mcdc_get.element.electron_ionization_reaction_IDs(i, element, data)
             )
             reaction = simulation["electron_ionization_reactions"][reaction_ID]
-            reaction_base_ID = reaction["parent_ID"]
+            reaction_base_ID = reaction["base_ID"]
             reaction_base = simulation["electron_reactions"][reaction_base_ID]
             total += reaction_micro_xs(E, reaction_base, element, data)
 
@@ -199,7 +199,7 @@ def collision(particle_container, collision_data_container, program, data):
                 )
             )
             reaction = simulation["electron_elastic_scattering_reactions"][reaction_ID]
-            reaction_base_ID = reaction["parent_ID"]
+            reaction_base_ID = reaction["base_ID"]
             reaction_base = simulation["electron_reactions"][reaction_base_ID]
             total += reaction_micro_xs(E, reaction_base, element, data)
 
@@ -218,7 +218,7 @@ def collision(particle_container, collision_data_container, program, data):
                 mcdc_get.element.electron_bremsstrahlung_reaction_IDs(i, element, data)
             )
             reaction = simulation["electron_bremsstrahlung_reactions"][reaction_ID]
-            reaction_base_ID = reaction["parent_ID"]
+            reaction_base_ID = reaction["base_ID"]
             reaction_base = simulation["electron_reactions"][reaction_base_ID]
             total += reaction_micro_xs(E, reaction_base, element, data)
 
@@ -241,7 +241,7 @@ def collision(particle_container, collision_data_container, program, data):
                 mcdc_get.element.electron_excitation_reaction_IDs(i, element, data)
             )
             reaction = simulation["electron_excitation_reactions"][reaction_ID]
-            reaction_base_ID = reaction["parent_ID"]
+            reaction_base_ID = reaction["base_ID"]
             reaction_base = simulation["electron_reactions"][reaction_base_ID]
             total += reaction_micro_xs(E, reaction_base, element, data)
 
@@ -272,7 +272,7 @@ def elastic_scattering(reaction, particle_container, element, simulation, data):
     # Total elastic xs
     # -------------------------------------------------------------------------
 
-    reaction_base_ID = int(reaction["parent_ID"])
+    reaction_base_ID = int(reaction["base_ID"])
     reaction_base = simulation["electron_reactions"][reaction_base_ID]
     xs_total = reaction_micro_xs(E, reaction_base, element, data)
 
diff --git a/mcdc/transport/physics/neutron/native.py b/mcdc/transport/physics/neutron/native.py
index f1d53bfae..c378dd745 100644
--- a/mcdc/transport/physics/neutron/native.py
+++ b/mcdc/transport/physics/neutron/native.py
@@ -172,7 +172,7 @@ def neutron_production_xs(reaction_type, particle_container, simulation, data):
 def _neutron_inelastic_scattering_production_xs(particle_container, simulation, data):
     particle = particle_container[0]
     material_base = simulation["materials"][particle["material_ID"]]
-    material = simulation["native_materials"][material_base["child_ID"]]
+    material = simulation["native_materials"][material_base["sub_ID"]]
 
     total = 0.0
     for i in range(material["N_nuclide"]):
@@ -189,7 +189,7 @@ def _neutron_inelastic_scattering_production_xs(particle_container, simulation,
                 )
             )
             reaction = simulation["neutron_inelastic_scattering_reactions"][reaction_ID]
-            reaction_base = simulation["neutron_reactions"][reaction["parent_ID"]]
+            reaction_base = simulation["neutron_reactions"][reaction["base_ID"]]
 
             xs = reaction_micro_xs(E, reaction_base, nuclide, data)
             nu = reaction["multiplicity"]
@@ -202,7 +202,7 @@ def _neutron_inelastic_scattering_production_xs(particle_container, simulation,
 def _neutron_fission_production_xs(particle_container, simulation, data):
     particle = particle_container[0]
     material_base = simulation["materials"][particle["material_ID"]]
-    material = simulation["native_materials"][material_base["child_ID"]]
+    material = simulation["native_materials"][material_base["sub_ID"]]
 
     if not material_base["fissionable"]:
         return 0.0
@@ -222,7 +222,7 @@ def _neutron_fission_production_xs(particle_container, simulation, data):
                 mcdc_get.nuclide.neutron_fission_reaction_IDs(j, nuclide, data)
             )
             reaction = simulation["neutron_fission_reactions"][reaction_ID]
-            reaction_base = simulation["neutron_reactions"][reaction["parent_ID"]]
+            reaction_base = simulation["neutron_reactions"][reaction["base_ID"]]
 
             xs = reaction_micro_xs(E, reaction_base, nuclide, data)
             nu_p = neutron_fission_prompt_multiplicity(E, nuclide, simulation, data)
@@ -277,7 +277,7 @@ def collision(particle_container, collision_data_container, program, data):
                     mcdc_get.nuclide.neutron_capture_reaction_IDs(j, nuclide, data)
                 )
                 reaction = simulation["neutron_capture_reactions"][reaction_ID]
-                reaction_base_ID = reaction["parent_ID"]
+                reaction_base_ID = reaction["base_ID"]
                 reaction_base = simulation["neutron_reactions"][reaction_base_ID]
                 xs = reaction_micro_xs(E, reaction_base, nuclide, data)
                 Sigma_rx = nuclide_density * xs
@@ -336,7 +336,7 @@ def collision(particle_container, collision_data_container, program, data):
                 )
             )
             reaction = simulation["neutron_elastic_scattering_reactions"][reaction_ID]
-            reaction_base_ID = reaction["parent_ID"]
+            reaction_base_ID = reaction["base_ID"]
             reaction_base = simulation["neutron_reactions"][reaction_base_ID]
             total += reaction_micro_xs(E, reaction_base, nuclide, data)
 
@@ -364,7 +364,7 @@ def collision(particle_container, collision_data_container, program, data):
                     mcdc_get.nuclide.neutron_capture_reaction_IDs(i, nuclide, data)
                 )
                 reaction = simulation["neutron_capture_reactions"][reaction_ID]
-                reaction_base_ID = reaction["parent_ID"]
+                reaction_base_ID = reaction["base_ID"]
                 reaction_base = simulation["neutron_reactions"][reaction_base_ID]
                 xs = reaction_micro_xs(E, reaction_base, nuclide, data)
                 total += xs
@@ -393,7 +393,7 @@ def collision(particle_container, collision_data_container, program, data):
                 )
             )
             reaction = simulation["neutron_inelastic_scattering_reactions"][reaction_ID]
-            reaction_base_ID = reaction["parent_ID"]
+            reaction_base_ID = reaction["base_ID"]
             reaction_base = simulation["neutron_reactions"][reaction_base_ID]
             xs = reaction_micro_xs(E, reaction_base, nuclide, data)
             total += xs
@@ -420,7 +420,7 @@ def collision(particle_container, collision_data_container, program, data):
                 mcdc_get.nuclide.neutron_fission_reaction_IDs(i, nuclide, data)
             )
             reaction = simulation["neutron_fission_reactions"][reaction_ID]
-            reaction_base_ID = reaction["parent_ID"]
+            reaction_base_ID = reaction["base_ID"]
             reaction_base = simulation["neutron_reactions"][reaction_base_ID]
             total += reaction_micro_xs(E, reaction_base, nuclide, data)
 
@@ -449,7 +449,7 @@ def capture(
     particle = particle_container[0]
     collision_data = collision_data_container[0]
 
-    reaction_base_ID = reaction["parent_ID"]
+    reaction_base_ID = reaction["base_ID"]
     reaction_base = simulation["neutron_reactions"][reaction_base_ID]
 
     # Terminate the particle
@@ -619,7 +619,7 @@ def inelastic_scattering(
     particle = particle_container[0]
     collision_data = collision_data_container[0]
 
-    reaction_base_ID = reaction["parent_ID"]
+    reaction_base_ID = reaction["base_ID"]
     reaction_base = simulation["neutron_reactions"][reaction_base_ID]
 
     # Particle attributes
@@ -661,7 +661,7 @@ def inelastic_scattering(
         elif angle_type == ANGLE_DISTRIBUTED:
             distribution_base = simulation["distributions"][reaction["mu_ID"]]
             multi_table = simulation["multi_table_distributions"][
-                distribution_base["child_ID"]
+                distribution_base["sub_ID"]
             ]
             mu = sample_multi_table(
                 E, particle_container_new, multi_table, simulation, data
@@ -720,7 +720,7 @@ def inelastic_scattering(
         # Frame transformation
         # ==============================================================================
 
-        reaction_base = simulation["neutron_reactions"][int(reaction["parent_ID"])]
+        reaction_base = simulation["neutron_reactions"][int(reaction["base_ID"])]
         reference_frame = reaction_base["reference_frame"]
         if reference_frame == REFERENCE_FRAME_COM:
             A = nuclide["atomic_weight_ratio"]
@@ -774,7 +774,7 @@ def fission(
 
     settings = simulation["settings"]
 
-    reaction_base_ID = reaction["parent_ID"]
+    reaction_base_ID = reaction["base_ID"]
     reaction_base = simulation["neutron_reactions"][reaction_base_ID]
 
     # Particle properties
@@ -855,7 +855,7 @@ def fission(
             elif angle_type == ANGLE_DISTRIBUTED:
                 distribution_base = simulation["distributions"][reaction["mu_ID"]]
                 multi_table = simulation["multi_table_distributions"][
-                    distribution_base["child_ID"]
+                    distribution_base["sub_ID"]
                 ]
                 mu = sample_multi_table(
                     E, particle_container_new, multi_table, simulation, data
@@ -881,7 +881,7 @@ def fission(
                 )
 
             # Frame transformation
-            reaction_base = simulation["neutron_reactions"][int(reaction["parent_ID"])]
+            reaction_base = simulation["neutron_reactions"][int(reaction["base_ID"])]
             reference_frame = reaction_base["reference_frame"]
             if reference_frame == REFERENCE_FRAME_COM:
                 A = nuclide["atomic_weight_ratio"]
diff --git a/mcdc/transport/tally/score.py b/mcdc/transport/tally/score.py
index fe2fbdee4..d8ff8c9a2 100644
--- a/mcdc/transport/tally/score.py
+++ b/mcdc/transport/tally/score.py
@@ -46,7 +46,7 @@ def surface_crossing_tally(
     data,
 ):
     particle = particle_container[0]
-    tally_base = simulation["tallies"][tally["parent_ID"]]
+    tally_base = simulation["tallies"][tally["base_ID"]]
 
     # Get filter indices
     MG_mode = simulation["settings"]["neutron_multigroup_mode"]
@@ -128,7 +128,7 @@ def collision_tally(
 ):
     particle = particle_container[0]
     collision_data = collision_data_container[0]
-    tally_base = simulation["tallies"][tally["parent_ID"]]
+    tally_base = simulation["tallies"][tally["base_ID"]]
 
     # Get filter indices
     MG_mode = simulation["settings"]["neutron_multigroup_mode"]
@@ -184,7 +184,7 @@ def collision_tally(
 @njit
 def tracklength_tally(particle_container, distance, tally, simulation, data):
     particle = particle_container[0]
-    tally_base = simulation["tallies"][tally["parent_ID"]]
+    tally_base = simulation["tallies"][tally["base_ID"]]
 
     # Get filter indices
     MG_mode = simulation["settings"]["neutron_multigroup_mode"]

From 991b77e1ed058f70a230f63a7ed7941a21568094 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 22 Jul 2026 13:41:25 +0700
Subject: [PATCH 026/202] edit input

---
 test/regression/azurv1/input.py | 37 +++++++++++++++++++++------------
 1 file changed, 24 insertions(+), 13 deletions(-)

diff --git a/test/regression/azurv1/input.py b/test/regression/azurv1/input.py
index 80eb28d39..e3a229449 100644
--- a/test/regression/azurv1/input.py
+++ b/test/regression/azurv1/input.py
@@ -1,14 +1,17 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("AZURV1")
+
 # ======================================================================================
-# Set model
+# Set simulation model
 # ======================================================================================
 # Infinite medium with isotropic plane surface at the center
 # Based on Ganapol LA-UR-01-1854 (AZURV1 benchmark)
 # Effective scattering ratio c = 1.1
 
-# Set materials
+# Materials
 m = mcdc.MaterialMG(
     capture=np.array([1.0 / 3.0]),
     scatter=np.array([[1.0 / 3.0]]),
@@ -16,36 +19,44 @@
     nu_p=np.array([2.3]),
 )
 
-# Set surfaces
+# Surfaces
 s1 = mcdc.Surface.PlaneX(x=-1e10, boundary_condition="reflective")
 s2 = mcdc.Surface.PlaneX(x=1e10, boundary_condition="reflective")
 
-# Set cells
-mcdc.Cell(region=+s1 & -s2, fill=m)
+# Cells
+cell = mcdc.Cell(region=+s1 & -s2, fill=m)
+
+# Set model
+simulation.set_model([cell])
 
 # ======================================================================================
-# Set source
+# Set simulation sources
 # ======================================================================================
 # Isotropic pulse at x=t=0
 
-mcdc.Source(
+source = mcdc.Source(
     position=[0.0, 0.0, 0.0],
     isotropic=True,
     energy_group=0,
     time=0.0,
 )
+simulation.set_sources([source])
 
 # ======================================================================================
-# Set tallies, settings, and run MC/DC
+# Set simulation tallies
 # ======================================================================================
 
-# Tallies
 mesh = mcdc.MeshStructured(x=np.linspace(-20.5, 20.5, 202))
-mcdc.Tally(mesh=mesh, scores=["flux"], time=np.linspace(0.0, 20.0, 21))
+tally = mcdc.Tally(mesh=mesh, scores=["flux"], time=np.linspace(0.0, 20.0, 21))
+simulation.set_tallies([tally])
+
+# ======================================================================================
+# Simulation settings and run simulation
+# ======================================================================================
 
 # Settings
-mcdc.settings.N_particle = 60
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 60
+simulation.settings.N_batch = 2
 
 # Run
-mcdc.run()
+simulation.run()

From c608c20f25a98ebbfd5b26cbe6807338e5d2111d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 22 Jul 2026 13:43:05 +0700
Subject: [PATCH 027/202] fix bug

---
 mcdc/object_/tally.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 9606b6ca8..98cd2acc2 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -627,7 +627,7 @@ def _compile_into_simulation(self, simulation) -> bool:
         # Attach to all cells if cell filter is not specified
         if not self.cell:
             for cell in simulation.cells:
-                cell.collision_tallies.append(self)
+                cell.tracklength_tallies.append(self)
 
         return True
 

From cc48f047d03ea873984d0583b7dc8f487c5f9db0 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 22 Jul 2026 17:06:52 +0700
Subject: [PATCH 028/202] fix tally filter bug

---
 mcdc/object_/tally.py | 90 ++++++++++++++++++++++++++-----------------
 1 file changed, 55 insertions(+), 35 deletions(-)

diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 98cd2acc2..37c7ce6b0 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -371,21 +371,19 @@ def __init__(
         self.cell_filtered = False
         self.cell_filter_ID = -1
 
-        # Surface filter
-        if surface is not None:
+        # Set surface filter
+        if surface:
             self.surface_filtered = True
-            self.surface_filter_ID = surface.ID
 
-            # Attach to the surface
+            # Attach to surface
             surface.tallies.append(self)
 
-        # Cell filter
-        if cell is not None:
+        # Set cell filter
+        if cell:
             self.cell_filtered = True
-            self.cell_filter_ID = cell.ID
 
-            # Attach to all bounding surfaces of the cell if surface filter is not specified
-            if surface is None:
+            # Attach to all bounding surfaces if surface filter is not specified
+            if not self.surface_filtered:
                 for boundary_surface in cell.surfaces:
                     boundary_surface.tallies.append(self)
 
@@ -394,6 +392,18 @@ def _compile_into_simulation(self, simulation) -> bool:
         if not super()._compile_into_simulation(simulation):
             return False
 
+        # Set surface ID
+        surface = self.surface
+        if surface:
+            surface._compile_into_simulation(simulation)
+            self.surface_filter_ID = surface.ID
+
+        # Set cell ID
+        cell = self.cell
+        if cell:
+            cell._compile_into_simulation(simulation)
+            self.cell_filter_ID = cell.ID
+
         return True
 
     def __repr__(self):
@@ -477,24 +487,17 @@ def __init__(
         self.mesh_stride_y = -1
         self.mesh_stride_x = -1
 
-        # Cell filter
-        if cell is not None:
+        # Set cell filter
+        if cell:
             self.cell_filtered = True
-            self.cell_filter_ID = cell.ID
 
-            # Attach to the cell
+            # Attach to cell
             cell.collision_tallies.append(self)
 
         # Mesh filter
-        if mesh is not None:
+        if mesh:
             self.mesh_filtered = True
-            self.mesh_filter_ID = mesh.ID
-
-            # Mesh type
-            if isinstance(mesh, MeshStructured):
-                self.mesh_filter_type = MESH_STRUCTURED
-            elif isinstance(mesh, MeshUniform):
-                self.mesh_filter_type = MESH_UNIFORM
+            self.mesh_filter_type = mesh.sub_type
 
             # Mesh strides
             N_score = len(self.scores)
@@ -507,8 +510,20 @@ def _compile_into_simulation(self, simulation) -> bool:
         if not super()._compile_into_simulation(simulation):
             return False
 
+        # Set cell ID
+        cell = self.cell
+        if cell:
+            cell._compile_into_simulation(simulation)
+            self.cell_filter_ID = cell.ID
+
+        # Set mesh ID
+        mesh = self.mesh
+        if mesh:
+            mesh._compile_into_simulation(simulation)
+            self.mesh_filter_ID = mesh.sub_ID
+
         # Attach to all cells if cell filter is not specified
-        if not self.cell:
+        if not self.cell_filtered:
             for cell in simulation.cells:
                 cell.collision_tallies.append(self)
 
@@ -594,24 +609,17 @@ def __init__(
         self.mesh_stride_y = -1
         self.mesh_stride_x = -1
 
-        # Cell filter
-        if cell is not None:
+        # Set cell filter
+        if cell:
             self.cell_filtered = True
-            self.cell_filter_ID = cell.ID
 
-            # Attach to the cell
+            # Attach to cell
             cell.tracklength_tallies.append(self)
 
         # Mesh filter
-        if mesh is not None:
+        if mesh:
             self.mesh_filtered = True
-            self.mesh_filter_ID = mesh.ID
-
-            # Mesh type
-            if isinstance(mesh, MeshStructured):
-                self.mesh_filter_type = MESH_STRUCTURED
-            elif isinstance(mesh, MeshUniform):
-                self.mesh_filter_type = MESH_UNIFORM
+            self.mesh_filter_type = mesh.sub_type
 
             # Mesh strides
             N_score = len(self.scores)
@@ -624,8 +632,20 @@ def _compile_into_simulation(self, simulation) -> bool:
         if not super()._compile_into_simulation(simulation):
             return False
 
+        # Set cell ID
+        cell = self.cell
+        if cell:
+            cell._compile_into_simulation(simulation)
+            self.cell_filter_ID = cell.ID
+
+        # Set mesh ID
+        mesh = self.mesh
+        if mesh:
+            mesh._compile_into_simulation(simulation)
+            self.mesh_filter_ID = mesh.sub_ID
+
         # Attach to all cells if cell filter is not specified
-        if not self.cell:
+        if not self.cell_filtered:
             for cell in simulation.cells:
                 cell.tracklength_tallies.append(self)
 

From 83020b9c2052f862928cf14bd235b3d904121efc Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 22 Jul 2026 18:17:51 +0700
Subject: [PATCH 029/202] relabel mesh_base consistently

---
 mcdc/transport/technique.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/mcdc/transport/technique.py b/mcdc/transport/technique.py
index 5de637998..cbec2f1bb 100644
--- a/mcdc/transport/technique.py
+++ b/mcdc/transport/technique.py
@@ -157,8 +157,8 @@ def get_ww_indices(particle_container, ww_obj, simulation, data):
     ie = util.find_bin(energy, energy_bounds)
 
     # get spatial index
-    mesh = simulation["meshes"][ww_obj["mesh_ID"]]
-    idx, idy, idz = get_mesh_indices(particle_container, mesh, simulation, data)
+    mesh_base = simulation["meshes"][ww_obj["mesh_ID"]]
+    idx, idy, idz = get_mesh_indices(particle_container, mesh_base, simulation, data)
 
     return (ie, idx, idy, idz)
 

From 980f8310286ebb71fa9964cd373cacafe10baea3 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 25 Jul 2026 11:08:40 +0700
Subject: [PATCH 030/202] working numba object generator

---
 mcdc/code_factory/numba_objects_generator.py | 22 ++++----------------
 mcdc/mcdc_get/surface.py                     | 20 +++++++++---------
 mcdc/mcdc_set/surface.py                     | 20 +++++++++---------
 mcdc/numba_types.py                          |  4 ++--
 mcdc/object_/surface.py                      | 10 ++++-----
 mcdc/object_/tally.py                        |  4 ++--
 mcdc/transport/simulation.py                 |  2 +-
 7 files changed, 34 insertions(+), 48 deletions(-)

diff --git a/mcdc/code_factory/numba_objects_generator.py b/mcdc/code_factory/numba_objects_generator.py
index f64730e8d..73f76748e 100644
--- a/mcdc/code_factory/numba_objects_generator.py
+++ b/mcdc/code_factory/numba_objects_generator.py
@@ -639,13 +639,7 @@ def set_object(
 
         # Non-singleton object
         elif isinstance(attribute, MCDCObject):
-            if (
-                not isinstance(attribute, MCDCPolymorphic)
-                or annotation[attribute_name] in polymorphic_bases
-            ):
-                record[f"{attribute_name}_ID"] = attribute.ID
-            else:
-                record[f"{attribute_name}_ID"] = attribute.sub_ID
+            record[f"{attribute_name}_ID"] = attribute.ID
 
         # List of Non-singleton objects
         elif type(attribute) == list:
@@ -663,17 +657,9 @@ def set_object(
             record[f"N_{singular_name}"] = len(attribute_flatten)
             record[f"{singular_name}_IDs_offset"] = data["size"]
             if set_data:
-                if (
-                    not issubclass(inner_type, MCDCPolymorphic)
-                    or inner_type in polymorphic_bases
-                ):
-                    data["array"][
-                        data["size"] : data["size"] + len(attribute_flatten)
-                    ] = [x.ID for x in attribute_flatten]
-                else:
-                    data["array"][
-                        data["size"] : data["size"] + len(attribute_flatten)
-                    ] = [x.sub_ID for x in attribute_flatten]
+                data["array"][data["size"] : data["size"] + len(attribute_flatten)] = [
+                    x.ID for x in attribute_flatten
+                ]
             data["size"] += len(attribute_flatten)
 
     # Complete for simulation object
diff --git a/mcdc/mcdc_get/surface.py b/mcdc/mcdc_get/surface.py
index 4a0230d76..68cb8e2a5 100644
--- a/mcdc/mcdc_get/surface.py
+++ b/mcdc/mcdc_get/surface.py
@@ -108,29 +108,29 @@ def move_translations_chunk(start, length, surface, data):
 
 
 @njit
-def tally_IDs(index, surface, data):
-    offset = surface["tally_IDs_offset"]
+def surface_crossing_tally_IDs(index, surface, data):
+    offset = surface["surface_crossing_tally_IDs_offset"]
     return data[offset + index]
 
 
 @njit
-def tally_IDs_all(surface, data):
-    start = surface["tally_IDs_offset"]
-    size = surface["N_tally"]
+def surface_crossing_tally_IDs_all(surface, data):
+    start = surface["surface_crossing_tally_IDs_offset"]
+    size = surface["N_surface_crossing_tally"]
     end = start + size
     return data[start:end]
 
 
 @njit
-def tally_IDs_last(surface, data):
-    start = surface["tally_IDs_offset"]
-    size = surface["N_tally"]
+def surface_crossing_tally_IDs_last(surface, data):
+    start = surface["surface_crossing_tally_IDs_offset"]
+    size = surface["N_surface_crossing_tally"]
     end = start + size
     return data[end - 1]
 
 
 @njit
-def tally_IDs_chunk(start, length, surface, data):
-    start += surface["tally_IDs_offset"]
+def surface_crossing_tally_IDs_chunk(start, length, surface, data):
+    start += surface["surface_crossing_tally_IDs_offset"]
     end = start + length
     return data[start:end]
diff --git a/mcdc/mcdc_set/surface.py b/mcdc/mcdc_set/surface.py
index 5ade2f533..ca594a39f 100644
--- a/mcdc/mcdc_set/surface.py
+++ b/mcdc/mcdc_set/surface.py
@@ -108,29 +108,29 @@ def move_translations_chunk(start, length, surface, data, value):
 
 
 @njit
-def tally_IDs(index, surface, data, value):
-    offset = surface["tally_IDs_offset"]
+def surface_crossing_tally_IDs(index, surface, data, value):
+    offset = surface["surface_crossing_tally_IDs_offset"]
     data[offset + index] = value
 
 
 @njit
-def tally_IDs_all(surface, data, value):
-    start = surface["tally_IDs_offset"]
-    size = surface["N_tally"]
+def surface_crossing_tally_IDs_all(surface, data, value):
+    start = surface["surface_crossing_tally_IDs_offset"]
+    size = surface["N_surface_crossing_tally"]
     end = start + size
     data[start:end] = value
 
 
 @njit
-def tally_IDs_last(surface, data, value):
-    start = surface["tally_IDs_offset"]
-    size = surface["N_tally"]
+def surface_crossing_tally_IDs_last(surface, data, value):
+    start = surface["surface_crossing_tally_IDs_offset"]
+    size = surface["N_surface_crossing_tally"]
     end = start + size
     data[end - 1] = value
 
 
 @njit
-def tally_IDs_chunk(start, length, surface, data, value):
-    start += surface["tally_IDs_offset"]
+def surface_crossing_tally_IDs_chunk(start, length, surface, data, value):
+    start += surface["surface_crossing_tally_IDs_offset"]
     end = start + length
     data[start:end] = value
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index c523ca920..5ee16a2c4 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -654,8 +654,8 @@
     ('move_time_grid_length', int64),
     ('move_translations_offset', int64),
     ('move_translations_length', int64),
-    ('N_tally', int64),
-    ('tally_IDs_offset', int64),
+    ('N_surface_crossing_tally', int64),
+    ('surface_crossing_tally_IDs_offset', int64),
     ('ID', int64),
 ])
 
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 8031a0385..7d922f240 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -72,7 +72,7 @@ class Surface(MCDCObject):
     move_durations: Annotated[NDArray[float64], ("N_move",)]
     move_time_grid: Annotated[NDArray[float64], ("N_move_grid",)]
     move_translations: Annotated[NDArray[float64], ("N_move_grid", 3)]
-    tallies: list[TallySurfaceCrossing]
+    surface_crossing_tallies: list[TallySurfaceCrossing]
 
     def __init__(self, type_, name, boundary_condition):
         super().__init__()
@@ -123,8 +123,8 @@ def __init__(self, type_, name, boundary_condition):
         self.move_time_grid = np.array([0.0, INF])
         self.move_translations = np.zeros((2, 3))
 
-        # Surface tallies
-        self.tallies = []
+        # Surface-crossing tallies
+        self.surface_crossing_tallies = []
 
     def _compile_into_simulation(self, simulation) -> bool:
         # Already compiled?
@@ -222,8 +222,8 @@ def __repr__(self):
             text += f"  - A, B, C: {self.A}, {self.B}, {self.C}\n"
             text += f"  - R: {self.R} cm\n"
             text += f"  - r: {self.r} cm\n"
-        if len(self.tallies) > 0:
-            text += f"  - Tallies: {[x.ID for x in self.tallies]}\n"
+        if len(self.surface_crossing_tallies) > 0:
+            text += f"  - Surface-crossing tallies: {[x.ID for x in self.surface_crossing_tallies]}\n"
 
         return text
 
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 37c7ce6b0..88a5439d1 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -376,7 +376,7 @@ def __init__(
             self.surface_filtered = True
 
             # Attach to surface
-            surface.tallies.append(self)
+            surface.surface_crossing_tallies.append(self)
 
         # Set cell filter
         if cell:
@@ -385,7 +385,7 @@ def __init__(
             # Attach to all bounding surfaces if surface filter is not specified
             if not self.surface_filtered:
                 for boundary_surface in cell.surfaces:
-                    boundary_surface.tallies.append(self)
+                    boundary_surface.surface_crossing_tallies.append(self)
 
     def _compile_into_simulation(self, simulation) -> bool:
         # Already compiled?
diff --git a/mcdc/transport/simulation.py b/mcdc/transport/simulation.py
index aca16d88f..1232c73bd 100644
--- a/mcdc/transport/simulation.py
+++ b/mcdc/transport/simulation.py
@@ -462,7 +462,7 @@ def surface_crossing(P_arr, simulation, data):
 
     # Score tally
     for i in range(surface["N_tally"]):
-        tally_ID = int(mcdc_get.surface.tally_IDs(i, surface, data))
+        tally_ID = int(mcdc_get.surface.surface_crossing_tally_IDs(i, surface, data))
         tally = simulation["surface_crossing_tallies"][tally_ID]
         tally_module.score.surface_crossing_tally(
             P_arr, surface, tally, simulation, data

From 519d55d051e73817ef372eedfff3930b6b094f2f Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 25 Jul 2026 11:33:55 +0700
Subject: [PATCH 031/202] add verbose option in pytest workflow

---
 .github/workflows/regression_test-gpu.yml | 2 +-
 .github/workflows/regression_test.yml     | 8 ++++----
 .github/workflows/unit_test.yml           | 2 +-
 3 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/regression_test-gpu.yml b/.github/workflows/regression_test-gpu.yml
index 4ffa831bf..6ba64f64b 100644
--- a/.github/workflows/regression_test-gpu.yml
+++ b/.github/workflows/regression_test-gpu.yml
@@ -35,4 +35,4 @@ jobs:
       run: |
           pwd
           source ../ci_testing/bin/activate
-          python -m pytest test/regression --mode=numba --target=gpu
+          python -m pytest -v test/regression --mode=numba --target=gpu
diff --git a/.github/workflows/regression_test.yml b/.github/workflows/regression_test.yml
index 06d5232db..6ed94566f 100644
--- a/.github/workflows/regression_test.yml
+++ b/.github/workflows/regression_test.yml
@@ -34,22 +34,22 @@ jobs:
           # Python modes:
           - mode: Python-Serial
             python-version: '3.13'
-            run_cmd: "python -m pytest test/regression"
+            run_cmd: "python -m pytest -v test/regression"
             timeout: 10
           - mode: Python-MPI
             python-version: '3.13'
             run_cmd: |
-              python -m pytest test/regression --mpiexec=4
+              python -m pytest -v test/regression --mpiexec=4
             timeout: 30
           # Numba modes:
           - mode: Numba-Serial
             python-version: '3.13'
-            run_cmd: "python -m pytest test/regression --mode numba"
+            run_cmd: "python -m pytest -v test/regression --mode numba"
             timeout: 120
           - mode: Numba-MPI
             python-version: '3.13'
             run_cmd: |
-              python -m pytest test/regression --mode numba --mpiexec=4
+              python -m pytest -v test/regression --mode numba --mpiexec=4
             timeout: 120
 
     steps:
diff --git a/.github/workflows/unit_test.yml b/.github/workflows/unit_test.yml
index 7a5d6ca95..0d2e722ac 100644
--- a/.github/workflows/unit_test.yml
+++ b/.github/workflows/unit_test.yml
@@ -46,4 +46,4 @@ jobs:
 
       - name: Run unit tests
         run: |
-          python -m pytest test/unit
+          python -m pytest -v test/unit

From 3f6e50807eccaf534b88b84b47876a77e6e74494 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 25 Jul 2026 11:43:43 +0700
Subject: [PATCH 032/202] add verbose option in pytest workflow

---
 .github/workflows/docker.yml | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml
index 04a2e952c..97f81d0bc 100644
--- a/.github/workflows/docker.yml
+++ b/.github/workflows/docker.yml
@@ -120,14 +120,14 @@ jobs:
         run: |
           docker run --rm \
             -w /opt/mcdc/test/unit \
-            mcdc:${{ needs.build.outputs.image_tag }} python -m pytest .
+            mcdc:${{ needs.build.outputs.image_tag }} python -m pytest -v .
 
       - name: Run unit tests (with workspace mount)
         run: |
           docker run --rm \
             -v ${{ github.workspace }}:/opt/mcdc \
             -w /opt/mcdc/test/unit \
-            mcdc:${{ needs.build.outputs.image_tag }} python -m pytest .
+            mcdc:${{ needs.build.outputs.image_tag }} python -m pytest -v .
 
   # ---------------------------------------------------------------------------
   # Stage 2b: Regression — only on push, or on PRs touching docker-relevant files
@@ -145,18 +145,18 @@ jobs:
       matrix:
         include:
           - mode: Python-Serial
-            run_cmd: "python -m pytest test/regression"
+            run_cmd: "python -m pytest -v test/regression"
             timeout: 10
           - mode: Python-MPI
             run_cmd: |
-              python -m pytest test/regression --mpiexec=2
+              python -m pytest -v test/regression --mpiexec=2
             timeout: 20
           - mode: Numba-Serial
-            run_cmd: "python -m pytest test/regression --mode numba"
+            run_cmd: "python -m pytest -v test/regression --mode numba"
             timeout: 120
           - mode: Numba-MPI
             run_cmd: |
-              python -m pytest test/regression --mode numba --mpiexec=2
+              python -m pytest -v test/regression --mode numba --mpiexec=2
             timeout: 120
 
     steps:

From dd1d332521422459058fa1b5db93e8b0567affbc Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 26 Jul 2026 14:26:28 +0700
Subject: [PATCH 033/202] Update IDing

---
 mcdc/object_/cell.py    | 8 ++++----
 mcdc/object_/surface.py | 2 +-
 mcdc/object_/tally.py   | 4 ++--
 3 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index bac77724a..46c39cbc0 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -181,13 +181,13 @@ def __repr__(self):
             text += f"  - Translation: {self.translation}\n"
         if self.fill_rotated:
             text += f"  - Rotation: {self.rotation * 180 / PI}\n"
-        # text += f"  - Bounding surfaces: {[x.ID for x in self.surfaces]}\n"
+        text += f"  - Bounding surfaces: {[x.name for x in self.surfaces]}\n"
         if len(self.collision_tallies) > 0:
-            text += f"  - Collision tallies: {[x.ID for x in self.collision_tallies]}\n"
-        if len(self.tracklength_tallies) > 0:
             text += (
-                f"  - Tracklength tallies: {[x.ID for x in self.tracklength_tallies]}\n"
+                f"  - Collision tallies: {[x.name for x in self.collision_tallies]}\n"
             )
+        if len(self.tracklength_tallies) > 0:
+            text += f"  - Tracklength tallies: {[x.name for x in self.tracklength_tallies]}\n"
         return text
 
 
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 7d922f240..5cdf3d1e3 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -223,7 +223,7 @@ def __repr__(self):
             text += f"  - R: {self.R} cm\n"
             text += f"  - r: {self.r} cm\n"
         if len(self.surface_crossing_tallies) > 0:
-            text += f"  - Surface-crossing tallies: {[x.ID for x in self.surface_crossing_tallies]}\n"
+            text += f"  - Surface-crossing tallies: {[x.name for x in self.surface_crossing_tallies]}\n"
 
         return text
 
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 88a5439d1..a246391a7 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -520,7 +520,7 @@ def _compile_into_simulation(self, simulation) -> bool:
         mesh = self.mesh
         if mesh:
             mesh._compile_into_simulation(simulation)
-            self.mesh_filter_ID = mesh.sub_ID
+            self.mesh_filter_ID = mesh.ID
 
         # Attach to all cells if cell filter is not specified
         if not self.cell_filtered:
@@ -642,7 +642,7 @@ def _compile_into_simulation(self, simulation) -> bool:
         mesh = self.mesh
         if mesh:
             mesh._compile_into_simulation(simulation)
-            self.mesh_filter_ID = mesh.sub_ID
+            self.mesh_filter_ID = mesh.ID
 
         # Attach to all cells if cell filter is not specified
         if not self.cell_filtered:

From e5210590377d4f90aa4d14bdb0a78851fe27b63d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 26 Jul 2026 14:41:16 +0700
Subject: [PATCH 034/202] reconfigure polymorphic base flagging

---
 mcdc/code_factory/numba_objects_generator.py | 6 ++----
 mcdc/code_factory/python_objects_compiler.py | 2 +-
 mcdc/object_/data.py                         | 2 +-
 mcdc/object_/distribution.py                 | 2 +-
 mcdc/object_/electron_reaction.py            | 2 +-
 mcdc/object_/material.py                     | 2 +-
 mcdc/object_/mesh.py                         | 2 +-
 mcdc/object_/neutron_reaction.py             | 2 +-
 mcdc/object_/tally.py                        | 2 +-
 9 files changed, 10 insertions(+), 12 deletions(-)

diff --git a/mcdc/code_factory/numba_objects_generator.py b/mcdc/code_factory/numba_objects_generator.py
index 73f76748e..65fa46f71 100644
--- a/mcdc/code_factory/numba_objects_generator.py
+++ b/mcdc/code_factory/numba_objects_generator.py
@@ -79,9 +79,7 @@
                 mcdc_classes.append(item)
 
 polymorphic_bases = [
-    x
-    for x in all_classes
-    if (x.__name__[-4:] == "Base" or x.__name__ == "Tally") and "label" in dir(x)
+    x for x in mcdc_classes if issubclass(x, MCDCPolymorphic) and x.sub_type == -1
 ]
 
 # ======================================================================================
@@ -211,7 +209,7 @@ def generate_numba_objects(simulation):
             structures[class_.label].append(("ID", type_map[int]))
         # Set parent and child ID and type if polymorphic
         if issubclass(class_, MCDCPolymorphic):
-            if class_.__name__[-4:] == "Base" or class_.__name__ == "Tally":
+            if class_ in polymorphic_bases:
                 structures[class_.label].append(("sub_type", type_map[int]))
                 structures[class_.label].append(("sub_ID", type_map[int]))
             else:
diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index 874ac1ca1..5e0985d32 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -107,7 +107,7 @@ def register_object(object_: MCDCObject, simulation: Simulation) -> bool:
         )
     object_.compile_ID = simulation.compile_ID
 
-    # Assign name if needed
+    # Assign name if needed (TODO: Resolve IDE error message)
     if hasattr(object_, "name") and object_.name.startswith("(Unnamed"):
         if isinstance(object_, MCDCPolymorphic):
             ID = object_.sub_ID
diff --git a/mcdc/object_/data.py b/mcdc/object_/data.py
index 4b96cfe75..8b6b2aa98 100644
--- a/mcdc/object_/data.py
+++ b/mcdc/object_/data.py
@@ -27,7 +27,7 @@
 class DataBase(MCDCPolymorphic):
     # MC/DC framework metadata
     label = "data"
-    sub_type = -1
+    sub_type = -1  # Polymorphic base
 
 
 # ======================================================================================
diff --git a/mcdc/object_/distribution.py b/mcdc/object_/distribution.py
index 2cd295986..c4463d245 100644
--- a/mcdc/object_/distribution.py
+++ b/mcdc/object_/distribution.py
@@ -36,7 +36,7 @@
 class DistributionBase(MCDCPolymorphic):
     # MC/DC framework metadata
     label = "distribution"
-    sub_type = -1
+    sub_type = -1  # Polymorphic base
 
 
 # ======================================================================================
diff --git a/mcdc/object_/electron_reaction.py b/mcdc/object_/electron_reaction.py
index 3e5a3235d..71913beac 100644
--- a/mcdc/object_/electron_reaction.py
+++ b/mcdc/object_/electron_reaction.py
@@ -28,7 +28,7 @@
 class ElectronReactionBase(MCDCPolymorphic):
     # MC/DC framework metadata
     label = "electron_reaction"
-    sub_type = -1
+    sub_type = -1  # Polymorphic base
 
     MT: int
     xs: NDArray[float64]
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 1d10032d3..70ebf7861 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -23,7 +23,7 @@
 class MaterialBase(MCDCPolymorphic):
     # MC/DC framework metadata
     label = "material"
-    sub_type = -1
+    sub_type = -1  # Polymorphic base
 
     name: str
     fissionable: bool
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index 6511a1016..b6e3ba725 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -18,7 +18,7 @@
 class MeshBase(MCDCPolymorphic):
     # MC/DC framework metadata
     label = "mesh"
-    sub_type = -1
+    sub_type = -1  # Polymorphic base
 
     name: str
     N_bin: int
diff --git a/mcdc/object_/neutron_reaction.py b/mcdc/object_/neutron_reaction.py
index 99b8464b4..612346c9b 100644
--- a/mcdc/object_/neutron_reaction.py
+++ b/mcdc/object_/neutron_reaction.py
@@ -39,7 +39,7 @@
 class NeutronReactionBase(MCDCPolymorphic):
     # MC/DC framework metadata
     label = "neutron_reaction"
-    sub_type = -1
+    sub_type = -1  # Polymorphic base
 
     MT: int
     xs: NDArray[float64]
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index a246391a7..7a652c51a 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -48,7 +48,7 @@
 class Tally(MCDCPolymorphic):
     # MC/DC framework metadata
     label = "tally"
-    sub_type = -1
+    sub_type = -1  # Polymorphic base
 
     # Basic properties
     name: str

From 029e89cdaabe88dca1289ea1df372ab236cc51b9 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 26 Jul 2026 15:17:42 +0700
Subject: [PATCH 035/202] reorganize data evaluation call

---
 mcdc/transport/distribution.py            | 12 ++++--------
 mcdc/transport/physics/electron/native.py |  8 ++++----
 mcdc/transport/physics/neutron/native.py  | 12 ++++++++----
 3 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/mcdc/transport/distribution.py b/mcdc/transport/distribution.py
index 230f7e95e..fabb7c079 100644
--- a/mcdc/transport/distribution.py
+++ b/mcdc/transport/distribution.py
@@ -18,14 +18,10 @@
     DISTRIBUTION_TABULATED_ENERGY_ANGLE,
     INTERPOLATION_HISTOGRAM,
     INTERPOLATION_LINEAR,
-    INTERPOLATION_LOG,
-    INTERPOLATION_SEMILOGX,
-    INTERPOLATION_SEMILOGY,
-    MAX_BISECTION_ITERATIONS,
     PI,
 )
-from mcdc.transport.data import evaluate_table, get_table_interpolation_law
-from mcdc.transport.util import find_bin, linear_interpolation
+from mcdc.transport.data import evaluate_data
+from mcdc.transport.util import find_bin
 
 # ======================================================================================
 # General distribution samplers
@@ -382,7 +378,7 @@ def _sample_multi_table(E, rng_state, multi_table, simulation, data, scale):
 def sample_maxwellian(E, rng_state, maxwellian, simulation, data):
     # Get nuclear temperature
     table = simulation["table_data"][maxwellian["nuclear_temperature_ID"]]
-    nuclear_temperature = evaluate_table(E, table, data)
+    nuclear_temperature = evaluate_data(E, table, simulation, data)
     restriction_energy = maxwellian["restriction_energy"]
 
     # Rejection sampling
@@ -412,7 +408,7 @@ def sample_level_scattering(E, level_scattering):
 def sample_evaporation(E, rng_state, evaporation, simulation, data):
     # Get nuclear temperature
     table = simulation["table_data"][evaporation["nuclear_temperature_ID"]]
-    nuclear_temperature = evaluate_table(E, table, data)
+    nuclear_temperature = evaluate_data(E, table, simulation, data)
     restriction_energy = evaporation["restriction_energy"]
 
     w = (E - restriction_energy) / nuclear_temperature
diff --git a/mcdc/transport/physics/electron/native.py b/mcdc/transport/physics/electron/native.py
index 2865d4cc7..247d2f85b 100644
--- a/mcdc/transport/physics/electron/native.py
+++ b/mcdc/transport/physics/electron/native.py
@@ -349,8 +349,8 @@ def sample_small_angle_mu_coulomb(E, Z, rng_state, mu_cut):
 
 @njit
 def elastic_large_xs(E, reaction, simulation, data):
-    data_base = simulation["data"][int(reaction["xs_large_ID"])]
-    return evaluate_data(E, data_base, simulation, data)
+    reaction_data = simulation["data"][int(reaction["xs_large_ID"])]
+    return evaluate_data(E, reaction_data, simulation, data)
 
 
 # ======================================================================================
@@ -387,8 +387,8 @@ def excitation(
 
 @njit
 def evaluate_eloss(E, reaction, simulation, data):
-    data_base = simulation["data"][int(reaction["eloss_ID"])]
-    return evaluate_data(E, data_base, simulation, data)
+    reaction_data = simulation["data"][int(reaction["eloss_ID"])]
+    return evaluate_data(E, reaction_data, simulation, data)
 
 
 # ======================================================================================
diff --git a/mcdc/transport/physics/neutron/native.py b/mcdc/transport/physics/neutron/native.py
index c378dd745..5cdf1f32e 100644
--- a/mcdc/transport/physics/neutron/native.py
+++ b/mcdc/transport/physics/neutron/native.py
@@ -980,11 +980,15 @@ def fission(
 
 @njit
 def neutron_fission_prompt_multiplicity(E, nuclide, simulation, data):
-    data_base = simulation["data"][nuclide["neutron_fission_prompt_multiplicity_ID"]]
-    return evaluate_data(E, data_base, simulation, data)
+    reaction_data = simulation["data"][
+        nuclide["neutron_fission_prompt_multiplicity_ID"]
+    ]
+    return evaluate_data(E, reaction_data, simulation, data)
 
 
 @njit
 def neutron_fission_delayed_multiplicity(E, nuclide, simulation, data):
-    data_base = simulation["data"][nuclide["neutron_fission_delayed_multiplicity_ID"]]
-    return evaluate_data(E, data_base, simulation, data)
+    reaction_data = simulation["data"][
+        nuclide["neutron_fission_delayed_multiplicity_ID"]
+    ]
+    return evaluate_data(E, reaction_data, simulation, data)

From 3e8d5a7912bc590639a3d7bcbe50b8ddacdc5ce8 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 26 Jul 2026 16:31:41 +0700
Subject: [PATCH 036/202] rename data_base

---
 mcdc/transport/data.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/mcdc/transport/data.py b/mcdc/transport/data.py
index abd9a205b..f0894d1c3 100644
--- a/mcdc/transport/data.py
+++ b/mcdc/transport/data.py
@@ -24,9 +24,9 @@
 
 
 @njit
-def evaluate_data(x, data_base, simulation, data):
-    data_type = data_base["sub_type"]
-    ID = data_base["sub_ID"]
+def evaluate_data(x, data_, simulation, data):
+    data_type = data_["sub_type"]
+    ID = data_["sub_ID"]
     if data_type == DATA_TABLE:
         table = simulation["table_data"][ID]
         return evaluate_table(x, table, data)

From b7f006b4f2f5f44b08356c4cc0fc716f6b9e4570 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 26 Jul 2026 16:59:49 +0700
Subject: [PATCH 037/202] update object base/sub inconsistency

---
 mcdc/transport/technique.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/mcdc/transport/technique.py b/mcdc/transport/technique.py
index cbec2f1bb..5de637998 100644
--- a/mcdc/transport/technique.py
+++ b/mcdc/transport/technique.py
@@ -157,8 +157,8 @@ def get_ww_indices(particle_container, ww_obj, simulation, data):
     ie = util.find_bin(energy, energy_bounds)
 
     # get spatial index
-    mesh_base = simulation["meshes"][ww_obj["mesh_ID"]]
-    idx, idy, idz = get_mesh_indices(particle_container, mesh_base, simulation, data)
+    mesh = simulation["meshes"][ww_obj["mesh_ID"]]
+    idx, idy, idz = get_mesh_indices(particle_container, mesh, simulation, data)
 
     return (ie, idx, idy, idz)
 

From 479be9a4dab0130bd9b00204b20f4902f91ce20e Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 26 Jul 2026 17:00:06 +0700
Subject: [PATCH 038/202] update object base/sub inconsistency

---
 mcdc/transport/tally/score.py | 126 +++++++++++++++++-----------------
 1 file changed, 64 insertions(+), 62 deletions(-)

diff --git a/mcdc/transport/tally/score.py b/mcdc/transport/tally/score.py
index d8ff8c9a2..8b5ce9ce3 100644
--- a/mcdc/transport/tally/score.py
+++ b/mcdc/transport/tally/score.py
@@ -41,17 +41,17 @@
 def surface_crossing_tally(
     particle_container,
     surface,
-    tally,
+    surface_crossing_tally,
     simulation,
     data,
 ):
     particle = particle_container[0]
-    tally_base = simulation["tallies"][tally["base_ID"]]
+    tally = simulation["tallies"][surface_crossing_tally["base_ID"]]
 
     # Get filter indices
     MG_mode = simulation["settings"]["neutron_multigroup_mode"]
     i_mu, i_azi, i_energy, i_time = get_filter_indices(
-        particle_container, tally_base, data, MG_mode
+        particle_container, tally, data, MG_mode
     )
 
     # No score if outside non-changing phase-space bins
@@ -60,11 +60,11 @@ def surface_crossing_tally(
 
     # Tally index
     idx_base = (
-        tally_base["bin_offset"]
-        + i_mu * tally_base["stride_mu"]
-        + i_azi * tally_base["stride_azi"]
-        + i_energy * tally_base["stride_energy"]
-        + i_time * tally_base["stride_time"]
+        tally["bin_offset"]
+        + i_mu * tally["stride_mu"]
+        + i_azi * tally["stride_azi"]
+        + i_energy * tally["stride_energy"]
+        + i_time * tally["stride_time"]
     )
 
     # Flux
@@ -73,9 +73,9 @@ def surface_crossing_tally(
     flux = particle["w"] / abs(mu)
 
     # Non-cell-filtered score
-    if not tally["cell_filtered"]:
-        for i_score in range(tally_base["scores_length"]):
-            score_type = mcdc_get.tally.scores(i_score, tally_base, data)
+    if not surface_crossing_tally["cell_filtered"]:
+        for i_score in range(tally["scores_length"]):
+            score_type = mcdc_get.tally.scores(i_score, tally, data)
 
             score = 0.0
             if score_type == SCORE_CURRENT_NET:
@@ -92,14 +92,14 @@ def surface_crossing_tally(
 
     # Cell-filtered score
     previous_cell_ID = particle["cell_ID"]
-    filter_cell_ID = tally["cell_filter_ID"]
+    filter_cell_ID = surface_crossing_tally["cell_filter_ID"]
     filter_cell = simulation["cells"][filter_cell_ID]
     was_in_filter_cell = previous_cell_ID == filter_cell_ID
     now_in_filter_cell = check_cell(particle_container, filter_cell, simulation, data)
     entered_filter_cell = not was_in_filter_cell and now_in_filter_cell
     exited_filter_cell = was_in_filter_cell and not now_in_filter_cell
-    for i_score in range(tally_base["scores_length"]):
-        score_type = mcdc_get.tally.scores(i_score, tally_base, data)
+    for i_score in range(tally["scores_length"]):
+        score_type = mcdc_get.tally.scores(i_score, tally, data)
 
         score = 0.0
         if score_type == SCORE_CURRENT_NET:
@@ -124,16 +124,16 @@ def surface_crossing_tally(
 
 @njit
 def collision_tally(
-    particle_container, collision_data_container, tally, simulation, data
+    particle_container, collision_data_container, collision_tally, simulation, data
 ):
     particle = particle_container[0]
     collision_data = collision_data_container[0]
-    tally_base = simulation["tallies"][tally["base_ID"]]
+    tally = simulation["tallies"][collision_tally["base_ID"]]
 
     # Get filter indices
     MG_mode = simulation["settings"]["neutron_multigroup_mode"]
     i_mu, i_azi, i_energy, i_time = get_filter_indices(
-        particle_container, tally_base, data, MG_mode
+        particle_container, tally, data, MG_mode
     )
 
     # No score if outside non-changing phase-space bins
@@ -142,8 +142,8 @@ def collision_tally(
 
     # Mesh tally indices if needed
     i_x, i_y, i_z = 0, 0, 0
-    if tally["mesh_filtered"]:
-        mesh = simulation["meshes"][tally["mesh_filter_ID"]]
+    if collision_tally["mesh_filtered"]:
+        mesh = simulation["meshes"][collision_tally["mesh_filter_ID"]]
         i_x, i_y, i_z = mesh_module.get_indices(
             particle_container, mesh, simulation, data
         )
@@ -154,22 +154,22 @@ def collision_tally(
 
     # Tally index
     idx_base = (
-        tally_base["bin_offset"]
-        + i_mu * tally_base["stride_mu"]
-        + i_azi * tally_base["stride_azi"]
-        + i_energy * tally_base["stride_energy"]
-        + i_time * tally_base["stride_time"]
+        tally["bin_offset"]
+        + i_mu * tally["stride_mu"]
+        + i_azi * tally["stride_azi"]
+        + i_energy * tally["stride_energy"]
+        + i_time * tally["stride_time"]
     )
-    if tally["mesh_filtered"]:
+    if collision_tally["mesh_filtered"]:
         idx_base += (
-            +i_x * tally["mesh_stride_x"]
-            + i_y * tally["mesh_stride_y"]
-            + i_z * tally["mesh_stride_z"]
+            +i_x * collision_tally["mesh_stride_x"]
+            + i_y * collision_tally["mesh_stride_y"]
+            + i_z * collision_tally["mesh_stride_z"]
         )
 
     # Score
-    for i_score in range(tally_base["scores_length"]):
-        score_type = mcdc_get.tally.scores(i_score, tally_base, data)
+    for i_score in range(tally["scores_length"]):
+        score_type = mcdc_get.tally.scores(i_score, tally, data)
         score = 0.0
         if score_type == SCORE_ENERGY_DEPOSITION:
             score = collision_data["energy_deposition"]
@@ -182,14 +182,16 @@ def collision_tally(
 
 
 @njit
-def tracklength_tally(particle_container, distance, tally, simulation, data):
+def tracklength_tally(
+    particle_container, distance, tracklength_tally, simulation, data
+):
     particle = particle_container[0]
-    tally_base = simulation["tallies"][tally["base_ID"]]
+    tally = simulation["tallies"][tracklength_tally["base_ID"]]
 
     # Get filter indices
     MG_mode = simulation["settings"]["neutron_multigroup_mode"]
     i_mu, i_azi, i_energy, i_time = get_filter_indices(
-        particle_container, tally_base, data, MG_mode
+        particle_container, tally, data, MG_mode
     )
 
     # No score if outside non-changing phase-space bins
@@ -211,8 +213,8 @@ def tracklength_tally(particle_container, distance, tally, simulation, data):
     t_final = t + ut * distance
 
     # No score if particle does not cross the time bins
-    t_min = mcdc_get.tally.time(0, tally_base, data)
-    t_max = mcdc_get.tally.time_last(tally_base, data)
+    t_min = mcdc_get.tally.time(0, tally, data)
+    t_max = mcdc_get.tally.time_last(tally, data)
     if (
         t_final < t_min + COINCIDENCE_TOLERANCE_TIME
         or t > t_max - COINCIDENCE_TOLERANCE_TIME
@@ -230,8 +232,8 @@ def tracklength_tally(particle_container, distance, tally, simulation, data):
 
     # Mesh axis indices
     i_x, i_y, i_z = 0, 0, 0
-    if tally["mesh_filtered"]:
-        mesh = simulation["meshes"][tally["mesh_filter_ID"]]
+    if tracklength_tally["mesh_filtered"]:
+        mesh = simulation["meshes"][tracklength_tally["mesh_filter_ID"]]
 
         # Mesh axis indices
         i_x, i_y, i_z = mesh_module.get_indices(
@@ -302,24 +304,24 @@ def tracklength_tally(particle_container, distance, tally, simulation, data):
 
     # Tally base index
     idx_base = (
-        tally_base["bin_offset"]
-        + i_mu * tally_base["stride_mu"]
-        + i_azi * tally_base["stride_azi"]
-        + i_energy * tally_base["stride_energy"]
-        + i_time * tally_base["stride_time"]
+        tally["bin_offset"]
+        + i_mu * tally["stride_mu"]
+        + i_azi * tally["stride_azi"]
+        + i_energy * tally["stride_energy"]
+        + i_time * tally["stride_time"]
     )
-    if tally["mesh_filtered"]:
+    if tracklength_tally["mesh_filtered"]:
         idx_base += (
-            i_x * tally["mesh_stride_x"]
-            + i_y * tally["mesh_stride_y"]
-            + i_z * tally["mesh_stride_z"]
+            i_x * tracklength_tally["mesh_stride_x"]
+            + i_y * tracklength_tally["mesh_stride_y"]
+            + i_z * tracklength_tally["mesh_stride_z"]
         )
 
     # Sweep through the distance
     distance_swept = 0.0
     while distance_swept < distance - COINCIDENCE_TOLERANCE:
         # The next time grid
-        t_next = mcdc_get.tally.time(i_time + 1, tally_base, data)
+        t_next = mcdc_get.tally.time(i_time + 1, tally, data)
 
         # Get the distance to score in this segment
         if t_final < t_next - COINCIDENCE_TOLERANCE_TIME:
@@ -333,8 +335,8 @@ def tracklength_tally(particle_container, distance, tally, simulation, data):
         #     axis is crossed
 
         axis_crossed = AXIS_T
-        if tally["mesh_filtered"]:
-            mesh = simulation["meshes"][tally["mesh_filter_ID"]]
+        if tracklength_tally["mesh_filtered"]:
+            mesh = simulation["meshes"][tracklength_tally["mesh_filter_ID"]]
 
             # x-direction
             if ux == 0.0:
@@ -386,8 +388,8 @@ def tracklength_tally(particle_container, distance, tally, simulation, data):
 
         # Score
         flux = distance_scored * particle["w"]
-        for i_score in range(tally_base["scores_length"]):
-            score_type = mcdc_get.tally.scores(i_score, tally_base, data)
+        for i_score in range(tally["scores_length"]):
+            score_type = mcdc_get.tally.scores(i_score, tally, data)
             score = 0.0
             if score_type == SCORE_FLUX:
                 score = flux
@@ -412,7 +414,7 @@ def tracklength_tally(particle_container, distance, tally, simulation, data):
         distance_swept += distance_scored
 
         # Move the 4D position
-        if tally["mesh_filtered"]:
+        if tracklength_tally["mesh_filtered"]:
             x += distance_scored * ux
             y += distance_scored * uy
             z += distance_scored * uz
@@ -421,44 +423,44 @@ def tracklength_tally(particle_container, distance, tally, simulation, data):
         # Increment index and heck if out of bounds
         if axis_crossed == AXIS_T:
             i_time += 1
-            idx_base += tally_base["stride_time"]
-            if i_time == tally_base["time_length"] - 1:
+            idx_base += tally["stride_time"]
+            if i_time == tally["time_length"] - 1:
                 return
-        elif tally["mesh_filtered"]:
-            mesh = simulation["meshes"][tally["mesh_filter_ID"]]
+        elif tracklength_tally["mesh_filtered"]:
+            mesh = simulation["meshes"][tracklength_tally["mesh_filter_ID"]]
             if axis_crossed == AXIS_X:
                 if ux > 0.0:
                     i_x += 1
                     if i_x == mesh["Nx"]:
                         return
-                    idx_base += tally["mesh_stride_x"]
+                    idx_base += tracklength_tally["mesh_stride_x"]
                 else:
                     i_x -= 1
                     if i_x == -1:
                         return
-                    idx_base -= tally["mesh_stride_x"]
+                    idx_base -= tracklength_tally["mesh_stride_x"]
             elif axis_crossed == AXIS_Y:
                 if uy > 0.0:
                     i_y += 1
                     if i_y == mesh["Ny"]:
                         return
-                    idx_base += tally["mesh_stride_y"]
+                    idx_base += tracklength_tally["mesh_stride_y"]
                 else:
                     i_y -= 1
                     if i_y == -1:
                         return
-                    idx_base -= tally["mesh_stride_y"]
+                    idx_base -= tracklength_tally["mesh_stride_y"]
             elif axis_crossed == AXIS_Z:
                 if uz > 0.0:
                     i_z += 1
                     if i_z == mesh["Nz"]:
                         return
-                    idx_base += tally["mesh_stride_z"]
+                    idx_base += tracklength_tally["mesh_stride_z"]
                 else:
                     i_z -= 1
                     if i_z == -1:
                         return
-                    idx_base -= tally["mesh_stride_z"]
+                    idx_base -= tracklength_tally["mesh_stride_z"]
 
 
 # =============================================================================

From 6be601c131ef7cba9671b77a1f0816c166c52d96 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 26 Jul 2026 17:00:16 +0700
Subject: [PATCH 039/202] update object base/sub inconsistency

---
 mcdc/transport/source.py | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/mcdc/transport/source.py b/mcdc/transport/source.py
index 0adbec6a7..bc133733c 100644
--- a/mcdc/transport/source.py
+++ b/mcdc/transport/source.py
@@ -26,6 +26,7 @@ def source_particle(particle_container, seed, simulation, data):
     # TODO: use cdf and binary search instead
     xi = rng.lcg(particle_container)
     tot = 0.0
+    source = simulation["sources"][0]
     for source in simulation["sources"]:
         tot += source["probability"]
         if tot >= xi:
@@ -68,7 +69,8 @@ def source_particle(particle_container, seed, simulation, data):
             g = source["energy_group"]
         else:
             ID = source["energy_group_pmf_ID"]
-            pmf = simulation["pmf_distributions"][ID]
+            sub_ID = simulation["distributions"][ID]["sub_ID"]
+            pmf = simulation["pmf_distributions"][sub_ID]
             g = sample_pmf(pmf, particle_container, data)
     else:
         g = 0
@@ -76,7 +78,8 @@ def source_particle(particle_container, seed, simulation, data):
             E = source["energy"]
         else:
             ID = source["energy_pdf_ID"]
-            table = simulation["tabulated_distributions"][ID]
+            sub_ID = simulation["distributions"][ID]["sub_ID"]
+            table = simulation["tabulated_distributions"][sub_ID]
             E = sample_tabulated(table, particle_container, simulation, data)
 
     # Time

From d1e7274cd45047e91344197e006e877596c38405 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 26 Jul 2026 17:00:31 +0700
Subject: [PATCH 040/202] update object base/sub inconsistency

---
 mcdc/transport/mesh/interface.py  | 56 ++++++++++++-------------
 mcdc/transport/mesh/structured.py | 68 +++++++++++++++++++------------
 mcdc/transport/mesh/uniform.py    | 44 ++++++++++----------
 3 files changed, 92 insertions(+), 76 deletions(-)

diff --git a/mcdc/transport/mesh/interface.py b/mcdc/transport/mesh/interface.py
index f395ae35c..0066fc422 100644
--- a/mcdc/transport/mesh/interface.py
+++ b/mcdc/transport/mesh/interface.py
@@ -7,57 +7,57 @@
 
 
 @njit
-def get_indices(particle_container, mesh_base, simulation, data):
-    mesh_type = mesh_base["sub_type"]
-    mesh_ID = mesh_base["sub_ID"]
+def get_indices(particle_container, mesh, simulation, data):
+    mesh_type = mesh["sub_type"]
+    mesh_ID = mesh["sub_ID"]
 
     if mesh_type == MESH_UNIFORM:
-        mesh = simulation["uniform_meshes"][mesh_ID]
-        return uniform.get_indices(particle_container, mesh)
+        uniform_mesh = simulation["uniform_meshes"][mesh_ID]
+        return uniform.get_indices(particle_container, uniform_mesh)
     elif mesh_type == MESH_STRUCTURED:
-        mesh = simulation["structured_meshes"][mesh_ID]
-        return structured.get_indices(particle_container, mesh, data)
+        structured_mesh = simulation["structured_meshes"][mesh_ID]
+        return structured.get_indices(particle_container, structured_mesh, data)
 
     return -1, -1, -1
 
 
 @njit
-def get_x(index, mesh_base, simulation, data):
-    mesh_type = mesh_base["sub_type"]
-    mesh_ID = mesh_base["sub_ID"]
+def get_x(index, mesh, simulation, data):
+    mesh_type = mesh["sub_type"]
+    mesh_ID = mesh["sub_ID"]
 
     if mesh_type == MESH_UNIFORM:
-        mesh = simulation["uniform_meshes"][mesh_ID]
-        return mesh["x0"] + mesh["dx"] * index
+        uniform_mesh = simulation["uniform_meshes"][mesh_ID]
+        return uniform_mesh["x0"] + uniform_mesh["dx"] * index
     elif mesh_type == MESH_STRUCTURED:
-        mesh = simulation["structured_meshes"][mesh_ID]
-        return mcdc_get.structured_mesh.x(index, mesh, data)
+        structured_mesh = simulation["structured_meshes"][mesh_ID]
+        return mcdc_get.structured_mesh.x(index, structured_mesh, data)
     return 0.0
 
 
 @njit
-def get_y(index, mesh_base, simulation, data):
-    mesh_type = mesh_base["sub_type"]
-    mesh_ID = mesh_base["sub_ID"]
+def get_y(index, mesh, simulation, data):
+    mesh_type = mesh["sub_type"]
+    mesh_ID = mesh["sub_ID"]
 
     if mesh_type == MESH_UNIFORM:
-        mesh = simulation["uniform_meshes"][mesh_ID]
-        return mesh["y0"] + mesh["dy"] * index
+        uniform_mesh = simulation["uniform_meshes"][mesh_ID]
+        return uniform_mesh["y0"] + uniform_mesh["dy"] * index
     elif mesh_type == MESH_STRUCTURED:
-        mesh = simulation["structured_meshes"][mesh_ID]
-        return mcdc_get.structured_mesh.y(index, mesh, data)
+        structured_mesh = simulation["structured_meshes"][mesh_ID]
+        return mcdc_get.structured_mesh.y(index, structured_mesh, data)
     return 0.0
 
 
 @njit
-def get_z(index, mesh_base, simulation, data):
-    mesh_type = mesh_base["sub_type"]
-    mesh_ID = mesh_base["sub_ID"]
+def get_z(index, mesh, simulation, data):
+    mesh_type = mesh["sub_type"]
+    mesh_ID = mesh["sub_ID"]
 
     if mesh_type == MESH_UNIFORM:
-        mesh = simulation["uniform_meshes"][mesh_ID]
-        return mesh["z0"] + mesh["dz"] * index
+        uniform_mesh = simulation["uniform_meshes"][mesh_ID]
+        return uniform_mesh["z0"] + uniform_mesh["dz"] * index
     elif mesh_type == MESH_STRUCTURED:
-        mesh = simulation["structured_meshes"][mesh_ID]
-        return mcdc_get.structured_mesh.z(index, mesh, data)
+        structured_mesh = simulation["structured_meshes"][mesh_ID]
+        return mcdc_get.structured_mesh.z(index, structured_mesh, data)
     return 0.0
diff --git a/mcdc/transport/mesh/structured.py b/mcdc/transport/mesh/structured.py
index 9afe50a8a..7e3ad989f 100644
--- a/mcdc/transport/mesh/structured.py
+++ b/mcdc/transport/mesh/structured.py
@@ -2,16 +2,14 @@
 
 ####
 
-import mcdc.mcdc_get as mcdc_get
-
-from mcdc.constant import COINCIDENCE_TOLERANCE, COINCIDENCE_TOLERANCE_TIME, INF
+from mcdc.constant import COINCIDENCE_TOLERANCE, INF
 from mcdc.transport.util import find_bin_with_rules
 
 
 @njit
-def get_indices(particle_container, mesh, data):
+def get_indices(particle_container, structured_mesh, data):
     """
-    Get mesh indices given the particle coordinate
+    Get structured_mesh indices given the particle coordinate
     """
     particle = particle_container[0]
 
@@ -23,12 +21,24 @@ def get_indices(particle_container, mesh, data):
     uy = particle["uy"]
     uz = particle["uz"]
 
-    grid_x = data[mesh["x_offset"] : (mesh["x_offset"] + mesh["x_length"])]
-    # Above is equivalent to: grid_x = mcdc_get.structured_mesh.x_all(mesh, data)
-    grid_y = data[mesh["y_offset"] : (mesh["y_offset"] + mesh["y_length"])]
-    # Above is equivalent to: grid_y = mcdc_get.structured_mesh.y_all(mesh, data)
-    grid_z = data[mesh["z_offset"] : (mesh["z_offset"] + mesh["z_length"])]
-    # Above is equivalent to: grid_z = mcdc_get.structured_mesh.z_all(mesh, data)
+    grid_x = data[
+        structured_mesh["x_offset"] : (
+            structured_mesh["x_offset"] + structured_mesh["x_length"]
+        )
+    ]
+    # Above is equivalent to: grid_x = mcdc_get.structured_mesh.x_all(structured_mesh, data)
+    grid_y = data[
+        structured_mesh["y_offset"] : (
+            structured_mesh["y_offset"] + structured_mesh["y_length"]
+        )
+    ]
+    # Above is equivalent to: grid_y = mcdc_get.structured_structured_mesh.y_all(structured_mesh, data)
+    grid_z = data[
+        structured_mesh["z_offset"] : (
+            structured_mesh["z_offset"] + structured_mesh["z_length"]
+        )
+    ]
+    # Above is equivalent to: grid_z = mcdc_get.structured_structured_mesh.z_all(structured_mesh, data)
 
     tolerance = COINCIDENCE_TOLERANCE
     ux_go_lower = ux < 0.0
@@ -43,10 +53,10 @@ def get_indices(particle_container, mesh, data):
 
 
 @njit
-def get_crossing_distance(particle_arr, speed, mesh):
+def get_crossing_distance(particle_arr, speed, structured_mesh):
     """
     Get distance for the particle, moving with the given speed,
-    to cross the nearest grid of the mesh
+    to cross the nearest grid of the structured_mesh
     """
     particle = particle_arr[0]
 
@@ -59,25 +69,31 @@ def get_crossing_distance(particle_arr, speed, mesh):
     uz = particle["uz"]
 
     # Mesh parameters
-    Nx = mesh["Nx"]
-    Ny = mesh["Ny"]
-    Nz = mesh["Nz"]
+    Nx = structured_mesh["Nx"]
+    Ny = structured_mesh["Ny"]
+    Nz = structured_mesh["Nz"]
 
-    # Check if particle is outside the mesh grid and moving away
+    # Check if particle is outside the structured_mesh grid and moving away
     if (
-        (x < mesh["x"][0] + COINCIDENCE_TOLERANCE and ux < 0.0)
-        or (x > mesh["x"][Nx] - COINCIDENCE_TOLERANCE and ux > 0.0)
-        or (y < mesh["y"][0] + COINCIDENCE_TOLERANCE and uy < 0.0)
-        or (y > mesh["y"][Ny] - COINCIDENCE_TOLERANCE and uy > 0.0)
-        or (z < mesh["z"][0] + COINCIDENCE_TOLERANCE and uz < 0.0)
-        or (z > mesh["z"][Nz] - COINCIDENCE_TOLERANCE and uz > 0.0)
+        (x < structured_mesh["x"][0] + COINCIDENCE_TOLERANCE and ux < 0.0)
+        or (x > structured_mesh["x"][Nx] - COINCIDENCE_TOLERANCE and ux > 0.0)
+        or (y < structured_mesh["y"][0] + COINCIDENCE_TOLERANCE and uy < 0.0)
+        or (y > structured_mesh["y"][Ny] - COINCIDENCE_TOLERANCE and uy > 0.0)
+        or (z < structured_mesh["z"][0] + COINCIDENCE_TOLERANCE and uz < 0.0)
+        or (z > structured_mesh["z"][Nz] - COINCIDENCE_TOLERANCE and uz > 0.0)
     ):
         return INF
 
     d = INF
-    d = min(d, _grid_distance(x, ux, mesh["x"], Nx + 1, COINCIDENCE_TOLERANCE))
-    d = min(d, _grid_distance(y, uy, mesh["y"], Ny + 1, COINCIDENCE_TOLERANCE))
-    d = min(d, _grid_distance(z, uz, mesh["z"], Nz + 1, COINCIDENCE_TOLERANCE))
+    d = min(
+        d, _grid_distance(x, ux, structured_mesh["x"], Nx + 1, COINCIDENCE_TOLERANCE)
+    )
+    d = min(
+        d, _grid_distance(y, uy, structured_mesh["y"], Ny + 1, COINCIDENCE_TOLERANCE)
+    )
+    d = min(
+        d, _grid_distance(z, uz, structured_mesh["z"], Nz + 1, COINCIDENCE_TOLERANCE)
+    )
     return d
 
 
diff --git a/mcdc/transport/mesh/uniform.py b/mcdc/transport/mesh/uniform.py
index 0384fabe6..7c62cd3ca 100644
--- a/mcdc/transport/mesh/uniform.py
+++ b/mcdc/transport/mesh/uniform.py
@@ -6,9 +6,9 @@
 
 
 @njit
-def get_indices(particle_container, mesh):
+def get_indices(particle_container, uniform_mesh):
     """
-    Get mesh indices given the particle coordinate
+    Get uniform_mesh indices given the particle coordinate
     """
     particle = particle_container[0]
 
@@ -21,15 +21,15 @@ def get_indices(particle_container, mesh):
     uz = particle["uz"]
 
     # Mesh parameters
-    x0 = mesh["x0"]
-    y0 = mesh["y0"]
-    z0 = mesh["z0"]
-    dx = mesh["dx"]
-    dy = mesh["dy"]
-    dz = mesh["dz"]
-    Nx = mesh["Nx"]
-    Ny = mesh["Ny"]
-    Nz = mesh["Nz"]
+    x0 = uniform_mesh["x0"]
+    y0 = uniform_mesh["y0"]
+    z0 = uniform_mesh["z0"]
+    dx = uniform_mesh["dx"]
+    dy = uniform_mesh["dy"]
+    dz = uniform_mesh["dz"]
+    Nx = uniform_mesh["Nx"]
+    Ny = uniform_mesh["Ny"]
+    Nz = uniform_mesh["Nz"]
     x_last = x0 + Nx * dx
     y_last = y0 + Ny * dy
     z_last = z0 + Nz * dz
@@ -77,10 +77,10 @@ def get_indices(particle_container, mesh):
 
 
 @njit
-def get_crossing_distance(particle_container, speed, mesh):
+def get_crossing_distance(particle_container, speed, uniform_mesh):
     """
     Get distance for the particle, moving with the given speed,
-    to cross the nearest grid of the mesh
+    to cross the nearest grid of the uniform_mesh
     """
     particle = particle_container[0]
 
@@ -93,15 +93,15 @@ def get_crossing_distance(particle_container, speed, mesh):
     uz = particle["uz"]
 
     # Mesh parameters
-    x0 = mesh["x0"]
-    y0 = mesh["y0"]
-    z0 = mesh["z0"]
-    dx = mesh["dx"]
-    dy = mesh["dy"]
-    dz = mesh["dz"]
-    Nx = mesh["Nx"]
-    Ny = mesh["Ny"]
-    Nz = mesh["Nz"]
+    x0 = uniform_mesh["x0"]
+    y0 = uniform_mesh["y0"]
+    z0 = uniform_mesh["z0"]
+    dx = uniform_mesh["dx"]
+    dy = uniform_mesh["dy"]
+    dz = uniform_mesh["dz"]
+    Nx = uniform_mesh["Nx"]
+    Ny = uniform_mesh["Ny"]
+    Nz = uniform_mesh["Nz"]
     x_last = x0 + Nx * dx
     y_last = y0 + Ny * dy
     z_last = z0 + Nz * dz

From a601cc2e97d21f9ae3f19324dfdd8ec4e199ae99 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 11:33:51 +0700
Subject: [PATCH 041/202] update sub/base IDing

---
 mcdc/transport/distribution.py            |  33 +++--
 mcdc/transport/geometry/interface.py      |   8 ++
 mcdc/transport/physics/electron/native.py |  97 +++++++-------
 mcdc/transport/physics/neutron/native.py  | 148 +++++++++-------------
 mcdc/transport/simulation.py              |  30 ++---
 mcdc/transport/tally/score.py             |  25 ++--
 6 files changed, 171 insertions(+), 170 deletions(-)

diff --git a/mcdc/transport/distribution.py b/mcdc/transport/distribution.py
index fabb7c079..15cec02f4 100644
--- a/mcdc/transport/distribution.py
+++ b/mcdc/transport/distribution.py
@@ -181,7 +181,8 @@ def sample_tabulated(table, rng_state, simulation, data):
     Sample a value from a tabulated distribution.
     """
 
-    pdf_table = simulation["table_data"][table["pdf_ID"]]
+    pdf_data = simulation["data"][table["pdf_ID"]]
+    pdf_table = simulation["table_data"][pdf_data["sub_ID"]]
 
     cdf = mcdc_get.table_data.aux_vector(0, pdf_table, data)
 
@@ -332,7 +333,8 @@ def _sample_multi_table(E, rng_state, multi_table, simulation, data, scale):
 
     # Sample from the selected table
     ID = int(mcdc_get.multi_table_distribution.table_IDs(idx, multi_table, data))
-    table_distribution = simulation["tabulated_distributions"][ID]
+    sub_ID = simulation["distributions"][ID]["sub_ID"]
+    table_distribution = simulation["tabulated_distributions"][sub_ID]
     sample = sample_tabulated(table_distribution, rng_state, simulation, data)
 
     # No scaling needed?
@@ -343,18 +345,27 @@ def _sample_multi_table(E, rng_state, multi_table, simulation, data, scale):
     if use_next_table:
         idx -= 1
 
-    # PDF table indices
+    # PDF tables
     ID0 = int(mcdc_get.multi_table_distribution.table_IDs(idx, multi_table, data))
     ID1 = int(mcdc_get.multi_table_distribution.table_IDs(idx + 1, multi_table, data))
     #
-    pdf_ID = table_distribution["pdf_ID"]
-    pdf_ID0 = simulation["tabulated_distributions"][ID0]["pdf_ID"]
-    pdf_ID1 = simulation["tabulated_distributions"][ID1]["pdf_ID"]
-
-    # The tables
-    table = simulation["table_data"][pdf_ID]
-    table0 = simulation["table_data"][pdf_ID0]
-    table1 = simulation["table_data"][pdf_ID1]
+    sub_ID0 = simulation["distributions"][ID0]["sub_ID"]
+    sub_ID1 = simulation["distributions"][ID1]["sub_ID"]
+    #
+    table_distribution0 = simulation["tabulated_distributions"][sub_ID0]
+    table_distribution1 = simulation["tabulated_distributions"][sub_ID1]
+    #
+    ID = table_distribution["pdf_ID"]
+    ID0 = table_distribution0["pdf_ID"]
+    ID1 = table_distribution1["pdf_ID"]
+    #
+    sub_ID = simulation["data"][ID]["sub_ID"]
+    sub_ID0 = simulation["data"][ID0]["sub_ID"]
+    sub_ID1 = simulation["data"][ID1]["sub_ID"]
+    #
+    table = simulation["table_data"][sub_ID]
+    table0 = simulation["table_data"][sub_ID0]
+    table1 = simulation["table_data"][sub_ID1]
 
     # Table's min
     val_min0 = mcdc_get.table_data.x(0, table0, data)
diff --git a/mcdc/transport/geometry/interface.py b/mcdc/transport/geometry/interface.py
index b225064de..f4c92ac56 100644
--- a/mcdc/transport/geometry/interface.py
+++ b/mcdc/transport/geometry/interface.py
@@ -138,6 +138,10 @@ def inspect_geometry(particle_container, simulation, data):
                 particle["y"] -= lattice["y0"] + (iy + 0.5) * lattice["dy"]
                 particle["z"] -= lattice["z0"] + (iz + 0.5) * lattice["dz"]
 
+            else:
+                # Unreached
+                universe_ID = -1
+
             # Get inner cell
             cell_ID = get_cell(particle_container, universe_ID, simulation, data)
             if cell_ID > -1:
@@ -244,6 +248,10 @@ def locate_particle(particle_container, simulation, data):
                 particle["y"] -= lattice["y0"] + (iy + 0.5) * lattice["dy"]
                 particle["z"] -= lattice["z0"] + (iz + 0.5) * lattice["dz"]
 
+            else:
+                # Unreached
+                universe_ID = -1
+
             # Get inner cell
             cell_ID = get_cell(particle_container, universe_ID, simulation, data)
             if cell_ID > -1:
diff --git a/mcdc/transport/physics/electron/native.py b/mcdc/transport/physics/electron/native.py
index 247d2f85b..5dd4b3ba9 100644
--- a/mcdc/transport/physics/electron/native.py
+++ b/mcdc/transport/physics/electron/native.py
@@ -25,7 +25,6 @@
 from mcdc.transport.data import evaluate_data
 from mcdc.transport.distribution import (
     sample_distribution,
-    sample_multi_table,
 )
 from mcdc.transport.physics.util import (
     evaluate_electron_xs_energy_grid,
@@ -91,18 +90,18 @@ def total_micro_xs(reaction_type, E, element, data):
 
 
 @njit
-def reaction_micro_xs(E, reaction_base, element, data):
+def reaction_micro_xs(E, reaction, element, data):
     idx, E0, E1 = evaluate_electron_xs_energy_grid(E, element, data)
 
     # Apply offset
-    offset = reaction_base["xs_offset_"]
+    offset = reaction["xs_offset_"]
     if idx < offset:
         return 0.0
     else:
         idx -= offset
 
-    xs0 = mcdc_get.electron_reaction.xs(idx, reaction_base, data)
-    xs1 = mcdc_get.electron_reaction.xs(idx + 1, reaction_base, data)
+    xs0 = mcdc_get.electron_reaction.xs(idx, reaction, data)
+    xs1 = mcdc_get.electron_reaction.xs(idx + 1, reaction, data)
     return linear_interpolation(E, E0, E1, xs0, xs1)
 
 
@@ -172,13 +171,11 @@ def collision(particle_container, collision_data_container, program, data):
             reaction_ID = int(
                 mcdc_get.element.electron_ionization_reaction_IDs(i, element, data)
             )
-            reaction = simulation["electron_ionization_reactions"][reaction_ID]
-            reaction_base_ID = reaction["base_ID"]
-            reaction_base = simulation["electron_reactions"][reaction_base_ID]
-            total += reaction_micro_xs(E, reaction_base, element, data)
+            reaction = simulation["electron_reactions"][reaction_ID]
+            total += reaction_micro_xs(E, reaction, element, data)
 
             if xi < total:
-                ionization(
+                sample_ionization(
                     reaction,
                     particle_container,
                     collision_data_container,
@@ -198,13 +195,11 @@ def collision(particle_container, collision_data_container, program, data):
                     i, element, data
                 )
             )
-            reaction = simulation["electron_elastic_scattering_reactions"][reaction_ID]
-            reaction_base_ID = reaction["base_ID"]
-            reaction_base = simulation["electron_reactions"][reaction_base_ID]
-            total += reaction_micro_xs(E, reaction_base, element, data)
+            reaction = simulation["electron_reactions"][reaction_ID]
+            total += reaction_micro_xs(E, reaction, element, data)
 
             if xi < total:
-                elastic_scattering(
+                sample_elastic_scattering(
                     reaction, particle_container, element, simulation, data
                 )
                 return
@@ -217,13 +212,11 @@ def collision(particle_container, collision_data_container, program, data):
             reaction_ID = int(
                 mcdc_get.element.electron_bremsstrahlung_reaction_IDs(i, element, data)
             )
-            reaction = simulation["electron_bremsstrahlung_reactions"][reaction_ID]
-            reaction_base_ID = reaction["base_ID"]
-            reaction_base = simulation["electron_reactions"][reaction_base_ID]
-            total += reaction_micro_xs(E, reaction_base, element, data)
+            reaction = simulation["electron_reactions"][reaction_ID]
+            total += reaction_micro_xs(E, reaction, element, data)
 
             if xi < total:
-                bremsstrahlung(
+                sample_bremsstrahlung(
                     reaction,
                     particle_container,
                     collision_data_container,
@@ -240,13 +233,11 @@ def collision(particle_container, collision_data_container, program, data):
             reaction_ID = int(
                 mcdc_get.element.electron_excitation_reaction_IDs(i, element, data)
             )
-            reaction = simulation["electron_excitation_reactions"][reaction_ID]
-            reaction_base_ID = reaction["base_ID"]
-            reaction_base = simulation["electron_reactions"][reaction_base_ID]
-            total += reaction_micro_xs(E, reaction_base, element, data)
+            reaction = simulation["electron_reactions"][reaction_ID]
+            total += reaction_micro_xs(E, reaction, element, data)
 
             if xi < total:
-                excitation(
+                sample_excitation(
                     reaction,
                     particle_container,
                     collision_data_container,
@@ -262,9 +253,12 @@ def collision(particle_container, collision_data_container, program, data):
 
 
 @njit
-def elastic_scattering(reaction, particle_container, element, simulation, data):
+def sample_elastic_scattering(reaction, particle_container, element, simulation, data):
     particle = particle_container[0]
 
+    sub_ID = reaction["sub_ID"]
+    elastic_scattering = simulation["electron_elastic_scattering_reactions"][sub_ID]
+
     # Current energy
     E = particle["E"]
 
@@ -272,12 +266,10 @@ def elastic_scattering(reaction, particle_container, element, simulation, data):
     # Total elastic xs
     # -------------------------------------------------------------------------
 
-    reaction_base_ID = int(reaction["base_ID"])
-    reaction_base = simulation["electron_reactions"][reaction_base_ID]
-    xs_total = reaction_micro_xs(E, reaction_base, element, data)
+    xs_total = reaction_micro_xs(E, reaction, element, data)
 
     # If large-angle, xs from data table
-    xs_large = elastic_large_xs(E, reaction, simulation, data)
+    xs_large = elastic_large_xs(E, elastic_scattering, simulation, data)
 
     # Important to check because of numerical issues
     if xs_large < 0.0:
@@ -286,7 +278,7 @@ def elastic_scattering(reaction, particle_container, element, simulation, data):
         xs_large = xs_total
 
     prob_large = xs_large / xs_total
-    mu_cut = float(reaction["mu_cut"])
+    mu_cut = float(elastic_scattering["mu_cut"])
 
     xi = rng.lcg(particle_container)
 
@@ -295,8 +287,12 @@ def elastic_scattering(reaction, particle_container, element, simulation, data):
         # Large-angle elastic scattering
         # ---------------------------------------------------------------------
 
-        multi_table = simulation["multi_table_distributions"][reaction["mu_ID"]]
-        mu0 = sample_multi_table(E, particle_container, multi_table, simulation, data)
+        mu_distribution = simulation["multi_table_distributions"][
+            elastic_scattering["mu_ID"]
+        ]
+        mu0 = sample_distribution(
+            E, mu_distribution, particle_container, simulation, data
+        )
 
     else:
         # ---------------------------------------------------------------------
@@ -348,8 +344,8 @@ def sample_small_angle_mu_coulomb(E, Z, rng_state, mu_cut):
 
 
 @njit
-def elastic_large_xs(E, reaction, simulation, data):
-    reaction_data = simulation["data"][int(reaction["xs_large_ID"])]
+def elastic_large_xs(E, elastic_scattering, simulation, data):
+    reaction_data = simulation["data"][int(elastic_scattering["xs_large_ID"])]
     return evaluate_data(E, reaction_data, simulation, data)
 
 
@@ -359,16 +355,19 @@ def elastic_large_xs(E, reaction, simulation, data):
 
 
 @njit
-def excitation(
+def sample_excitation(
     reaction, particle_container, collision_data_container, simulation, data
 ):
     particle = particle_container[0]
     collision_data = collision_data_container[0]
 
+    sub_ID = reaction["sub_ID"]
+    excitation = simulation["electron_excitation_reactions"][sub_ID]
+
     # Current energy
     E = particle["E"]
 
-    dE = evaluate_eloss(E, reaction, simulation, data)
+    dE = evaluate_eloss(E, excitation, simulation, data)
 
     # Calculate outgoing energy
     E_out = E - dE
@@ -397,16 +396,19 @@ def evaluate_eloss(E, reaction, simulation, data):
 
 
 @njit
-def bremsstrahlung(
+def sample_bremsstrahlung(
     reaction, particle_container, collision_data_container, simulation, data
 ):
     particle = particle_container[0]
     collision_data = collision_data_container[0]
 
+    sub_ID = reaction["sub_ID"]
+    bremsstrahlung = simulation["electron_bremsstrahlung_reactions"][sub_ID]
+
     # Current energy
     E = particle["E"]
 
-    dE = evaluate_eloss(E, reaction, simulation, data)
+    dE = evaluate_eloss(E, bremsstrahlung, simulation, data)
     E_out = E - dE
 
     # Check for cutoff
@@ -426,22 +428,25 @@ def bremsstrahlung(
 
 
 @njit
-def ionization(
+def sample_ionization(
     reaction, particle_container, collision_data_container, element, program, data
 ):
     simulation = util.access_simulation(program)
     particle = particle_container[0]
     collision_data = collision_data_container[0]
 
+    sub_ID = reaction["sub_ID"]
+    ionization = simulation["electron_ionization_reactions"][sub_ID]
+
     # Current energy
     E = particle["E"]
 
     # Sample subshell
-    N = int(reaction["N_subshell"])
+    N = int(ionization["N_subshell"])
     total = 0.0
     for i in range(N):
         xs_sub_ID = int(
-            mcdc_get.electron_ionization_reaction.subshell_x_IDs(i, reaction, data)
+            mcdc_get.electron_ionization_reaction.subshell_x_IDs(i, ionization, data)
         )
         xs_sub_table = simulation["data"][xs_sub_ID]
         total += evaluate_data(E, xs_sub_table, simulation, data)
@@ -451,7 +456,7 @@ def ionization(
     chosen = 0
     for i in range(N):
         xs_sub_ID = int(
-            mcdc_get.electron_ionization_reaction.subshell_x_IDs(i, reaction, data)
+            mcdc_get.electron_ionization_reaction.subshell_x_IDs(i, ionization, data)
         )
         xs_sub_table = simulation["data"][xs_sub_ID]
         total_acc += evaluate_data(E, xs_sub_table, simulation, data)
@@ -472,11 +477,11 @@ def ionization(
     # Sample secondary energy
     dist_ID = int(
         mcdc_get.electron_ionization_reaction.subshell_product_IDs(
-            chosen, reaction, data
+            chosen, ionization, data
         )
     )
-    dist_base = simulation["distributions"][dist_ID]
-    T_delta = sample_distribution(E, dist_base, particle_container, simulation, data)
+    T_dist = simulation["distributions"][dist_ID]
+    T_delta = sample_distribution(E, T_dist, particle_container, simulation, data)
 
     # Primary outgoing energy
     E_out = E - B - T_delta
diff --git a/mcdc/transport/physics/neutron/native.py b/mcdc/transport/physics/neutron/native.py
index 5cdf1f32e..b2aeca9a9 100644
--- a/mcdc/transport/physics/neutron/native.py
+++ b/mcdc/transport/physics/neutron/native.py
@@ -32,10 +32,10 @@
 from mcdc.transport.data import evaluate_data
 from mcdc.transport.distribution import (
     sample_correlated_distribution_with_scale,
+    sample_distribution,
     sample_distribution_with_scale,
     sample_isotropic_cosine,
     sample_isotropic_direction,
-    sample_multi_table,
 )
 from mcdc.transport.physics.util import (
     evaluate_neutron_xs_energy_grid,
@@ -115,18 +115,18 @@ def total_micro_xs(reaction_type, E, nuclide, data):
 
 
 @njit
-def reaction_micro_xs(E, reaction_base, nuclide, data):
+def reaction_micro_xs(E, reaction, nuclide, data):
     idx, E0, E1 = evaluate_neutron_xs_energy_grid(E, nuclide, data)
 
     # Apply offset
-    offset = reaction_base["xs_offset_"]
+    offset = reaction["xs_offset_"]
     if idx < offset:
         return 0.0
     else:
         idx -= offset
 
-    xs0 = mcdc_get.neutron_reaction.xs(idx, reaction_base, data)
-    xs1 = mcdc_get.neutron_reaction.xs(idx + 1, reaction_base, data)
+    xs0 = mcdc_get.neutron_reaction.xs(idx, reaction, data)
+    xs1 = mcdc_get.neutron_reaction.xs(idx + 1, reaction, data)
     return linear_interpolation(E, E0, E1, xs0, xs1)
 
 
@@ -188,10 +188,9 @@ def _neutron_inelastic_scattering_production_xs(particle_container, simulation,
                     j, nuclide, data
                 )
             )
-            reaction = simulation["neutron_inelastic_scattering_reactions"][reaction_ID]
-            reaction_base = simulation["neutron_reactions"][reaction["base_ID"]]
+            reaction = simulation["neutron_reactions"][reaction_ID]
 
-            xs = reaction_micro_xs(E, reaction_base, nuclide, data)
+            xs = reaction_micro_xs(E, reaction, nuclide, data)
             nu = reaction["multiplicity"]
             total += nuclide_density * nu * xs
 
@@ -221,10 +220,9 @@ def _neutron_fission_production_xs(particle_container, simulation, data):
             reaction_ID = int(
                 mcdc_get.nuclide.neutron_fission_reaction_IDs(j, nuclide, data)
             )
-            reaction = simulation["neutron_fission_reactions"][reaction_ID]
-            reaction_base = simulation["neutron_reactions"][reaction["base_ID"]]
+            reaction = simulation["neutron_reactions"][reaction_ID]
 
-            xs = reaction_micro_xs(E, reaction_base, nuclide, data)
+            xs = reaction_micro_xs(E, reaction, nuclide, data)
             nu_p = neutron_fission_prompt_multiplicity(E, nuclide, simulation, data)
             nu_d = neutron_fission_delayed_multiplicity(E, nuclide, simulation, data)
             nu = nu_d + nu_p
@@ -276,13 +274,11 @@ def collision(particle_container, collision_data_container, program, data):
                 reaction_ID = int(
                     mcdc_get.nuclide.neutron_capture_reaction_IDs(j, nuclide, data)
                 )
-                reaction = simulation["neutron_capture_reactions"][reaction_ID]
-                reaction_base_ID = reaction["base_ID"]
-                reaction_base = simulation["neutron_reactions"][reaction_base_ID]
-                xs = reaction_micro_xs(E, reaction_base, nuclide, data)
+                reaction = simulation["neutron_reactions"][reaction_ID]
+                xs = reaction_micro_xs(E, reaction, nuclide, data)
                 Sigma_rx = nuclide_density * xs
                 collision_data["energy_deposition"] += (
-                    reaction_base["q_value"] * 1e6 * particle["w"] * Sigma_rx / SigmaT
+                    reaction["q_value"] * 1e6 * particle["w"] * Sigma_rx / SigmaT
                 )
 
         # Capture particle weight
@@ -335,14 +331,12 @@ def collision(particle_container, collision_data_container, program, data):
                     i, nuclide, data
                 )
             )
-            reaction = simulation["neutron_elastic_scattering_reactions"][reaction_ID]
-            reaction_base_ID = reaction["base_ID"]
-            reaction_base = simulation["neutron_reactions"][reaction_base_ID]
-            total += reaction_micro_xs(E, reaction_base, nuclide, data)
+            reaction = simulation["neutron_reactions"][reaction_ID]
+            total += reaction_micro_xs(E, reaction, nuclide, data)
 
             # Execute the reaction
             if xi < total:
-                elastic_scattering(
+                sample_elastic_scattering(
                     reaction,
                     particle_container,
                     collision_data_container,
@@ -363,10 +357,8 @@ def collision(particle_container, collision_data_container, program, data):
                 reaction_ID = int(
                     mcdc_get.nuclide.neutron_capture_reaction_IDs(i, nuclide, data)
                 )
-                reaction = simulation["neutron_capture_reactions"][reaction_ID]
-                reaction_base_ID = reaction["base_ID"]
-                reaction_base = simulation["neutron_reactions"][reaction_base_ID]
-                xs = reaction_micro_xs(E, reaction_base, nuclide, data)
+                reaction = simulation["neutron_reactions"][reaction_ID]
+                xs = reaction_micro_xs(E, reaction, nuclide, data)
                 total += xs
 
                 # Execute the reaction
@@ -392,15 +384,13 @@ def collision(particle_container, collision_data_container, program, data):
                     i, nuclide, data
                 )
             )
-            reaction = simulation["neutron_inelastic_scattering_reactions"][reaction_ID]
-            reaction_base_ID = reaction["base_ID"]
-            reaction_base = simulation["neutron_reactions"][reaction_base_ID]
-            xs = reaction_micro_xs(E, reaction_base, nuclide, data)
+            reaction = simulation["neutron_reactions"][reaction_ID]
+            xs = reaction_micro_xs(E, reaction, nuclide, data)
             total += xs
 
             # Execute the reaction
             if xi < total:
-                inelastic_scattering(
+                sample_inelastic_scattering(
                     reaction,
                     particle_container,
                     collision_data_container,
@@ -419,14 +409,12 @@ def collision(particle_container, collision_data_container, program, data):
             reaction_ID = int(
                 mcdc_get.nuclide.neutron_fission_reaction_IDs(i, nuclide, data)
             )
-            reaction = simulation["neutron_fission_reactions"][reaction_ID]
-            reaction_base_ID = reaction["base_ID"]
-            reaction_base = simulation["neutron_reactions"][reaction_base_ID]
-            total += reaction_micro_xs(E, reaction_base, nuclide, data)
+            reaction = simulation["neutron_reactions"][reaction_ID]
+            total += reaction_micro_xs(E, reaction, nuclide, data)
 
             # Execute the reaction
             if xi < total:
-                fission(
+                sample_fission(
                     reaction,
                     particle_container,
                     collision_data_container,
@@ -449,15 +437,12 @@ def capture(
     particle = particle_container[0]
     collision_data = collision_data_container[0]
 
-    reaction_base_ID = reaction["base_ID"]
-    reaction_base = simulation["neutron_reactions"][reaction_base_ID]
-
     # Terminate the particle
     particle["alive"] = False
 
     # Energy deposition
     E = particle["E"]
-    q_value = reaction_base["q_value"] * 1e6
+    q_value = reaction["q_value"] * 1e6
     collision_data["energy_deposition"] += (E + q_value) * particle["w"]
 
 
@@ -467,11 +452,13 @@ def capture(
 
 
 @njit
-def elastic_scattering(
+def sample_elastic_scattering(
     reaction, particle_container, collision_data_container, nuclide, simulation, data
 ):
     particle = particle_container[0]
     collision_data = collision_data_container[0]
+    sub_ID = reaction["sub_ID"]
+    elastic_scattering = simulation["neutron_elastic_scattering_reactions"][sub_ID]
 
     # Particle attributes
     E = particle["E"]
@@ -524,8 +511,8 @@ def elastic_scattering(
     uz = vz / speed
 
     # Sample the scattering cosine from the multi-PDF distribution
-    multi_table = simulation["multi_table_distributions"][reaction["mu_table_ID"]]
-    mu0 = sample_multi_table(E, particle_container, multi_table, simulation, data)
+    mu_distribution = simulation["distributions"][elastic_scattering["mu_table_ID"]]
+    mu0 = sample_distribution(E, mu_distribution, particle_container, simulation, data)
 
     # Scatter the direction in COM
     azi = 2.0 * PI * rng.lcg(particle_container)
@@ -612,15 +599,14 @@ def sample_nucleus_velocity(A, particle_container):
 
 
 @njit
-def inelastic_scattering(
+def sample_inelastic_scattering(
     reaction, particle_container, collision_data_container, nuclide, program, data
 ):
     simulation = util.access_simulation(program)
     particle = particle_container[0]
     collision_data = collision_data_container[0]
-
-    reaction_base_ID = reaction["base_ID"]
-    reaction_base = simulation["neutron_reactions"][reaction_base_ID]
+    sub_ID = reaction["sub_ID"]
+    inelastic_scattering = simulation["neutron_inelastic_scattering_reactions"][sub_ID]
 
     # Particle attributes
     E = particle["E"]
@@ -632,12 +618,12 @@ def inelastic_scattering(
     particle["alive"] = False
 
     # Energy deposition
-    q_value = reaction_base["q_value"] * 1e6
+    q_value = reaction["q_value"] * 1e6
     collision_data["energy_deposition"] += (E + q_value) * particle["w"]
 
     # Number of secondaries and spectra
-    N = reaction["multiplicity"]
-    N_spectrum = reaction["N_spectrum"]
+    N = inelastic_scattering["multiplicity"]
+    N_spectrum = inelastic_scattering["N_spectrum"]
     use_all_spectrum = N == N_spectrum
 
     # Set up secondary partice container
@@ -653,18 +639,15 @@ def inelastic_scattering(
         # Sample angle (if not energy-correlated)
         # ==============================================================================
 
-        angle_type = reaction["angle_type"]
+        angle_type = inelastic_scattering["angle_type"]
         if angle_type == ANGLE_ENERGY_CORRELATED:
             pass
         elif angle_type == ANGLE_ISOTROPIC:
             mu = sample_isotropic_cosine(particle_container_new)
         elif angle_type == ANGLE_DISTRIBUTED:
-            distribution_base = simulation["distributions"][reaction["mu_ID"]]
-            multi_table = simulation["multi_table_distributions"][
-                distribution_base["sub_ID"]
-            ]
-            mu = sample_multi_table(
-                E, particle_container_new, multi_table, simulation, data
+            mu_distribution = simulation["distributions"][inelastic_scattering["mu_ID"]]
+            mu = sample_distribution(
+                E, mu_distribution, particle_container_new, simulation, data
             )
 
         # ==============================================================================
@@ -675,17 +658,17 @@ def inelastic_scattering(
         if use_all_spectrum:
             ID = int(
                 mcdc_get.neutron_inelastic_scattering_reaction.energy_spectrum_IDs(
-                    n, reaction, data
+                    n, inelastic_scattering, data
                 )
             )
-            spectrum_base = simulation["distributions"][ID]
+            spectrum = simulation["distributions"][ID]
         else:
-            offset = reaction["spectrum_probability_grid_offset"]
-            length = reaction["spectrum_probability_grid_length"]
+            offset = inelastic_scattering["spectrum_probability_grid_offset"]
+            length = inelastic_scattering["spectrum_probability_grid_length"]
             probability_grid = data[offset : offset + length]
             # Above is equivalent to:
             # probability_grid = mcdc_get.neutron_inelastic_scattering_reaction.spectrum_probability_grid_all(
-            #     reaction, data
+            #     inelastic_scattering, data
             # )
             probability_idx = find_bin(E, probability_grid)
             xi = rng.lcg(particle_container_new)
@@ -693,35 +676,34 @@ def inelastic_scattering(
             for j in range(N_spectrum):
                 probability = (
                     mcdc_get.neutron_inelastic_scattering_reaction.spectrum_probability(
-                        probability_idx, j, reaction, data
+                        probability_idx, j, inelastic_scattering, data
                     )
                 )
                 total += probability
                 if xi < total:
                     ID = int(
                         mcdc_get.neutron_inelastic_scattering_reaction.energy_spectrum_IDs(
-                            j, reaction, data
+                            j, inelastic_scattering, data
                         )
                     )
-                    spectrum_base = simulation["distributions"][ID]
+                    spectrum = simulation["distributions"][ID]
                     break
 
         # Sample energy
         if not angle_type == ANGLE_ENERGY_CORRELATED:
             E_new = sample_distribution_with_scale(
-                E, spectrum_base, particle_container_new, simulation, data
+                E, spectrum, particle_container_new, simulation, data
             )
         else:
             E_new, mu = sample_correlated_distribution_with_scale(
-                E, spectrum_base, particle_container_new, simulation, data
+                E, spectrum, particle_container_new, simulation, data
             )
 
         # ==============================================================================
         # Frame transformation
         # ==============================================================================
 
-        reaction_base = simulation["neutron_reactions"][int(reaction["base_ID"])]
-        reference_frame = reaction_base["reference_frame"]
+        reference_frame = reaction["reference_frame"]
         if reference_frame == REFERENCE_FRAME_COM:
             A = nuclide["atomic_weight_ratio"]
             mu_COM = mu
@@ -765,17 +747,17 @@ def inelastic_scattering(
 
 
 @njit
-def fission(
+def sample_fission(
     reaction, particle_container, collision_data_container, nuclide, program, data
 ):
     simulation = util.access_simulation(program)
     particle = particle_container[0]
     collision_data = collision_data_container[0]
 
-    settings = simulation["settings"]
+    sub_ID = reaction["sub_ID"]
+    fission = simulation["neutron_fission_reactions"][sub_ID]
 
-    reaction_base_ID = reaction["base_ID"]
-    reaction_base = simulation["neutron_reactions"][reaction_base_ID]
+    settings = simulation["settings"]
 
     # Particle properties
     E = particle["E"]
@@ -788,7 +770,7 @@ def fission(
 
     # Energy deposition
     #   TODO: Use energy-dependent Q-value
-    q_value = reaction_base["q_value"] * 1e6
+    q_value = reaction["q_value"] * 1e6
     collision_data["energy_deposition"] += (E + q_value) * particle["w"]
 
     # Adjust production and product weights if weighted emission
@@ -847,26 +829,23 @@ def fission(
 
         if prompt:
             # Sample angle (if not energy-correlated)
-            angle_type = reaction["angle_type"]
+            angle_type = fission["angle_type"]
             if angle_type == ANGLE_ENERGY_CORRELATED:
                 pass
             elif angle_type == ANGLE_ISOTROPIC:
                 mu = sample_isotropic_cosine(particle_container_new)
             elif angle_type == ANGLE_DISTRIBUTED:
-                distribution_base = simulation["distributions"][reaction["mu_ID"]]
-                multi_table = simulation["multi_table_distributions"][
-                    distribution_base["sub_ID"]
-                ]
-                mu = sample_multi_table(
-                    E, particle_container_new, multi_table, simulation, data
+                mu_distribution = simulation["distributions"][fission["mu_ID"]]
+                mu = sample_distribution(
+                    E, mu_distribution, particle_container_new, simulation, data
                 )
 
             # Sample energy (also angle if correlated)
-            spectrum_base = simulation["distributions"][reaction["spectrum_ID"]]
+            spectrum = simulation["distributions"][fission["spectrum_ID"]]
             if not angle_type == ANGLE_ENERGY_CORRELATED:
                 E_new = sample_distribution_with_scale(
                     E,
-                    spectrum_base,
+                    spectrum,
                     particle_container_new,
                     simulation,
                     data,
@@ -874,15 +853,14 @@ def fission(
             else:
                 E_new, mu = sample_correlated_distribution_with_scale(
                     E,
-                    spectrum_base,
+                    spectrum,
                     particle_container_new,
                     simulation,
                     data,
                 )
 
             # Frame transformation
-            reaction_base = simulation["neutron_reactions"][int(reaction["base_ID"])]
-            reference_frame = reaction_base["reference_frame"]
+            reference_frame = reaction["reference_frame"]
             if reference_frame == REFERENCE_FRAME_COM:
                 A = nuclide["atomic_weight_ratio"]
                 mu_COM = mu
diff --git a/mcdc/transport/simulation.py b/mcdc/transport/simulation.py
index 1232c73bd..f4b01cb65 100644
--- a/mcdc/transport/simulation.py
+++ b/mcdc/transport/simulation.py
@@ -302,8 +302,8 @@ def step_particle(particle_container, program, data):
             cell = simulation["cells"][particle["cell_ID"]]
             for i in range(cell["N_collision_tally"]):
                 tally_ID = int(mcdc_get.cell.collision_tally_IDs(i, cell, data))
-                tally = simulation["collision_tallies"][tally_ID]
-                tally_module.score.collision_tally(
+                tally = simulation["tallies"][tally_ID]
+                tally_module.score.collision(
                     particle_container,
                     collision_data_container,
                     tally,
@@ -431,8 +431,8 @@ def move_to_event(particle_container, simulation, data):
         cell = simulation["cells"][particle["cell_ID"]]
         for i in range(cell["N_tracklength_tally"]):
             tally_ID = int(mcdc_get.cell.tracklength_tally_IDs(i, cell, data))
-            tally = simulation["tracklength_tallies"][tally_ID]
-            tally_module.score.tracklength_tally(
+            tally = simulation["tallies"][tally_ID]
+            tally_module.score.tracklength(
                 particle_container, distance, tally, simulation, data
             )
 
@@ -446,29 +446,29 @@ def move_to_event(particle_container, simulation, data):
 
 
 @njit
-def surface_crossing(P_arr, simulation, data):
-    P = P_arr[0]
-    crossed_surface_ID = P["surface_ID"]
+def surface_crossing(particle_container, simulation, data):
+    particle = particle_container[0]
+    crossed_surface_ID = particle["surface_ID"]
 
     surface = simulation["surfaces"][crossed_surface_ID]
     BC = surface["boundary_condition"]
 
     # Apply BC
     if BC == BC_VACUUM:
-        P["alive"] = False
+        particle["alive"] = False
     elif BC == BC_REFLECTIVE:
-        surface_module.reflect(P_arr, surface)
+        surface_module.reflect(particle_container, surface)
         return  # No score
 
     # Score tally
     for i in range(surface["N_tally"]):
         tally_ID = int(mcdc_get.surface.surface_crossing_tally_IDs(i, surface, data))
-        tally = simulation["surface_crossing_tallies"][tally_ID]
-        tally_module.score.surface_crossing_tally(
-            P_arr, surface, tally, simulation, data
+        tally = simulation["tallies"][tally_ID]
+        tally_module.score.surface_crossing(
+            particle_container, surface, tally, simulation, data
         )
 
     # Flag to check new cell later
-    if P["alive"]:
-        P["cell_ID"] = -1
-        P["material_ID"] = -1
+    if particle["alive"]:
+        particle["cell_ID"] = -1
+        particle["material_ID"] = -1
diff --git a/mcdc/transport/tally/score.py b/mcdc/transport/tally/score.py
index 8b5ce9ce3..09f9a4889 100644
--- a/mcdc/transport/tally/score.py
+++ b/mcdc/transport/tally/score.py
@@ -33,20 +33,21 @@
 from mcdc.transport.tally.filter import get_filter_indices
 
 # ======================================================================================
-# Surface crossing tally
+# Surface-crossing
 # ======================================================================================
 
 
 @njit
-def surface_crossing_tally(
+def surface_crossing(
     particle_container,
     surface,
-    surface_crossing_tally,
+    tally,
     simulation,
     data,
 ):
     particle = particle_container[0]
-    tally = simulation["tallies"][surface_crossing_tally["base_ID"]]
+    sub_ID = tally["sub_ID"]
+    surface_crossing_tally = simulation["surface_crossing_tallies"][sub_ID]
 
     # Get filter indices
     MG_mode = simulation["settings"]["neutron_multigroup_mode"]
@@ -118,17 +119,16 @@ def surface_crossing_tally(
 
 
 # ======================================================================================
-# Collision tally
+# Collision
 # ======================================================================================
 
 
 @njit
-def collision_tally(
-    particle_container, collision_data_container, collision_tally, simulation, data
-):
+def collision(particle_container, collision_data_container, tally, simulation, data):
     particle = particle_container[0]
     collision_data = collision_data_container[0]
-    tally = simulation["tallies"][collision_tally["base_ID"]]
+    sub_ID = tally["sub_ID"]
+    collision_tally = simulation["collision_tallies"][sub_ID]
 
     # Get filter indices
     MG_mode = simulation["settings"]["neutron_multigroup_mode"]
@@ -182,11 +182,10 @@ def collision_tally(
 
 
 @njit
-def tracklength_tally(
-    particle_container, distance, tracklength_tally, simulation, data
-):
+def tracklength(particle_container, distance, tally, simulation, data):
     particle = particle_container[0]
-    tally = simulation["tallies"][tracklength_tally["base_ID"]]
+    sub_ID = tally["sub_ID"]
+    tracklength_tally = simulation["tracklength_tallies"][sub_ID]
 
     # Get filter indices
     MG_mode = simulation["settings"]["neutron_multigroup_mode"]

From 021326c738b008ba4de2f69764d77c96ca007ae6 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 11:41:46 +0700
Subject: [PATCH 042/202] debug for numba mode

---
 mcdc/transport/distribution.py            | 4 ++--
 mcdc/transport/physics/electron/native.py | 4 +---
 mcdc/transport/simulation.py              | 2 +-
 3 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/mcdc/transport/distribution.py b/mcdc/transport/distribution.py
index 15cec02f4..4583f195b 100644
--- a/mcdc/transport/distribution.py
+++ b/mcdc/transport/distribution.py
@@ -388,7 +388,7 @@ def _sample_multi_table(E, rng_state, multi_table, simulation, data, scale):
 @njit
 def sample_maxwellian(E, rng_state, maxwellian, simulation, data):
     # Get nuclear temperature
-    table = simulation["table_data"][maxwellian["nuclear_temperature_ID"]]
+    table = simulation["data"][maxwellian["nuclear_temperature_ID"]]
     nuclear_temperature = evaluate_data(E, table, simulation, data)
     restriction_energy = maxwellian["restriction_energy"]
 
@@ -418,7 +418,7 @@ def sample_level_scattering(E, level_scattering):
 @njit
 def sample_evaporation(E, rng_state, evaporation, simulation, data):
     # Get nuclear temperature
-    table = simulation["table_data"][evaporation["nuclear_temperature_ID"]]
+    table = simulation["data"][evaporation["nuclear_temperature_ID"]]
     nuclear_temperature = evaluate_data(E, table, simulation, data)
     restriction_energy = evaporation["restriction_energy"]
 
diff --git a/mcdc/transport/physics/electron/native.py b/mcdc/transport/physics/electron/native.py
index 5dd4b3ba9..170add771 100644
--- a/mcdc/transport/physics/electron/native.py
+++ b/mcdc/transport/physics/electron/native.py
@@ -287,9 +287,7 @@ def sample_elastic_scattering(reaction, particle_container, element, simulation,
         # Large-angle elastic scattering
         # ---------------------------------------------------------------------
 
-        mu_distribution = simulation["multi_table_distributions"][
-            elastic_scattering["mu_ID"]
-        ]
+        mu_distribution = simulation["distributions"][elastic_scattering["mu_ID"]]
         mu0 = sample_distribution(
             E, mu_distribution, particle_container, simulation, data
         )
diff --git a/mcdc/transport/simulation.py b/mcdc/transport/simulation.py
index f4b01cb65..7d949acec 100644
--- a/mcdc/transport/simulation.py
+++ b/mcdc/transport/simulation.py
@@ -461,7 +461,7 @@ def surface_crossing(particle_container, simulation, data):
         return  # No score
 
     # Score tally
-    for i in range(surface["N_tally"]):
+    for i in range(surface["N_surface_crossing_tally"]):
         tally_ID = int(mcdc_get.surface.surface_crossing_tally_IDs(i, surface, data))
         tally = simulation["tallies"][tally_ID]
         tally_module.score.surface_crossing(

From 168ad1fedf2419bf04820082ea87583556bb81db Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 14:15:33 +0700
Subject: [PATCH 043/202] update docs

---
 docs/source/pythonapi/index.rst   |   9 +-
 mcdc/object_/base.py              |  22 ++++
 mcdc/object_/cell.py              |  87 ++++++++++++++++
 mcdc/object_/data.py              |  35 +++++++
 mcdc/object_/distribution.py      |  59 +++++++++++
 mcdc/object_/electron_reaction.py |  22 ++++
 mcdc/object_/element.py           |  14 +++
 mcdc/object_/gpu_tools.py         |   2 +
 mcdc/object_/material.py          | 132 ++++++++++++++++++++++++
 mcdc/object_/mesh.py              |  69 +++++++++++++
 mcdc/object_/neutron_reaction.py  |  26 +++++
 mcdc/object_/nuclide.py           |  25 +++++
 mcdc/object_/particle.py          |  15 +++
 mcdc/object_/settings.py          |  52 ++++++++++
 mcdc/object_/simulation.py        |  98 ++++++++++++++++++
 mcdc/object_/source.py            |  30 +++---
 mcdc/object_/surface.py           | 164 ++++++++++++++++++++++++++++++
 mcdc/object_/tally.py             | 134 ++++++++++++++++++++++++
 mcdc/object_/technique.py         |  37 +++++++
 mcdc/object_/universe.py          |  89 ++++++++++++++++
 mcdc/object_/util.py              |  24 +++++
 21 files changed, 1126 insertions(+), 19 deletions(-)

diff --git a/docs/source/pythonapi/index.rst b/docs/source/pythonapi/index.rst
index f3a8ed46f..57b28006a 100644
--- a/docs/source/pythonapi/index.rst
+++ b/docs/source/pythonapi/index.rst
@@ -92,16 +92,15 @@ Techniques are enabled by calling methods on the ``mcdc.simulation`` singleton:
 - ``mcdc.simulation.weighted_emission(active=True, weight_target=1.0)``
 - ``mcdc.simulation.weight_windows(weight_windows, mesh=None, energy=None)``
 
-Running
--------
+Running simulations
+-------------------
 
 .. autosummary::
    :toctree: generated
    :nosignatures:
-   :template: omcfunction.rst
-
-   mcdc.run
+   :template: omcclass.rst
 
+   mcdc.Simulation
 
 
 
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index 062137518..25aa5dd20 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -2,6 +2,13 @@
 
 
 class MCDCBase:
+    """Base class for Python-side MC/DC model and runtime objects.
+
+    Subclasses declare a :attr:`label` and type-annotated fields. Assignments to
+    annotated fields are checked at runtime so invalid model data is rejected
+    before the simulation is packed for transport.
+    """
+
     label: str
 
     def __init_subclass__(cls):
@@ -18,6 +25,14 @@ def __setattr__(self, key, value):
 
 
 class MCDCObject(MCDCBase):
+    """Base class for model objects registered during simulation compilation.
+
+    ``ID`` identifies an object in its heterogeneous simulation collection.
+    ``compile_ID`` records the compilation pass in which the object was most
+    recently registered, preventing duplicate registration when objects are
+    shared by multiple parts of a model.
+    """
+
     # MC/DC framework metadata
     label = "object"
 
@@ -44,6 +59,13 @@ def _compile_into_simulation(self, simulation) -> bool:
 
 
 class MCDCPolymorphic(MCDCObject):
+    """Base class for model objects with multiple packed representations.
+
+    In addition to the global :attr:`~MCDCObject.ID`, polymorphic objects carry
+    a subtype code and a subtype-local ``sub_ID``. The transport kernels use
+    these values to dispatch to the correct packed object representation.
+    """
+
     # MC/DC framework metadata
     label = "polymorphic"
 
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 46c39cbc0..a1bffd266 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -40,6 +40,14 @@
 
 
 class Region:
+    """Boolean combination of oriented surface half-spaces.
+
+    Regions are normally built with unary ``+`` and ``-`` on
+    :class:`~mcdc.object_.surface.Surface` objects, followed by ``&`` (intersection),
+    ``|`` (union), and ``~`` (complement). During compilation, the expression is
+    converted to reverse Polish notation for evaluation by the geometry kernels.
+    """
+
     type: str
     A: Surface | Region | NoneType
     B: Region | int | NoneType
@@ -51,6 +59,21 @@ def __init__(self, type_, A, B):
 
     @classmethod
     def make_halfspace(cls, surface, sense):
+        """Create the positive or negative half-space of a surface.
+
+        Parameters
+        ----------
+        surface : Surface
+            Bounding surface.
+        sense : int
+            Positive for the positive half-space and negative for the negative
+            half-space.
+
+        Returns
+        -------
+        Region
+            Half-space region used to build a cell expression.
+        """
         region = Region("halfspace", surface, sense)
         return region
 
@@ -73,6 +96,63 @@ def __repr__(self):
 
 
 class Cell(MCDCObject):
+    """Define a geometric region and the object that fills it.
+
+    Parameters
+    ----------
+    region : Region, optional
+        Boolean region expression. If omitted, the cell covers all space.
+    fill : MaterialBase, Universe, Lattice, or None, optional
+        Material or nested geometry placed in the cell. ``None`` creates a void
+        cell.
+    name : str, optional
+        User-facing name. An automatic name is assigned during compilation when
+        omitted.
+    translation : sequence of 3 float, optional
+        Translation, in cm, applied when entering a universe or lattice fill.
+    rotation : sequence of 3 float, optional
+        Rotation angles about the x, y, and z axes, in degrees, applied when
+        entering a universe or lattice fill.
+
+    Notes
+    -----
+    A cell region is commonly written as ``+left & -right``. Surface signs select
+    half-spaces; intersections, unions, and complements may be combined freely.
+
+    Examples
+    --------
+    Fill a slab between two z planes with a one-group material:
+
+    >>> import numpy as np
+    >>> import mcdc
+    >>> material = mcdc.MaterialMG(capture=np.array([1.0]))
+    >>> lower = mcdc.Surface.PlaneZ(z=0.0)
+    >>> upper = mcdc.Surface.PlaneZ(z=2.0)
+    >>> cell = mcdc.Cell(region=+lower & -upper, fill=material)
+
+    Create a void cell outside the slab:
+
+    >>> void = mcdc.Cell(name="Upper void", region=+upper)
+
+    Combine regions with a union:
+
+    >>> left_sphere = mcdc.Surface.Sphere(center=[-1.0, 0.0, 0.0], radius=0.5)
+    >>> right_sphere = mcdc.Surface.Sphere(center=[1.0, 0.0, 0.0], radius=0.5)
+    >>> two_spheres = mcdc.Cell(
+    ...     region=-left_sphere | -right_sphere,
+    ...     fill=material,
+    ... )
+
+    Place a reusable universe with a translation and rotation:
+
+    >>> assembly = mcdc.Universe(name="Assembly", cells=[cell])
+    >>> placed_assembly = mcdc.Cell(
+    ...     fill=assembly,
+    ...     translation=[5.0, 0.0, 0.0],
+    ...     rotation=[0.0, 0.0, 90.0],
+    ... )
+    """
+
     # MC/DC framework metadata
     label = "cell"
     non_numba = ["region", "region_RPN", "fill"]
@@ -192,6 +272,11 @@ def __repr__(self):
 
 
 def generate_RPN_tokens(region, simulation):
+    """Compile a region expression into geometry-kernel RPN tokens.
+
+    Surface objects encountered in the expression are registered with
+    ``simulation`` as part of this operation.
+    """
     from mcdc.object_.surface import Surface
 
     # The RPN tokens
@@ -255,6 +340,7 @@ def generate_RPN_tokens(region, simulation):
 
 
 def generate_RPN(rpn_tokens):
+    """Convert region RPN tokens to a simplified SymPy Boolean expression."""
     stack = []
 
     for token in rpn_tokens:
@@ -280,6 +366,7 @@ def generate_RPN(rpn_tokens):
 
 
 def list_surfaces(rpn_tokens, simulation):
+    """Return the registered surfaces referenced by a token sequence."""
     surfaces = []
 
     for token in rpn_tokens:
diff --git a/mcdc/object_/data.py b/mcdc/object_/data.py
index 8b6b2aa98..4babd704c 100644
--- a/mcdc/object_/data.py
+++ b/mcdc/object_/data.py
@@ -25,6 +25,8 @@
 
 
 class DataBase(MCDCPolymorphic):
+    """Base class for scalar data evaluated by transport kernels."""
+
     # MC/DC framework metadata
     label = "data"
     sub_type = -1  # Polymorphic base
@@ -38,6 +40,8 @@ class DataBase(MCDCPolymorphic):
 
 
 class DataNone(DataBase):
+    """Placeholder used when a reaction has no associated evaluable data."""
+
     # MC/DC framework metadata
     label = "none_data"
     sub_type = DATA_NONE
@@ -49,6 +53,25 @@ class DataNone(DataBase):
 
 
 class DataTable(DataBase):
+    """One-dimensional table with one or more interpolation regions.
+
+    Parameters
+    ----------
+    x, y : ndarray
+        One-dimensional abscissa and ordinate arrays of equal nonzero length.
+    interpolations : int or sequence of int
+        Packed interpolation code for each region. A scalar applies to the full
+        table.
+    interpolation_boundaries : sequence of int, optional
+        Exclusive end index of each interpolation region. Required when
+        ``interpolations`` contains multiple codes; the final value must equal
+        ``len(x)``.
+    aux : ndarray, optional
+        Additional values aligned with ``x``. A one-dimensional array is stored
+        as one auxiliary row; a two-dimensional array must have shape
+        ``(N_aux, len(x))``.
+    """
+
     # MC/DC framework metadata
     label = "table_data"
     sub_type = DATA_TABLE
@@ -200,6 +223,8 @@ def __repr__(self) -> str:
 
 
 def decode_interpolation(type_: int) -> str:
+    """Return the name associated with a packed interpolation code."""
+
     if type_ == INTERPOLATION_HISTOGRAM:
         return "histogram"
     if type_ == INTERPOLATION_LINEAR:
@@ -215,6 +240,8 @@ def decode_interpolation(type_: int) -> str:
 
 
 def encode_interpolation(name: str) -> int:
+    """Return the packed code associated with an interpolation name."""
+
     if name == "histogram":
         return INTERPOLATION_HISTOGRAM
     if name == "linear":
@@ -235,6 +262,14 @@ def encode_interpolation(name: str) -> int:
 
 
 class DataPolynomial(DataBase):
+    """Polynomial coefficients evaluated in ascending power order.
+
+    Parameters
+    ----------
+    coefficients : ndarray
+        One-dimensional coefficient array.
+    """
+
     # MC/DC framework metadata
     label = "polynomial_data"
     sub_type = DATA_POLYNOMIAL
diff --git a/mcdc/object_/distribution.py b/mcdc/object_/distribution.py
index c4463d245..ca9adbc73 100644
--- a/mcdc/object_/distribution.py
+++ b/mcdc/object_/distribution.py
@@ -34,6 +34,8 @@
 
 
 class DistributionBase(MCDCPolymorphic):
+    """Base class for probability distributions sampled during transport."""
+
     # MC/DC framework metadata
     label = "distribution"
     sub_type = -1  # Polymorphic base
@@ -48,6 +50,8 @@ class DistributionBase(MCDCPolymorphic):
 
 
 class DistributionNone(DistributionBase):
+    """Placeholder for an implicit or externally stored distribution."""
+
     # MC/DC framework metadata
     label = "none_distribution"
     sub_type = DISTRIBUTION_NONE
@@ -59,6 +63,16 @@ class DistributionNone(DistributionBase):
 
 
 class DistributionPMF(DistributionBase):
+    """Discrete probability mass function.
+
+    Parameters
+    ----------
+    value : array_like
+        Values that may be sampled.
+    pmf : array_like
+        Nonnegative relative masses, normalized internally.
+    """
+
     # MC/DC framework metadata
     label = "pmf_distribution"
     sub_type = DISTRIBUTION_PMF
@@ -98,6 +112,13 @@ def __repr__(self) -> str:
 
 
 class DistributionTabulated(DistributionBase):
+    """One-dimensional continuous tabulated distribution.
+
+    Exactly one of ``pdf`` or ``cdf`` must be supplied alongside ``value``.
+    PDF input is treated as piecewise linear; CDF input produces a histogram
+    density. The distribution is normalized internally.
+    """
+
     # MC/DC framework metadata
     label = "tabulated_distribution"
     sub_type = DISTRIBUTION_TABULATED
@@ -171,6 +192,12 @@ def __repr__(self) -> str:
 
 
 class DistributionMultiTable(DistributionBase):
+    """Family of tabulated distributions indexed by another grid.
+
+    ``offset`` marks the first entry of each table in the flattened ``value``
+    and probability arrays. Exactly one of ``pdf`` or ``cdf`` is required.
+    """
+
     # MC/DC framework metadata
     label = "multi_table_distribution"
     sub_type = DISTRIBUTION_MULTITABLE
@@ -277,6 +304,14 @@ def __repr__(self) -> str:
 
 
 class DistributionLevelScattering(DistributionBase):
+    """Discrete-level inelastic-scattering energy distribution.
+
+    Parameters
+    ----------
+    C1, C2 : float
+        Level-scattering law coefficients.
+    """
+
     # MC/DC framework metadata
     label = "level_scattering_distribution"
     sub_type = DISTRIBUTION_LEVEL_SCATTERING
@@ -304,6 +339,8 @@ def __repr__(self) -> str:
 
 
 class DistributionEvaporation(DistributionBase):
+    """Evaporation spectrum with incident-energy-dependent temperature."""
+
     # MC/DC framework metadata
     label = "evaporation_distribution"
     sub_type = DISTRIBUTION_EVAPORATION
@@ -350,6 +387,8 @@ def __repr__(self) -> str:
 
 
 class DistributionMaxwellian(DistributionBase):
+    """Maxwellian spectrum with incident-energy-dependent temperature."""
+
     # MC/DC framework metadata
     label = "maxwellian_distribution"
     sub_type = DISTRIBUTION_MAXWELLIAN
@@ -396,6 +435,12 @@ def __repr__(self) -> str:
 
 
 class DistributionKalbachMann(DistributionBase):
+    """Correlated Kalbach-Mann outgoing energy-angle distribution.
+
+    Incident-energy tables are stored in flattened arrays delimited by
+    ``offset``. Probability densities are normalized per table.
+    """
+
     # MC/DC framework metadata
     label = "kalbach_mann_distribution"
     sub_type = DISTRIBUTION_KALBACH_MANN
@@ -453,6 +498,12 @@ def __repr__(self) -> str:
 
 
 class DistributionTabulatedEnergyAngle(DistributionBase):
+    """Correlated tabulated outgoing energy and scattering-angle distribution.
+
+    ``offset`` delimits outgoing-energy tables and ``cosine_offset`` delimits
+    conditional cosine tables in the flattened arrays.
+    """
+
     # MC/DC framework metadata
     label = "tabulated_energy_angle_distribution"
     sub_type = DISTRIBUTION_TABULATED_ENERGY_ANGLE
@@ -549,6 +600,14 @@ def __repr__(self) -> str:
 
 
 class DistributionNBody(DistributionBase):
+    """N-body phase-space outgoing-energy distribution.
+
+    Parameters
+    ----------
+    values, probabilities : array_like
+        Outgoing values and their piecewise-linear relative density.
+    """
+
     # MC/DC framework metadata
     label = "nbody_distribution"
     sub_type = DISTRIBUTION_N_BODY
diff --git a/mcdc/object_/electron_reaction.py b/mcdc/object_/electron_reaction.py
index 71913beac..804605c65 100644
--- a/mcdc/object_/electron_reaction.py
+++ b/mcdc/object_/electron_reaction.py
@@ -26,6 +26,12 @@
 
 
 class ElectronReactionBase(MCDCPolymorphic):
+    """Base electron reaction data loaded from the HDF5 physics library.
+
+    Stores the ENDF reaction identifier, cross-section segment and its offset
+    into the element energy grid, and the reaction reference frame.
+    """
+
     # MC/DC framework metadata
     label = "electron_reaction"
     sub_type = -1  # Polymorphic base
@@ -53,6 +59,8 @@ def __repr__(self):
 
 
 def decode_reference_frame(type_):
+    """Return the display name for a packed reference-frame code."""
+
     if type_ == REFERENCE_FRAME_LAB:
         return "Laboratory"
     elif type_ == REFERENCE_FRAME_COM:
@@ -65,6 +73,8 @@ def decode_reference_frame(type_):
 
 
 class ElectronReactionIonization(ElectronReactionBase):
+    """Electron ionization reaction with subshell cross sections and products."""
+
     # MC/DC framework metadata
     label = "electron_ionization_reaction"
     sub_type = ELECTRON_REACTION_IONIZATION
@@ -90,6 +100,7 @@ def __init__(
 
     @classmethod
     def from_h5_group(cls, h5_group):
+        """Build an ionization reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame = set_basic_properties(h5_group)
 
         subshells = h5_group["subshells"]
@@ -157,6 +168,8 @@ def __repr__(self):
 
 
 class ElectronReactionElasticScattering(ElectronReactionBase):
+    """Elastic electron scattering with large-angle cross section and cosine law."""
+
     # MC/DC framework metadata
     label = "electron_elastic_scattering_reaction"
     sub_type = ELECTRON_REACTION_ELASTIC_SCATTERING
@@ -181,6 +194,7 @@ def __init__(
 
     @classmethod
     def from_h5_group(cls, h5_group):
+        """Build an elastic-scattering reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame = set_basic_properties(h5_group)
 
         large_angle = h5_group["large_angle"]
@@ -220,6 +234,8 @@ def __repr__(self):
 
 
 class ElectronReactionBremsstrahlung(ElectronReactionBase):
+    """Electron bremsstrahlung reaction with tabulated energy loss."""
+
     # MC/DC framework metadata
     label = "electron_bremsstrahlung_reaction"
     sub_type = ELECTRON_REACTION_BREMSSTRAHLUNG
@@ -232,6 +248,7 @@ def __init__(self, MT, xs, xs_offset, reference_frame, eloss):
 
     @classmethod
     def from_h5_group(cls, h5_group):
+        """Build a bremsstrahlung reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame = set_basic_properties(h5_group)
 
         base = h5_group["energy_loss"]
@@ -251,6 +268,8 @@ def __repr__(self):
 
 
 class ElectronReactionExcitation(ElectronReactionBase):
+    """Electron excitation reaction with tabulated energy loss."""
+
     # MC/DC framework metadata
     label = "electron_excitation_reaction"
     sub_type = ELECTRON_REACTION_EXCITATION
@@ -263,6 +282,7 @@ def __init__(self, MT, xs, xs_offset, reference_frame, eloss):
 
     @classmethod
     def from_h5_group(cls, h5_group):
+        """Build an excitation reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame = set_basic_properties(h5_group)
 
         base = h5_group["energy_loss"]
@@ -282,6 +302,8 @@ def __repr__(self):
 
 
 def set_basic_properties(h5_group):
+    """Read properties shared by all electron reactions from an HDF5 group."""
+
     MT = h5_group.attrs["MT"][()]
     xs = h5_group["xs"][()]
     xs_offset = h5_group["xs"].attrs["offset"]
diff --git a/mcdc/object_/element.py b/mcdc/object_/element.py
index 0efd92232..cc292c8cc 100644
--- a/mcdc/object_/element.py
+++ b/mcdc/object_/element.py
@@ -17,6 +17,19 @@
 
 
 class Element(MCDCObject):
+    """Element data loaded from the MC/DC HDF5 library.
+
+    Parameters
+    ----------
+    element_name : str
+        Chemical symbol used to locate ``<element_name>.h5`` under ``MCDC_LIB``.
+
+    Notes
+    -----
+    Construction loads basic atomic properties. Electron reaction cross sections
+    and secondary distributions are loaded later by :meth:`set_electron_data`.
+    """
+
     # MC/DC framework metadata
     label = "element"
 
@@ -52,6 +65,7 @@ def __init__(self, element_name: str):
         file.close()
 
     def set_electron_data(self):
+        """Load electron cross sections and reaction data from ``MCDC_LIB``."""
         element_name = self.name
 
         # Load data library
diff --git a/mcdc/object_/gpu_tools.py b/mcdc/object_/gpu_tools.py
index 1a97fa0e8..854891697 100644
--- a/mcdc/object_/gpu_tools.py
+++ b/mcdc/object_/gpu_tools.py
@@ -8,6 +8,8 @@
 
 @dataclass
 class GPUMeta(MCDCBase):
+    """Opaque device pointers owned by the GPU execution bridge."""
+
     # MC/DC framework metadata
     label = "gpu_meta"
 
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 70ebf7861..727bf2f20 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -21,6 +21,14 @@
 
 
 class MaterialBase(MCDCPolymorphic):
+    """Base class shared by continuous-energy and multigroup materials.
+
+    Parameters
+    ----------
+    name : str
+        User-facing material name.
+    """
+
     # MC/DC framework metadata
     label = "material"
     sub_type = -1  # Polymorphic base
@@ -48,6 +56,54 @@ def __repr__(self):
 
 
 class Material(MaterialBase):
+    """Define a continuous-energy material from a data-library composition.
+
+    Parameters
+    ----------
+    name : str, optional
+        User-facing material name.
+    nuclide_composition : dict of str to float, optional
+        Nuclide names and atomic densities in atoms/(barn cm).
+    element_composition : dict of str to float, optional
+        Element symbols and atomic densities in atoms/(barn cm).
+    temperature : float, optional
+        Material temperature in kelvin. Each nuclide uses the closest
+        temperature available in the data library.
+
+    Notes
+    -----
+    Exactly one of ``nuclide_composition`` or ``element_composition`` must be
+    supplied. The ``MCDC_LIB`` environment variable must point to the directory
+    containing the corresponding HDF5 data-library files.
+
+    Examples
+    --------
+    Define uranium dioxide from nuclide atomic densities:
+
+    >>> import mcdc
+    >>> fuel = mcdc.Material(
+    ...     name="UO2",
+    ...     nuclide_composition={"U235": 5.0e-4, "U238": 2.2e-2, "O16": 4.5e-2},
+    ...     temperature=293.6,
+    ... )
+
+    Define a material from natural elemental compositions:
+
+    >>> steel = mcdc.Material(
+    ...     name="Steel",
+    ...     element_composition={"Fe": 8.0e-2, "C": 8.0e-4},
+    ...     temperature=600.0,
+    ... )
+
+    Define a single-isotope material at another supported temperature:
+
+    >>> moderator = mcdc.Material(
+    ...     name="Hydrogen",
+    ...     nuclide_composition={"H1": 6.7e-2},
+    ...     temperature=273.15,
+    ... )
+    """
+
     # MC/DC framework metadata
     label = "native_material"
     sub_type = MATERIAL
@@ -191,6 +247,76 @@ def __repr__(self):
 
 
 class MaterialMG(MaterialBase):
+    """Define a material with multigroup neutron data.
+
+    Parameters
+    ----------
+    name : str, optional
+        User-facing material name.
+    capture : ndarray, optional
+        Capture macroscopic cross section by incident group.
+    scatter : ndarray, optional
+        Scattering production matrix in ``[outgoing_group, incident_group]``
+        order. Column sums define the scattering cross section.
+    fission : ndarray, optional
+        Fission macroscopic cross section by incident group.
+    nu_s : ndarray, optional
+        Mean number of neutrons emitted per scattering event by incident group.
+    nu_p : ndarray, optional
+        Prompt-fission neutron yield by incident group.
+    nu_d : ndarray, optional
+        Delayed-fission neutron yield in
+        ``[delayed_group, incident_group]`` order.
+    chi_p : ndarray, optional
+        Prompt-fission spectrum. A one-dimensional spectrum is shared by all
+        incident groups; a matrix uses
+        ``[outgoing_group, incident_group]`` order.
+    chi_d : ndarray, optional
+        Delayed-fission spectrum in ``[outgoing_group, delayed_group]`` order.
+    speed : ndarray, optional
+        Particle speed by energy group.
+    decay_rate : ndarray, optional
+        Delayed-neutron precursor decay rate by delayed group.
+
+    Notes
+    -----
+    At least one of ``capture``, ``scatter``, or ``fission`` is required and
+    determines the number of energy groups. Cross sections are expected in
+    inverse centimetres.
+
+    Examples
+    --------
+    Define a one-group purely absorbing material:
+
+    >>> import numpy as np
+    >>> import mcdc
+    >>> absorber = mcdc.MaterialMG(
+    ...     name="Absorber",
+    ...     capture=np.array([1.0]),
+    ... )
+
+    Define a two-group scattering material:
+
+    >>> scatterer = mcdc.MaterialMG(
+    ...     name="Scatterer",
+    ...     capture=np.array([0.05, 0.10]),
+    ...     scatter=np.array([
+    ...         [0.70, 0.10],
+    ...         [0.20, 0.50],
+    ...     ]),
+    ...     nu_s=np.array([1.0, 1.0]),
+    ... )
+
+    Define a one-group prompt-fission material:
+
+    >>> fuel = mcdc.MaterialMG(
+    ...     name="Fuel",
+    ...     capture=np.array([0.10]),
+    ...     fission=np.array([0.20]),
+    ...     nu_p=np.array([2.50]),
+    ... )
+    """
+
     # MC/DC framework metadata
     label = "multigroup_material"
     sub_type = MATERIAL_MG
@@ -369,6 +495,8 @@ def __repr__(self):
 
 
 def set_nuclides_from_elements(material):
+    """Expand an elemental material composition into natural isotopes."""
+
     material.nuclides = []
     material.nuclide_composition = {}
     nuclide_densities = []
@@ -410,6 +538,8 @@ def set_nuclides_from_elements(material):
 
 
 def set_elements_from_nuclides(material):
+    """Collapse a nuclide composition into elemental atomic densities."""
+
     material.elements = []
     material.element_composition = {}
 
@@ -455,6 +585,8 @@ def set_elements_from_nuclides(material):
 
 
 def update_fissionable_from_nuclides(material):
+    """Update a material's fissionable flag from its constituent nuclides."""
+
     material.fissionable = False
     for nuclide in material.nuclides:
         if nuclide.fissionable:
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index b6e3ba725..3ce0b574e 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -16,6 +16,8 @@
 
 
 class MeshBase(MCDCPolymorphic):
+    """Base class for spatial meshes used by tallies and techniques."""
+
     # MC/DC framework metadata
     label = "mesh"
     sub_type = -1  # Polymorphic base
@@ -46,6 +48,39 @@ def __repr__(self):
 
 
 class MeshUniform(MeshBase):
+    """Define a Cartesian mesh with uniform spacing on each axis.
+
+    Parameters
+    ----------
+    name : str, optional
+        User-facing mesh name.
+    x, y, z : tuple of (float, float, int), optional
+        ``(origin, spacing, number_of_bins)`` for each axis, in cm. Omitted
+        axes default to one effectively unbounded bin.
+
+    Examples
+    --------
+    Create 100 uniform bins along z from 0 to 10 cm:
+
+    >>> import mcdc
+    >>> mesh = mcdc.MeshUniform(z=(0.0, 0.1, 100))
+
+    Create a two-dimensional x-y mesh:
+
+    >>> mesh_xy = mcdc.MeshUniform(
+    ...     x=(-5.0, 0.5, 20),
+    ...     y=(-5.0, 0.5, 20),
+    ... )
+
+    Create a three-dimensional mesh with different axis spacings:
+
+    >>> mesh_xyz = mcdc.MeshUniform(
+    ...     x=(0.0, 1.0, 10),
+    ...     y=(0.0, 2.0, 5),
+    ...     z=(-3.0, 0.25, 24),
+    ... )
+    """
+
     # MC/DC framework metadata
     label = "uniform_mesh"
     sub_type = MESH_UNIFORM
@@ -99,6 +134,40 @@ def __repr__(self):
 
 
 class MeshStructured(MeshBase):
+    """Define a Cartesian mesh from explicit grid boundaries.
+
+    Parameters
+    ----------
+    name : str, optional
+        User-facing mesh name.
+    x, y, z : sequence of float, optional
+        Strictly ordered grid boundaries in cm. Each omitted axis defaults to
+        one effectively unbounded bin.
+
+    Examples
+    --------
+    Create nonuniform bins along z:
+
+    >>> import mcdc
+    >>> mesh = mcdc.MeshStructured(z=[0.0, 0.5, 2.0, 10.0])
+
+    Create a two-dimensional mesh from explicit boundaries:
+
+    >>> mesh_xy = mcdc.MeshStructured(
+    ...     x=[-2.0, -1.0, 0.0, 2.0],
+    ...     y=[-3.0, 0.0, 1.0, 3.0],
+    ... )
+
+    Mix uniformly generated and explicitly listed boundaries:
+
+    >>> import numpy as np
+    >>> mesh_xyz = mcdc.MeshStructured(
+    ...     x=np.linspace(-5.0, 5.0, 21),
+    ...     y=[-1.0, 0.0, 1.0],
+    ...     z=np.linspace(0.0, 10.0, 101),
+    ... )
+    """
+
     # MC/DC framework metadata
     label = "structured_mesh"
     sub_type = MESH_STRUCTURED
diff --git a/mcdc/object_/neutron_reaction.py b/mcdc/object_/neutron_reaction.py
index 612346c9b..2fe64fdd2 100644
--- a/mcdc/object_/neutron_reaction.py
+++ b/mcdc/object_/neutron_reaction.py
@@ -37,6 +37,12 @@
 
 
 class NeutronReactionBase(MCDCPolymorphic):
+    """Base neutron reaction data loaded from the HDF5 physics library.
+
+    Stores the ENDF reaction identifier, cross-section segment and offset,
+    reaction reference frame, and Q value.
+    """
+
     # MC/DC framework metadata
     label = "neutron_reaction"
     sub_type = -1  # Polymorphic base
@@ -66,6 +72,8 @@ def __repr__(self):
 
 
 def decode_reference_frame(type_):
+    """Return the display name for a packed reference-frame code."""
+
     if type_ == REFERENCE_FRAME_LAB:
         return "Laboratory"
     elif type_ == REFERENCE_FRAME_COM:
@@ -78,6 +86,8 @@ def decode_reference_frame(type_):
 
 
 class NeutronReactionElasticScattering(NeutronReactionBase):
+    """Elastic neutron scattering with incident-energy-dependent cosine data."""
+
     # MC/DC framework metadata
     label = "neutron_elastic_scattering_reaction"
     sub_type = NEUTRON_REACTION_ELASTIC_SCATTERING
@@ -90,6 +100,7 @@ def __init__(self, MT, xs, xs_offset, reference_frame, mu):
 
     @classmethod
     def from_h5_group(cls, h5_group):
+        """Build an elastic-scattering reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame, _ = set_basic_properties(h5_group)
         _, mu = set_angular_distribution(h5_group["angular_cosine_distribution"])
         return cls(MT, xs, xs_offset, reference_frame, mu)
@@ -106,6 +117,8 @@ def __repr__(self):
 
 
 class NeutronReactionCapture(NeutronReactionBase):
+    """Neutron capture reaction."""
+
     # MC/DC framework metadata
     label = "neutron_capture_reaction"
     sub_type = NEUTRON_REACTION_CAPTURE
@@ -115,6 +128,7 @@ def __init__(self, MT, xs, xs_offset, reference_frame, q_value):
 
     @classmethod
     def from_h5_group(cls, h5_group):
+        """Build a capture reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame, q_value = set_basic_properties(h5_group)
         return cls(MT, xs, xs_offset, reference_frame, q_value)
 
@@ -125,6 +139,8 @@ def from_h5_group(cls, h5_group):
 
 
 class NeutronReactionInelasticScattering(NeutronReactionBase):
+    """Inelastic scattering with angular data and one or more energy spectra."""
+
     # MC/DC framework metadata
     label = "neutron_inelastic_scattering_reaction"
     sub_type = NEUTRON_REACTION_INELASTIC_SCATTERING
@@ -167,6 +183,7 @@ def __init__(
 
     @classmethod
     def from_h5_group(cls, h5_group):
+        """Build an inelastic-scattering reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame, q_value = set_basic_properties(h5_group)
         multiplicity = int(h5_group["multiplicity"][()])
 
@@ -219,6 +236,8 @@ def __repr__(self):
 
 
 class NeutronReactionFission(NeutronReactionBase):
+    """Fission reaction with prompt angular and energy distributions."""
+
     # MC/DC framework metadata
     label = "neutron_fission_reaction"
     sub_type = NEUTRON_REACTION_FISSION
@@ -245,6 +264,7 @@ def __init__(
 
     @classmethod
     def from_h5_group(cls, h5_group):
+        """Build a fission reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame, q_value = set_basic_properties(h5_group)
 
         # Prompt angular distribution
@@ -282,6 +302,8 @@ def __repr__(self):
 
 
 def set_basic_properties(h5_group):
+    """Read properties shared by all neutron reactions from an HDF5 group."""
+
     MT = h5_group.attrs["MT"][()]
     xs = h5_group["xs"][()]
     xs_offset = h5_group["xs"].attrs["offset"]
@@ -295,6 +317,8 @@ def set_basic_properties(h5_group):
 
 
 def set_angular_distribution(h5_group):
+    """Create the packed angle type and distribution from an HDF5 group."""
+
     mu_type = h5_group.attrs["type"]
     if mu_type == "isotropic":
         angle_type = ANGLE_ISOTROPIC
@@ -314,6 +338,8 @@ def set_angular_distribution(h5_group):
 
 
 def set_energy_distribution(h5_group):
+    """Create an outgoing-energy distribution from an HDF5 group."""
+
     spectrum_type = h5_group.attrs["type"]
 
     if spectrum_type == "tabulated":
diff --git a/mcdc/object_/nuclide.py b/mcdc/object_/nuclide.py
index 089e8c8e6..91d83814c 100644
--- a/mcdc/object_/nuclide.py
+++ b/mcdc/object_/nuclide.py
@@ -26,6 +26,22 @@
 
 
 class Nuclide(MCDCObject):
+    """Temperature-specific nuclide data from the MC/DC HDF5 library.
+
+    Parameters
+    ----------
+    nuclide_name : str
+        Nuclide identifier, such as ``"U235"``.
+    temperature : float
+        Library temperature in kelvin.
+
+    Notes
+    -----
+    Construction loads basic nuclide properties. Neutron cross sections,
+    reactions, multiplicities, and delayed-neutron data are loaded later by
+    :meth:`set_neutron_data`.
+    """
+
     # MC/DC framework metadata
     label = "nuclide"
 
@@ -77,6 +93,13 @@ def __init__(self, nuclide_name, temperature):
         file.close()
 
     def set_neutron_data(self, simulation):
+        """Load and attach neutron physics data from ``MCDC_LIB``.
+
+        Parameters
+        ----------
+        simulation : Simulation
+            Simulation that owns placeholder data and compiled distributions.
+        """
         nuclide_name = self.name
         temperature = self.temperature
 
@@ -250,6 +273,8 @@ def __repr__(self):
 
 
 def set_fission_multiplicity(h5_group):
+    """Build tabulated or polynomial fission multiplicity from HDF5 data."""
+
     multiplicity_type = h5_group.attrs["type"]
 
     if multiplicity_type == "tabulated":
diff --git a/mcdc/object_/particle.py b/mcdc/object_/particle.py
index 56ef818d8..bbd7319f1 100644
--- a/mcdc/object_/particle.py
+++ b/mcdc/object_/particle.py
@@ -13,6 +13,8 @@
 
 @dataclass
 class ParticleData(MCDCBase):
+    """Serializable phase-space state stored in particle banks."""
+
     # MC/DC framework metadata
     label = "particle_data"
 
@@ -32,6 +34,8 @@ class ParticleData(MCDCBase):
 
 @dataclass
 class CollisionData(MCDCBase):
+    """Per-collision values passed from physics to tally scoring."""
+
     # MC/DC framework metadata
     label = "collision_data"
 
@@ -40,6 +44,8 @@ class CollisionData(MCDCBase):
 
 @dataclass
 class Particle(ParticleData):
+    """Active transport particle with geometry and event-tracking state."""
+
     # MC/DC framework metadata
     label = "particle"
 
@@ -52,6 +58,15 @@ class Particle(ParticleData):
 
 
 class ParticleBank(MCDCBase):
+    """Particle storage metadata used by the compiled runtime.
+
+    Parameters
+    ----------
+    tag : str
+        Bank role, such as ``"active"``, ``"source"``, ``"census"``, or
+        ``"future"``.
+    """
+
     # MC/DC framework metadata
     label = "particle_bank"
     non_numba = ["particles"]
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index 063f6e5bb..fcba8d895 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -19,6 +19,14 @@
 
 @dataclass
 class Settings(MCDCBase):
+    """Simulation controls compiled into the transport state.
+
+    Settings are owned by a :class:`~mcdc.object_.simulation.Simulation` and
+    configure histories, batches, random-number generation, time censuses,
+    eigenvalue mode, transported particle species, output, particle banks, and
+    GPU execution.
+    """
+
     # MC/DC framework metadata
     label = "settings"
 
@@ -72,6 +80,17 @@ class Settings(MCDCBase):
     gpu_storage: int = GPU_STORAGE_SEPARATE
 
     def set_time_census(self, time, tally_frequency=None):
+        """Configure census times for time-dependent transport.
+
+        Parameters
+        ----------
+        time : array_like of float
+            Positive, nondecreasing census times in seconds. An infinite final
+            census is appended automatically.
+        tally_frequency : int, optional
+            Number of tally intervals per census period. A positive value enables
+            census-based tally output.
+        """
         # Make sure that the time grid points are sorted
         if not is_sorted(time):
             print_error("Time census: Time grid points have to be sorted.")
@@ -101,6 +120,23 @@ def set_eigenmode(
         gyration_radius=None,
         save_particle=False,
     ):
+        """Enable neutron k-eigenvalue mode.
+
+        Parameters
+        ----------
+        N_inactive : int, optional
+            Number of inactive cycles.
+        N_active : int, optional
+            Number of active cycles used for statistics.
+        k_init : float, optional
+            Initial multiplication-factor estimate.
+        gyration_radius : str, optional
+            Gyration-radius mode: ``"all"``, ``"infinite-x"``,
+            ``"infinite-y"``, ``"infinite-z"``, ``"only-x"``, ``"only-y"``,
+            or ``"only-z"``.
+        save_particle : bool, optional
+            Whether to save source-bank particles.
+        """
         # Update setting self
         self.N_inactive = N_inactive
         self.N_active = N_active
@@ -130,6 +166,15 @@ def set_eigenmode(
                 print_error("Unknown gyration radius type")
 
     def set_source_file(self, source_file_name):
+        """Use particles from an HDF5 source file.
+
+        The particle count is read from the file's ``particles_size`` dataset.
+
+        Parameters
+        ----------
+        source_file_name : str or path-like
+            Source-particle HDF5 file.
+        """
         self.use_source_file = True
         self.source_file_name = source_file_name
 
@@ -138,6 +183,13 @@ def set_source_file(self, source_file_name):
             self.N_particle = int(f["particles_size"][()])
 
     def set_transported_particles(self, transported_particles: List[str]):
+        """Select the particle species enabled during transport.
+
+        Parameters
+        ----------
+        transported_particles : list of {"neutron", "electron", "proton"}
+            Particle species to enable. Species not listed are disabled.
+        """
         # Reset the flags
         self.neutron_transport = False
         self.electron_transport = False
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index daff000fd..2bf7ed5c6 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -46,6 +46,94 @@
 
 
 class Simulation(MCDCBase):
+    """Own a complete MC/DC model, settings, techniques, and runtime state.
+
+    Parameters
+    ----------
+    name : str, optional
+        User-facing simulation name.
+
+    Notes
+    -----
+    Geometry, sources, and tallies are supplied with :meth:`set_model`,
+    :meth:`set_sources`, and :meth:`set_tallies`. :meth:`compile` walks the
+    resulting object graph, assigns IDs, and prepares it for conversion to the
+    packed arrays consumed by :mod:`mcdc.transport`.
+
+    Examples
+    --------
+    Assemble a minimal one-group slab simulation:
+
+    >>> import numpy as np
+    >>> import mcdc
+    >>> material = mcdc.MaterialMG(capture=np.array([1.0]))
+    >>> left = mcdc.Surface.PlaneX(x=0.0, boundary_condition="vacuum")
+    >>> right = mcdc.Surface.PlaneX(x=1.0, boundary_condition="vacuum")
+    >>> cell = mcdc.Cell(region=+left & -right, fill=material)
+    >>> source = mcdc.Source(x=[0.0, 1.0], isotropic=True, energy_group=0)
+    >>> tally = mcdc.Tally(cell=cell, scores=["flux"])
+    >>> simulation = mcdc.Simulation(name="Slab")
+    >>> simulation.set_model([cell])
+    >>> simulation.set_sources([source])
+    >>> simulation.set_tallies([tally])
+    >>> simulation.settings.N_particle = 1_000
+
+    Visualize an x-z slice of the model:
+
+    >>> simulation.visualize_model(
+    ...     vis_plane="xz",
+    ...     x=[0.0, 1.0],
+    ...     y=0.0,
+    ...     z=[-0.5, 0.5],
+    ...     pixels=(100, 100),
+    ...     colors=None,
+    ...     time=[0.0],
+    ...     save_as="slab",
+    ... )
+
+    Run particle transport and write the configured output:
+
+    >>> simulation.run()
+
+    Configure a time-dependent calculation with census times:
+
+    >>> transient = mcdc.Simulation(name="Transient slab")
+    >>> transient.set_model([cell])
+    >>> transient.set_sources([source])
+    >>> transient.set_tallies([tally])
+    >>> transient.settings.N_particle = 10_000
+    >>> transient.settings.set_time_census(
+    ...     time=[1.0e-6, 2.0e-6, 5.0e-6],
+    ...     tally_frequency=10,
+    ... )
+
+    Configure a k-eigenvalue calculation:
+
+    >>> fuel = mcdc.MaterialMG(
+    ...     capture=np.array([0.10]),
+    ...     fission=np.array([0.20]),
+    ...     nu_p=np.array([2.50]),
+    ... )
+    >>> fuel_cell = mcdc.Cell(region=+left & -right, fill=fuel)
+    >>> eigenvalue = mcdc.Simulation(name="Critical slab")
+    >>> eigenvalue.set_model([fuel_cell])
+    >>> eigenvalue.set_sources([source])
+    >>> eigenvalue.settings.N_particle = 10_000
+    >>> eigenvalue.settings.set_eigenmode(
+    ...     N_inactive=20,
+    ...     N_active=100,
+    ...     k_init=1.0,
+    ... )
+
+    Enable common variance-reduction techniques:
+
+    >>> simulation.implicit_capture()
+    >>> simulation.global_weight_roulette(
+    ...     weight_threshold=0.25,
+    ...     weight_target=1.0,
+    ... )
+    """
+
     # MC/DC framework metadata
     label = "simulation"
     non_numba = [
@@ -267,14 +355,17 @@ def _reset_model(self) -> None:
     # ==================================================================================
 
     def set_model(self, cells: Sequence[Cell]) -> None:
+        """Set the cells in the root universe and invalidate compiled state."""
         self.root_universe.cells = list(cells)
         self.compiled = False
 
     def set_sources(self, sources: Sequence[Source]) -> None:
+        """Set particle sources and invalidate compiled state."""
         self.sources = list(sources)
         self.compiled = False
 
     def set_tallies(self, tallies: Sequence[Tally]) -> None:
+        """Set requested tallies and invalidate compiled state."""
         self.tallies = list(tallies)
         self.compiled = False
 
@@ -283,6 +374,7 @@ def set_tallies(self, tallies: Sequence[Tally]) -> None:
     # ==================================================================================
 
     def compile(self) -> None:
+        """Compile the Python object graph into registered simulation objects."""
         from mcdc.code_factory.python_objects_compiler import compile_simulation
 
         self.compile_ID = type(self)._next_compile_ID
@@ -302,6 +394,11 @@ def visualize_model(
         time,
         save_as,
     ) -> None:
+        """Render a two-dimensional material map of the compiled model.
+
+        Parameters are forwarded to :func:`mcdc.visualize.visualize_model`.
+        The model is compiled first when necessary.
+        """
         if not self.compiled:
             self.compile()
 
@@ -310,6 +407,7 @@ def visualize_model(
         visualize_model(self, vis_plane, x, y, z, pixels, colors, time, save_as)
 
     def run(self) -> None:
+        """Compile if needed, execute particle transport, and write output."""
         from mcdc.main import run_simulation
 
         if not self.compiled:
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index b565a685f..594a5266b 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -21,6 +21,8 @@
 
 
 def decode_particle_type(type_):
+    """Return the display name for a packed particle-type code."""
+
     if type_ == PARTICLE_NEUTRON:
         return "Neutron"
     elif type_ == PARTICLE_ELECTRON:
@@ -35,11 +37,7 @@ def decode_particle_type(type_):
 
 
 class Source(MCDCObject):
-    # MC/DC framework metadata
-    label = "source"
-
-    """
-    Define a particle source.
+    """Define a particle source.
 
     A source specifies the initial position, direction, energy, time, particle
     type, and relative sampling probability for emitted particles.
@@ -74,15 +72,14 @@ class Source(MCDCObject):
         Bounds for the sampled azimuthal angle,
         ``[azi_min, azi_max]`` in radians, measured about ``direction``.
         Defaults to ``[0.0, 2π]``.
-    energy : float or ndarray, optional
-        Source energy in eV. A float defines a mono-energetic source. An array
-        defines a tabulated energy distribution. Defaults to a mono-energetic
-        source at **1 MeV**.
-
-    energy_group : int or ndarray, optional
-        Source energy group. An integer defines a mono-group source. An array
-        defines a discrete group probability mass function. In multigroup
-        simulations, the default is **group 0**.
+    energy : float or two-item sequence, optional
+        Source energy in eV. A float defines a mono-energetic source. A sequence
+        ``[values, pdf]`` defines a tabulated energy distribution. Defaults to a
+        mono-energetic source at **1 MeV**.
+    energy_group : int or two-item sequence, optional
+        Source energy group. An integer defines a mono-group source. A sequence
+        ``[groups, probabilities]`` defines a discrete probability mass
+        function. In multigroup simulations, the default is **group 0**.
     time : float or array_like of float, optional
         Emission time in seconds. A float defines a discrete emission time.
         A two-entry array-like value defines a time interval
@@ -115,6 +112,8 @@ class Source(MCDCObject):
     --------
     Point source at the origin emitting mono-energetic neutrons isotropically:
 
+    >>> import numpy as np
+    >>> import mcdc
     >>> src = mcdc.Source(position=[0.0, 0.0, 0.0], isotropic=True)
 
     Uniform box source distributed along z:
@@ -164,6 +163,9 @@ class Source(MCDCObject):
     ... )
     """
 
+    # MC/DC framework metadata
+    label = "source"
+
     name: str
 
     # Position
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 5cdf3d1e3..cdda32d53 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -41,6 +41,60 @@
 
 
 class Surface(MCDCObject):
+    """Implicit surface used to bound cells.
+
+    Surfaces are created with class methods such as :meth:`PlaneX`,
+    :meth:`CylinderZ`, and :meth:`Sphere`. Unary ``+`` and ``-`` return the
+    corresponding positive and negative half-space
+    :class:`~mcdc.object_.cell.Region`.
+
+    Boundary conditions may be ``"none"``, ``"vacuum"``, or ``"reflective"``.
+    A surface can also undergo piecewise-constant translational motion configured
+    with :meth:`move`.
+
+    Examples
+    --------
+    Create a vacuum x plane and select its positive half-space:
+
+    >>> import numpy as np
+    >>> import mcdc
+    >>> plane = mcdc.Surface.PlaneX(x=0.0, boundary_condition="vacuum")
+    >>> region = +plane
+
+    Create a sphere and select its interior:
+
+    >>> sphere = mcdc.Surface.Sphere(center=[0.0, 0.0, 0.0], radius=2.0)
+    >>> interior = -sphere
+
+    Create a cylinder parallel to the z axis:
+
+    >>> cylinder = mcdc.Surface.CylinderZ(
+    ...     center=[1.0, -1.0],
+    ...     radius=0.5,
+    ... )
+
+    Create an oblique plane from its equation coefficients:
+
+    >>> oblique = mcdc.Surface.Plane(A=1.0, B=1.0, C=0.0, D=-2.0)
+
+    Create a torus with an arbitrary symmetry axis:
+
+    >>> torus = mcdc.Surface.Torus(
+    ...     center=[0.0, 0.0, 0.0],
+    ...     axis=[1.0, 1.0, 0.0],
+    ...     R=2.0,
+    ...     r=0.5,
+    ... )
+
+    Define piecewise-constant motion for a plane:
+
+    >>> moving_plane = mcdc.Surface.PlaneX(x=0.0)
+    >>> moving_plane.move(
+    ...     velocities=np.array([[1.0, 0.0, 0.0]]),
+    ...     durations=np.array([0.5]),
+    ... )
+    """
+
     # MC/DC framework metadata
     label = "surface"
 
@@ -238,6 +292,17 @@ def PlaneX(
         x: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create the plane ``x = constant``.
+
+        Parameters
+        ----------
+        name : str, optional
+            User-facing surface name.
+        x : float, optional
+            Plane position in cm.
+        boundary_condition : {"none", "vacuum", "reflective"}, optional
+            Boundary condition applied when a particle crosses the plane.
+        """
         type_ = SURFACE_PLANE_X
         surface = cls(type_, name, boundary_condition)
 
@@ -258,6 +323,12 @@ def PlaneY(
         y: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create the plane ``y = constant``.
+
+        Parameters are the surface ``name``, position ``y`` in cm, and a
+        ``boundary_condition`` of ``"none"``, ``"vacuum"``, or
+        ``"reflective"``.
+        """
         type_ = SURFACE_PLANE_Y
         surface = cls(type_, name, boundary_condition)
 
@@ -278,6 +349,12 @@ def PlaneZ(
         z: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create the plane ``z = constant``.
+
+        Parameters are the surface ``name``, position ``z`` in cm, and a
+        ``boundary_condition`` of ``"none"``, ``"vacuum"``, or
+        ``"reflective"``.
+        """
         type_ = SURFACE_PLANE_Z
         surface = cls(type_, name, boundary_condition)
 
@@ -301,6 +378,11 @@ def Plane(
         D: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create a general plane ``A*x + B*y + C*z + D = 0``.
+
+        The coefficients are normalized internally. ``(A, B, C)`` must be a
+        nonzero normal vector.
+        """
         type_ = SURFACE_PLANE
         surface = cls(type_, name, boundary_condition)
 
@@ -335,6 +417,10 @@ def CylinderX(
         radius: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create an infinite cylinder parallel to the x axis.
+
+        ``center`` gives ``[y, z]`` in cm and ``radius`` is in cm.
+        """
         type_ = SURFACE_CYLINDER_X
         surface = cls(type_, name, boundary_condition)
 
@@ -362,6 +448,10 @@ def CylinderY(
         radius: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create an infinite cylinder parallel to the y axis.
+
+        ``center`` gives ``[x, z]`` in cm and ``radius`` is in cm.
+        """
         type_ = SURFACE_CYLINDER_Y
         surface = cls(type_, name, boundary_condition)
 
@@ -389,6 +479,10 @@ def CylinderZ(
         radius: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create an infinite cylinder parallel to the z axis.
+
+        ``center`` gives ``[x, y]`` in cm and ``radius`` is in cm.
+        """
         type_ = SURFACE_CYLINDER_Z
         surface = cls(type_, name, boundary_condition)
 
@@ -418,6 +512,17 @@ def Cylinder(
         point: Sequence[float] = [0.0, 0.0, 0.0],
         boundary_condition: str = "none",
     ):
+        """Create an infinite cylinder with an arbitrary axis.
+
+        Parameters
+        ----------
+        radius : float, optional
+            Cylinder radius in cm.
+        axis : sequence of 3 float, optional
+            Nonzero vector parallel to the cylinder axis.
+        point : sequence of 3 float, optional
+            A point on the cylinder axis, in cm.
+        """
         type_ = SURFACE_CYLINDER
         surface = cls(type_, name, boundary_condition)
 
@@ -458,6 +563,7 @@ def Sphere(
         radius: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create a sphere from its center and radius in cm."""
         type_ = SURFACE_SPHERE
         surface = cls(type_, name, boundary_condition)
 
@@ -487,6 +593,11 @@ def ConeX(
         t_sq: float = 1.0,
         boundary_condition: str = "none",
     ):
+        """Create a double cone aligned with the x axis.
+
+        ``apex`` is in cm and ``t_sq`` is the squared tangent of the opening
+        half-angle.
+        """
         type_ = SURFACE_CONE_X
         surface = cls(type_, name, boundary_condition)
 
@@ -514,6 +625,11 @@ def ConeY(
         t_sq: float = 1.0,
         boundary_condition: str = "none",
     ):
+        """Create a double cone aligned with the y axis.
+
+        ``apex`` is in cm and ``t_sq`` is the squared tangent of the opening
+        half-angle.
+        """
         type_ = SURFACE_CONE_Y
         surface = cls(type_, name, boundary_condition)
 
@@ -541,6 +657,11 @@ def ConeZ(
         t_sq: float = 1.0,
         boundary_condition: str = "none",
     ):
+        """Create a double cone aligned with the z axis.
+
+        ``apex`` is in cm and ``t_sq`` is the squared tangent of the opening
+        half-angle.
+        """
         type_ = SURFACE_CONE_Z
         surface = cls(type_, name, boundary_condition)
 
@@ -576,6 +697,12 @@ def Quadric(
         J: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create a general second-degree surface.
+
+        The coefficients define
+        ``A*x**2 + B*y**2 + C*z**2 + D*x*y + E*x*z + F*y*z
+        + G*x + H*y + I*z + J = 0``.
+        """
         type_ = SURFACE_QUADRIC
         surface = cls(type_, name, boundary_condition)
 
@@ -607,6 +734,10 @@ def TorusX(
         r: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create a torus centered at ``(A, B, C)`` and aligned with x.
+
+        ``R`` is the major radius and ``r`` the minor radius, both in cm.
+        """
         type_ = SURFACE_TORUS_X
         surface = cls(type_, name, boundary_condition)
 
@@ -634,6 +765,10 @@ def TorusY(
         r: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create a torus centered at ``(A, B, C)`` and aligned with y.
+
+        ``R`` is the major radius and ``r`` the minor radius, both in cm.
+        """
         type_ = SURFACE_TORUS_Y
         surface = cls(type_, name, boundary_condition)
 
@@ -661,6 +796,10 @@ def TorusZ(
         r: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create a torus centered at ``(A, B, C)`` and aligned with z.
+
+        ``R`` is the major radius and ``r`` the minor radius, both in cm.
+        """
         type_ = SURFACE_TORUS_Z
         surface = cls(type_, name, boundary_condition)
 
@@ -687,6 +826,19 @@ def Torus(
         r: float = 0.0,
         boundary_condition: str = "none",
     ):
+        """Create a torus with an arbitrary axis.
+
+        Parameters
+        ----------
+        center : sequence of 3 float, optional
+            Torus center in cm.
+        axis : sequence of 3 float, optional
+            Nonzero symmetry-axis vector.
+        R : float, optional
+            Major radius in cm.
+        r : float, optional
+            Minor radius in cm.
+        """
         x, y, z = center
         ax, ay, az = axis
         norm = (ax**2 + ay**2 + az**2) ** 0.5
@@ -728,10 +880,22 @@ def __neg__(self):
     # ==================================================================================
 
     def move(self, velocities, durations):
+        """Define piecewise-constant translational motion.
+
+        Parameters
+        ----------
+        velocities : array_like, shape (N, 3)
+            Velocity vector for each segment in cm/s.
+        durations : array_like, shape (N,)
+            Segment durations in seconds. A final stationary segment is appended
+            automatically.
+        """
         move_object(self, velocities, durations)
 
 
 def decode_BC_type(type_):
+    """Return the display name for a packed boundary-condition code."""
+
     if type_ == BC_NONE:
         return "None"
     elif type_ == BC_VACUUM:
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 7a652c51a..337599d40 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -46,6 +46,120 @@
 
 
 class Tally(MCDCPolymorphic):
+    """Create a tally and select its estimator from the requested scores.
+
+    Parameters
+    ----------
+    name : str, optional
+        User-facing tally name.
+    scores : list of str, optional
+        Scores to accumulate. Track-length scores are ``"flux"``, ``"density"``,
+        ``"collision"``, ``"capture"``, and ``"fission"``; surface-crossing
+        scores are ``"current-net"``, ``"current-in"``, and ``"current-out"``;
+        the collision score is ``"energy_deposition"``. Scores from different
+        estimator families cannot be mixed.
+    surface : Surface, optional
+        Surface filter. Required for a surface-crossing tally unless ``cell`` is
+        provided.
+    cell : Cell, optional
+        Cell filter.
+    mesh : MeshBase, optional
+        Spatial mesh filter for track-length or collision tallies.
+    mu : sequence of float, optional
+        Polar-cosine bin boundaries.
+    azi : sequence of float, optional
+        Azimuthal-angle bin boundaries in radians.
+    polar_reference : sequence of 3 float, optional
+        Reference direction for the angular filters.
+    energy : sequence of float or "all_groups", optional
+        Energy-bin boundaries in eV, or ``"all_groups"`` in multigroup mode.
+    time : sequence of float, optional
+        Time-bin boundaries in seconds.
+
+    Returns
+    -------
+    TallySurfaceCrossing, TallyTracklength, or TallyCollision
+        Concrete tally selected from ``scores``.
+
+    Examples
+    --------
+    Score flux and fission on a structured mesh:
+
+    >>> import numpy as np
+    >>> import mcdc
+    >>> mesh = mcdc.MeshStructured(z=np.linspace(0.0, 10.0, 101))
+    >>> tally = mcdc.Tally(
+    ...     name="Axial flux",
+    ...     mesh=mesh,
+    ...     scores=["flux", "fission"],
+    ...     energy=[0.0, 1.0e6, 20.0e6],
+    ... )
+
+    Score net current crossing a surface:
+
+    >>> boundary = mcdc.Surface.PlaneZ(z=10.0)
+    >>> current = mcdc.Tally(surface=boundary, scores=["current-net"])
+
+    Filter a track-length tally by cell, angle, and time:
+
+    >>> material = mcdc.MaterialMG(capture=np.array([1.0]))
+    >>> lower = mcdc.Surface.PlaneZ(z=0.0)
+    >>> upper = mcdc.Surface.PlaneZ(z=10.0)
+    >>> cell = mcdc.Cell(region=+lower & -upper, fill=material)
+    >>> filtered_flux = mcdc.Tally(
+    ...     cell=cell,
+    ...     scores=["flux", "capture"],
+    ...     mu=np.linspace(-1.0, 1.0, 11),
+    ...     azi=np.linspace(-np.pi, np.pi, 17),
+    ...     time=[0.0, 1.0e-6, 2.0e-6],
+    ... )
+
+    Compile the geometry to resolve the cell's bounding surfaces:
+
+    >>> model = mcdc.Simulation(name="Cell-current example")
+    >>> model.set_model([cell])
+    >>> model.compile()
+
+    Score current entering and leaving the cell through any of its boundaries:
+
+    >>> cell_current = mcdc.Tally(
+    ...     cell=cell,
+    ...     scores=["current-net", "current-in", "current-out"],
+    ... )
+
+    A cell-only surface-crossing filter scores genuine changes in cell membership.
+    Crossings of surfaces inside the cell that do not enter or leave the cell are
+    not scored.
+
+    Restrict the cell current to one particular boundary surface:
+
+    >>> upper_surface_current = mcdc.Tally(
+    ...     surface=upper,
+    ...     cell=cell,
+    ...     scores=["current-net", "current-in", "current-out"],
+    ... )
+    >>> model.set_tallies([cell_current, upper_surface_current])
+
+    With both filters, the surface selects where crossings are scored, while the
+    cell determines whether each crossing is incoming or outgoing.
+
+    Score energy deposition with both cell and mesh filters:
+
+    >>> deposition = mcdc.Tally(
+    ...     cell=cell,
+    ...     mesh=mesh,
+    ...     scores=["energy_deposition"],
+    ... )
+
+    Use one energy bin per multigroup energy group:
+
+    >>> group_flux = mcdc.Tally(
+    ...     cell=cell,
+    ...     scores=["flux"],
+    ...     energy="all_groups",
+    ... )
+    """
+
     # MC/DC framework metadata
     label = "tally"
     sub_type = -1  # Polymorphic base
@@ -294,6 +408,8 @@ def __repr__(self):
 
 
 def decode_score_type(type_, lower_case=False):
+    """Return the display or input name for a packed tally-score code."""
+
     if type_ == SCORE_FLUX:
         return "Flux" if not lower_case else "flux"
     elif type_ == SCORE_DENSITY:
@@ -323,6 +439,12 @@ def decode_score_type(type_, lower_case=False):
 
 
 class TallySurfaceCrossing(Tally):
+    """Surface-crossing current tally.
+
+    Instances are normally created through :class:`Tally`, which selects this
+    estimator for current scores.
+    """
+
     # MC/DC framework metadata
     label = "surface_crossing_tally"
     sub_type = TALLY_SURFACE_CROSSING
@@ -424,6 +546,12 @@ def __repr__(self):
 
 
 class TallyCollision(Tally):
+    """Collision-estimator tally.
+
+    Instances are normally created through :class:`Tally`, which selects this
+    estimator for the ``"energy_deposition"`` score.
+    """
+
     # MC/DC framework metadata
     label = "collision_tally"
     sub_type = TALLY_COLLISION
@@ -546,6 +674,12 @@ def __repr__(self):
 
 
 class TallyTracklength(Tally):
+    """Track-length estimator tally.
+
+    Instances are normally created through :class:`Tally`, which selects this
+    estimator for flux, density, reaction-rate, and collision scores.
+    """
+
     # MC/DC framework metadata
     label = "tracklength_tally"
     sub_type = TALLY_TRACKLENGTH
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index d3bd8fe6e..e7d7a77e2 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -13,6 +13,8 @@
 
 
 class ImplicitCapture(MCDCBase):
+    """Configuration for implicit capture."""
+
     # MC/DC framework metadata
     label = "implicit_capture"
 
@@ -22,6 +24,7 @@ def __init__(self):
         self.active = False
 
     def __call__(self, active: bool = True):
+        """Enable or disable implicit capture."""
         self.active = active
 
 
@@ -31,6 +34,8 @@ def __call__(self, active: bool = True):
 
 
 class WeightedEmission(MCDCBase):
+    """Configuration for weighted secondary-particle emission."""
+
     # MC/DC framework metadata
     label = "weighted_emission"
 
@@ -42,6 +47,15 @@ def __init__(self):
         self.weight_target = 0.0
 
     def __call__(self, active: bool = True, weight_target: float = 1.0):
+        """Configure weighted emission.
+
+        Parameters
+        ----------
+        active : bool, optional
+            Whether the technique is active.
+        weight_target : float, optional
+            Target statistical weight for emitted particles.
+        """
         self.active = active
         self.weight_target = weight_target
 
@@ -52,6 +66,8 @@ def __call__(self, active: bool = True, weight_target: float = 1.0):
 
 
 class GlobalWeightRoulette(MCDCBase):
+    """Configuration for global low-weight particle roulette."""
+
     # MC/DC framework metadata
     label = "global_weight_roulette"
 
@@ -65,6 +81,10 @@ def __init__(self):
         self.weight_target = 1.0
 
     def __call__(self, weight_threshold: float = 0.0, weight_target: float = 1.0):
+        """Enable roulette below a global weight threshold.
+
+        ``weight_threshold`` must not exceed ``weight_target``.
+        """
         if weight_threshold > weight_target:
             print_error(
                 "For weight roulette, weight threshold has to be smaller than the target"
@@ -80,6 +100,8 @@ def __call__(self, weight_threshold: float = 0.0, weight_target: float = 1.0):
 
 
 class WeightWindows(MCDCBase):
+    """Space- and energy-dependent particle weight-window configuration."""
+
     # MC/DC framework metadata
     label = "weight_windows"
 
@@ -112,6 +134,18 @@ def __init__(self):
         self.upper_weights = np.array([1.0]).reshape(*shape)
 
     def __call__(self, weight_windows, mesh=None, energy=None):
+        """Configure lower, target, and upper particle weights.
+
+        Parameters
+        ----------
+        weight_windows : ndarray, shape (Ne, Nx, Ny, Nz, 3)
+            Lower, target, and upper weights in the final dimension.
+        mesh : MeshUniform or MeshStructured, optional
+            Spatial mesh. The default is one unbounded uniform bin.
+        energy : ndarray, optional
+            Strictly increasing energy-group boundaries. The default is one
+            all-energy bin.
+        """
         # fill in defaults
         if mesh is None:
             mesh = MeshUniform()
@@ -183,6 +217,8 @@ def __call__(self, weight_windows, mesh=None, energy=None):
 
 
 class PopulationControl(MCDCBase):
+    """Configuration for source-bank population control."""
+
     # MC/DC framework metadata
     label = "population_control"
 
@@ -192,4 +228,5 @@ def __init__(self):
         self.active = False
 
     def __call__(self, active: bool = True):
+        """Enable or disable population control."""
         self.active = active
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index b9c0ee0fd..14a7cb4bf 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -24,6 +24,50 @@
 
 
 class Universe(MCDCObject):
+    """Group cells into a reusable geometry.
+
+    Parameters
+    ----------
+    name : str, optional
+        User-facing universe name.
+    cells : list of Cell, optional
+        Cells belonging to the universe. Cells are tested in list order by the
+        geometry search.
+
+    Examples
+    --------
+    Group two cells into a reusable universe:
+
+    >>> import numpy as np
+    >>> import mcdc
+    >>> left = mcdc.Surface.PlaneX(x=-1.0)
+    >>> middle = mcdc.Surface.PlaneX(x=0.0)
+    >>> right = mcdc.Surface.PlaneX(x=1.0)
+    >>> material = mcdc.MaterialMG(capture=np.array([1.0]))
+    >>> cells = [
+    ...     mcdc.Cell(region=+left & -middle, fill=material),
+    ...     mcdc.Cell(region=+middle & -right, fill=material),
+    ... ]
+    >>> universe = mcdc.Universe(name="Two regions", cells=cells)
+
+    Create a universe for a spherical inclusion and its surrounding material:
+
+    >>> sphere = mcdc.Surface.Sphere(radius=0.5)
+    >>> fuel = mcdc.MaterialMG(fission=np.array([0.2]), nu_p=np.array([2.5]))
+    >>> water = mcdc.MaterialMG(capture=np.array([0.01]))
+    >>> pin = mcdc.Universe(
+    ...     name="Pin",
+    ...     cells=[
+    ...         mcdc.Cell(region=-sphere, fill=fuel),
+    ...         mcdc.Cell(region=+sphere, fill=water),
+    ...     ],
+    ... )
+
+    Use a universe as a cell fill:
+
+    >>> placed_pin = mcdc.Cell(fill=pin, translation=[1.0, 0.0, 0.0])
+    """
+
     # MC/DC framework metadata
     label = "universe"
 
@@ -61,6 +105,51 @@ def __repr__(self):
 
 
 class Lattice(MCDCObject):
+    """Arrange universes on a uniform Cartesian lattice.
+
+    Parameters
+    ----------
+    name : str, optional
+        User-facing lattice name.
+    x, y, z : tuple of (float, float, int), optional
+        ``(origin, spacing, number_of_bins)`` for each finite lattice axis, in
+        cm. An omitted axis is treated as a single unbounded bin.
+    universes : nested list of Universe, optional
+        Universe layout supplied in ``[z][y][x]`` order. The y and z axes are
+        reversed internally to match MC/DC's Cartesian indexing convention.
+
+    Examples
+    --------
+    Place two universes next to each other along x:
+
+    >>> import mcdc
+    >>> left = mcdc.Universe(name="Left")
+    >>> right = mcdc.Universe(name="Right")
+    >>> lattice = mcdc.Lattice(
+    ...     x=(-1.0, 1.0, 2),
+    ...     universes=[[left, right]],
+    ... )
+
+    Build a two-dimensional 2-by-2 lattice:
+
+    >>> u00 = mcdc.Universe(name="Lower left")
+    >>> u10 = mcdc.Universe(name="Lower right")
+    >>> u01 = mcdc.Universe(name="Upper left")
+    >>> u11 = mcdc.Universe(name="Upper right")
+    >>> lattice_xy = mcdc.Lattice(
+    ...     x=(-1.0, 1.0, 2),
+    ...     y=(-1.0, 1.0, 2),
+    ...     universes=[
+    ...         [u00, u10],
+    ...         [u01, u11],
+    ...     ],
+    ... )
+
+    Place the lattice inside a cell:
+
+    >>> lattice_cell = mcdc.Cell(fill=lattice_xy)
+    """
+
     # MC/DC framework metadata
     label = "lattice"
     non_numba = ["universes"]
diff --git a/mcdc/object_/util.py b/mcdc/object_/util.py
index d706ef0d9..d7de7dbb1 100644
--- a/mcdc/object_/util.py
+++ b/mcdc/object_/util.py
@@ -137,6 +137,21 @@ def pdf_from_cdf(
 
 
 def multi_cdf_from_pdf(offset, value, pdf):
+    """Normalize multiple flattened PDFs and construct their CDFs.
+
+    Parameters
+    ----------
+    offset : array_like of int
+        Start index of each table.
+    value, pdf : ndarray
+        Flattened sample values and probability densities.
+
+    Returns
+    -------
+    pdf, cdf : ndarray
+        Per-table normalized densities and cumulative distributions.
+    """
+
     cdf = np.zeros_like(pdf)
 
     for i in range(len(offset)):
@@ -159,6 +174,7 @@ def multi_cdf_from_pdf(offset, value, pdf):
 
 
 def is_sorted(a):
+    """Return whether an array is monotonically nondecreasing."""
     return np.all(a[:-1] <= a[1:])
 
 
@@ -625,6 +641,13 @@ def is_sorted(a):
 
 
 def move_object(object_, velocities, durations):
+    """Populate the shared piecewise-constant motion representation.
+
+    A zero-velocity segment of infinite duration is appended after the supplied
+    segments. The input lists are therefore mutated; array inputs are converted
+    to lists first.
+    """
+
     object_.moving = True
     object_.N_move = len(durations) + 1
     object_.N_move_grid = len(durations) + 2
@@ -656,4 +679,5 @@ def move_object(object_, velocities, durations):
 
 
 def subtype_size(main_list, subtype: str):
+    """Count objects whose framework label matches ``subtype``."""
     return len([x for x in main_list if x.label == subtype])

From ba3800e707316b5102d9461373ee7bedcbc5787d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 14:59:14 +0700
Subject: [PATCH 044/202] update regtest

---
 test/regression/azurv1_census/input.py        | 28 ++++++++++-------
 test/regression/azurv1_census_tally/input.py  | 28 ++++++++++-------
 test/regression/basic_weight_windows/input.py | 26 +++++++++-------
 test/regression/c5g7_2d_k_eigenvalue/input.py | 28 +++++++++--------
 test/regression/cooper2/input.py              | 28 ++++++++++-------
 test/regression/fuel_array_packaged/input.py  | 30 +++++++++++++------
 test/regression/inf_shem361/input.py          | 20 ++++++++-----
 .../inf_shem361_k_eigenvalue/input.py         | 22 +++++++++-----
 test/regression/inf_shem361_td/input.py       | 20 ++++++++-----
 .../regression/inf_shem361_td_census/input.py | 26 +++++++++-------
 test/regression/kobayashi3-TD/input.py        | 26 ++++++++++------
 test/regression/kornreich/input.py            | 24 +++++++++------
 test/regression/lockwood/input.py             | 29 ++++++++++--------
 test/regression/moving_pellet/input.py        | 26 +++++++++-------
 test/regression/moving_source/input.py        | 16 ++++++----
 .../pincell-energy_deposition/input.py        | 24 +++++++++------
 test/regression/pincell-k_eigenvalue/input.py | 26 +++++++++-------
 test/regression/pincell/input.py              | 24 +++++++++------
 test/regression/slab_absorbium/input.py       | 28 +++++++++++------
 test/regression/slab_isobeam_td/input.py      | 18 +++++++----
 .../slab_isobeam_td_census/input.py           | 24 +++++++++------
 test/regression/slab_reed/input.py            | 26 +++++++++-------
 test/regression/sphere_in_cube/input.py       | 22 +++++++++-----
 23 files changed, 357 insertions(+), 212 deletions(-)

diff --git a/test/regression/azurv1_census/input.py b/test/regression/azurv1_census/input.py
index 9a8098887..c7d2e7122 100644
--- a/test/regression/azurv1_census/input.py
+++ b/test/regression/azurv1_census/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("AZURV1 census")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -21,19 +24,21 @@
 s2 = mcdc.Surface.PlaneX(x=1e10, boundary_condition="reflective")
 
 # Set cells
-mcdc.Cell(region=+s1 & -s2, fill=m)
+cell = mcdc.Cell(region=+s1 & -s2, fill=m)
+simulation.set_model([cell])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 # Isotropic pulse at x=t=0
 
-mcdc.Source(
+source = mcdc.Source(
     position=[0.0, 0.0, 0.0],
     isotropic=True,
     energy_group=0,
     time=0.0,
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, techniques, and run MC/DC
@@ -41,17 +46,18 @@
 
 # Tallies
 mesh = mcdc.MeshStructured(x=np.linspace(-20.5, 20.5, 202))
-mcdc.Tally(mesh=mesh, scores=["flux"], time=np.linspace(0.0, 20.0, 21))
+tally = mcdc.Tally(mesh=mesh, scores=["flux"], time=np.linspace(0.0, 20.0, 21))
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 50
-mcdc.settings.N_batch = 2
-mcdc.settings.census_bank_buffer_ratio = 5.0
-mcdc.settings.source_bank_buffer_ratio = 5.0
-mcdc.settings.set_time_census(np.linspace(0.0, 20.0, 21)[1:-1])
+simulation.settings.N_particle = 50
+simulation.settings.N_batch = 2
+simulation.settings.census_bank_buffer_ratio = 5.0
+simulation.settings.source_bank_buffer_ratio = 5.0
+simulation.settings.set_time_census(np.linspace(0.0, 20.0, 21)[1:-1])
 
-# Tecniques
-mcdc.simulation.population_control()
+# Techniques
+simulation.population_control()
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/azurv1_census_tally/input.py b/test/regression/azurv1_census_tally/input.py
index ab15e958d..ce8459839 100644
--- a/test/regression/azurv1_census_tally/input.py
+++ b/test/regression/azurv1_census_tally/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("AZURV1 census tally")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -21,19 +24,21 @@
 s2 = mcdc.Surface.PlaneX(x=1e10, boundary_condition="reflective")
 
 # Set cells
-mcdc.Cell(region=+s1 & -s2, fill=m)
+cell = mcdc.Cell(region=+s1 & -s2, fill=m)
+simulation.set_model([cell])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 # Isotropic pulse at x=t=0
 
-mcdc.Source(
+source = mcdc.Source(
     position=[0.0, 0.0, 0.0],
     isotropic=True,
     energy_group=0,
     time=0.0,
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, techniques, and run MC/DC
@@ -41,20 +46,21 @@
 
 # Tallies
 mesh = mcdc.MeshStructured(x=np.linspace(-20.5, 20.5, 202))
-mcdc.Tally(mesh=mesh, scores=["flux"], time=np.linspace(0.0, 20.0, 21))
+tally = mcdc.Tally(mesh=mesh, scores=["flux"], time=np.linspace(0.0, 20.0, 21))
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 50
-mcdc.settings.N_batch = 2
-mcdc.settings.census_bank_buffer_ratio = 5.0
-mcdc.settings.source_bank_buffer_ratio = 5.0
-mcdc.settings.set_time_census(np.linspace(0.0, 20.0, 21)[1:], tally_frequency=5)
+simulation.settings.N_particle = 50
+simulation.settings.N_batch = 2
+simulation.settings.census_bank_buffer_ratio = 5.0
+simulation.settings.source_bank_buffer_ratio = 5.0
+simulation.settings.set_time_census(np.linspace(0.0, 20.0, 21)[1:], tally_frequency=5)
 
-# Tecniques
-mcdc.simulation.population_control()
+# Techniques
+simulation.population_control()
 
 # Run
-mcdc.run()
+simulation.run()
 
 # Post-processing
 mcdc.recombine_tallies()
diff --git a/test/regression/basic_weight_windows/input.py b/test/regression/basic_weight_windows/input.py
index 38d3e9805..a475a125e 100644
--- a/test/regression/basic_weight_windows/input.py
+++ b/test/regression/basic_weight_windows/input.py
@@ -5,6 +5,9 @@
 
 os.environ["MCDC_LIB"] = "../mcdc-regression_test_data/"
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Basic weight windows")
+
 # Uses Pincell model as the basis
 
 # Material
@@ -31,17 +34,19 @@
 y0 = mcdc.Surface.PlaneY(y=-pitch / 2, boundary_condition="reflective")
 y1 = mcdc.Surface.PlaneY(y=pitch / 2, boundary_condition="reflective")
 #
-mcdc.Cell(-cylinder, fill=fuel)
-mcdc.Cell(+x0 & -x1 & +y0 & -y1 & +cylinder, fill=moderator)
+fuel_cell = mcdc.Cell(-cylinder, fill=fuel)
+moderator_cell = mcdc.Cell(+x0 & -x1 & +y0 & -y1 & +cylinder, fill=moderator)
+simulation.set_model([fuel_cell, moderator_cell])
 
 # Source
-mcdc.Source(position=[0.0, 0.0, 0.0], isotropic=True, time=0.0, energy=14.1e6)
+source = mcdc.Source(position=[0.0, 0.0, 0.0], isotropic=True, time=0.0, energy=14.1e6)
+simulation.set_sources([source])
 
 # Setting
-mcdc.settings.N_particle = 20
-mcdc.settings.N_batch = 2
-mcdc.settings.time_boundary = 1.0
-mcdc.settings.active_bank_buffer = 1000
+simulation.settings.N_particle = 20
+simulation.settings.N_batch = 2
+simulation.settings.time_boundary = 1.0
+simulation.settings.active_bank_buffer = 1000
 
 # Mesh
 Nx, Ny = 20, 20
@@ -50,7 +55,8 @@
 mesh = mcdc.MeshUniform(x=(x0, dx, Nx), y=(y0, dy, Ny))
 
 # Tally
-mcdc.Tally(mesh=mesh, scores=["flux"])
+tally = mcdc.Tally(mesh=mesh, scores=["flux"])
+simulation.set_tallies([tally])
 
 # Weight windows
 ww_array = np.ones((1, 20, 20, 1, 3))
@@ -58,6 +64,6 @@
 ww_array[..., 0] = 0.55  # Forces roulette on split particles from 1.0
 ww_array[..., 1] = 0.7  # arbitrary in the middle
 ww_array[..., 2] = 0.9  # forces splitting on all particles born with w=1.0
-mcdc.simulation.weight_windows(ww_array, mesh=mesh)
+simulation.weight_windows(ww_array, mesh=mesh)
 
-mcdc.run()
+simulation.run()
diff --git a/test/regression/c5g7_2d_k_eigenvalue/input.py b/test/regression/c5g7_2d_k_eigenvalue/input.py
index 2b8a87d3c..11cb111e9 100644
--- a/test/regression/c5g7_2d_k_eigenvalue/input.py
+++ b/test/regression/c5g7_2d_k_eigenvalue/input.py
@@ -3,6 +3,9 @@
 
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("C5G7 2-D k-eigenvalue")
+
 # =============================================================================
 # Materials
 # =============================================================================
@@ -167,18 +170,19 @@ def set_mat(mat):
 )
 
 # Root universe
-mcdc.simulation.set_root_universe(cells=[core])
+simulation.set_model([core])
 
 # =============================================================================
 # Set source
 # =============================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     x=[0.0, pitch * 17 * 2],
     y=[-pitch * 17 * 2, 0.0],
     isotropic=True,
     energy_group=6,
 )
+simulation.set_sources([source])
 
 # =============================================================================
 # Set tallies, settings, techniques, and run MC/DC
@@ -189,19 +193,19 @@ def set_mat(mat):
     x=np.linspace(0.0, pitch * 17 * 3, 17 * 3 + 1),
     y=np.linspace(-pitch * 17 * 3, 0.0, 17 * 3 + 1),
 )
-mcdc.Tally(mesh=mesh, scores=["flux"])
+tally = mcdc.Tally(mesh=mesh, scores=["flux"])
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 20
-mcdc.settings.census_bank_buffer_ratio = 4.0
-mcdc.settings.source_bank_buffer_ratio = 3.0
-mcdc.settings.set_eigenmode(N_inactive=1, N_active=2, gyration_radius="infinite-z")
+simulation.settings.N_particle = 20
+simulation.settings.census_bank_buffer_ratio = 4.0
+simulation.settings.source_bank_buffer_ratio = 3.0
+simulation.settings.set_eigenmode(
+    N_inactive=1, N_active=2, gyration_radius="infinite-z"
+)
 
 # Techniques
-mcdc.simulation.population_control()
+simulation.population_control()
 
 # Run
-mcdc.settings.set_eigenmode(N_inactive=1, N_active=2, gyration_radius="infinite-z")
-
-
-mcdc.run()
+simulation.run()
diff --git a/test/regression/cooper2/input.py b/test/regression/cooper2/input.py
index be89385db..b2b5b0809 100644
--- a/test/regression/cooper2/input.py
+++ b/test/regression/cooper2/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Cooper problem 2")
+
 # =============================================================================
 # Set model
 # =============================================================================
@@ -26,22 +29,24 @@
 sy3 = mcdc.Surface.PlaneY(y=4.0, boundary_condition="vacuum")
 
 # Set cells
-mcdc.Cell(region=+sx1 & -sx2 & +sy1 & -sy2, fill=m_room)
-mcdc.Cell(region=+sx1 & -sx4 & +sy2 & -sy3, fill=m_room)
-mcdc.Cell(region=+sx3 & -sx4 & +sy1 & -sy2, fill=m_room)
-mcdc.Cell(region=+sx2 & -sx3 & +sy1 & -sy2, fill=m_barrier)
+room_lower_left = mcdc.Cell(region=+sx1 & -sx2 & +sy1 & -sy2, fill=m_room)
+room_upper = mcdc.Cell(region=+sx1 & -sx4 & +sy2 & -sy3, fill=m_room)
+room_lower_right = mcdc.Cell(region=+sx3 & -sx4 & +sy1 & -sy2, fill=m_room)
+barrier = mcdc.Cell(region=+sx2 & -sx3 & +sy1 & -sy2, fill=m_barrier)
+simulation.set_model([room_lower_left, room_upper, room_lower_right, barrier])
 
 # =============================================================================
 # Set source
 # =============================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     x=[0.0, 1.0],
     y=[0.0, 1.0],
     isotropic=True,
     energy_group=0,
     time=0.0,
 )
+simulation.set_sources([source])
 
 # =============================================================================
 # Set tallies, settings, techniques, and run MC/DC
@@ -49,15 +54,16 @@
 
 # Tallies
 mesh = mcdc.MeshUniform(x=(0.0, 0.1, 40), y=(0.0, 0.1, 40))
-mcdc.Tally(mesh=mesh, scores=["flux"])
+tally = mcdc.Tally(mesh=mesh, scores=["flux"])
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 1000
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 1000
+simulation.settings.N_batch = 2
 
 # Techniques
-mcdc.simulation.implicit_capture()
-mcdc.simulation.global_weight_roulette(0.1, 1.0)
+simulation.implicit_capture()
+simulation.global_weight_roulette(0.1, 1.0)
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/fuel_array_packaged/input.py b/test/regression/fuel_array_packaged/input.py
index 551123012..8bf04d9a0 100644
--- a/test/regression/fuel_array_packaged/input.py
+++ b/test/regression/fuel_array_packaged/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Packaged fuel array")
+
 # ======================================================================================
 # Materials
 # ======================================================================================
@@ -69,13 +72,14 @@
 )
 
 # Root universe
-mcdc.simulation.set_root_universe(cells=[assembly_left, assembly_right])
+simulation.set_model([assembly_left, assembly_right])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 
-mcdc.Source(x=[-0.1, 0.1], isotropic=True, energy_group=0)
+source = mcdc.Source(x=[-0.1, 0.1], isotropic=True, energy_group=0)
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
@@ -86,23 +90,31 @@
     x=np.linspace(-10, 10, 201),
     z=np.linspace(-5, 5, 101),
 )
-mcdc.Tally(mesh=mesh, scores=["fission"])
+tally = mcdc.Tally(mesh=mesh, scores=["fission"])
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 100
-mcdc.settings.N_batch = 2
-mcdc.settings.active_bank_buffer = 1000
+simulation.settings.N_particle = 100
+simulation.settings.N_batch = 2
+simulation.settings.active_bank_buffer = 1000
 
 # Run (or visualize)
 visualize = False
 if not visualize:
-    mcdc.run()
+    simulation.run()
 else:
     colors = {
         fuel: "red",
         cover: "gray",
         water: "blue",
     }
-    mcdc.visualize(
-        "xz", y=0.0, x=[-11.0, 11.0], z=[-6, 6], pixels=(400, 400), colors=colors
+    simulation.visualize_model(
+        vis_plane="xz",
+        y=0.0,
+        x=[-11.0, 11.0],
+        z=[-6, 6],
+        pixels=(400, 400),
+        colors=colors,
+        time=[0.0],
+        save_as=None,
     )
diff --git a/test/regression/inf_shem361/input.py b/test/regression/inf_shem361/input.py
index 60b97b20c..4d7b45c71 100644
--- a/test/regression/inf_shem361/input.py
+++ b/test/regression/inf_shem361/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Infinite SHEM-361")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -36,26 +39,29 @@
 
 # Set cells
 c = mcdc.Cell(region=+s1 & -s2, fill=m)
+simulation.set_model([c])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     position=(0.0, 0.0, 0.0), isotropic=True, energy_group=np.array([[360], [1.0]])
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
 # ======================================================================================
 
 # Tallies
-mcdc.Tally(scores=["flux"], energy="all_groups")
+tally = mcdc.Tally(scores=["flux"], energy="all_groups")
+simulation.set_tallies([tally])
 
-# Swttings
-mcdc.settings.N_particle = 25
-mcdc.settings.N_batch = 2
-mcdc.settings.active_bank_buffer = 1000
+# Settings
+simulation.settings.N_particle = 25
+simulation.settings.N_batch = 2
+simulation.settings.active_bank_buffer = 1000
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/inf_shem361_k_eigenvalue/input.py b/test/regression/inf_shem361_k_eigenvalue/input.py
index e57e0b691..cf7df499a 100644
--- a/test/regression/inf_shem361_k_eigenvalue/input.py
+++ b/test/regression/inf_shem361_k_eigenvalue/input.py
@@ -2,6 +2,9 @@
 
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Infinite SHEM-361 k-eigenvalue")
+
 # =============================================================================
 # Set model
 # =============================================================================
@@ -35,30 +38,33 @@
 
 # Set cells
 c = mcdc.Cell(region=+s1 & -s2, fill=m)
+simulation.set_model([c])
 
 # =============================================================================
 # Set initial source
 # =============================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     position=(0.0, 0.0, 0.0), isotropic=True, energy_group=np.array([[360], [1.0]])
 )
+simulation.set_sources([source])
 
 # =============================================================================
 # Set tallies, settings, techniques, and run MC/DC
 # =============================================================================
 
 # Tallies
-mcdc.Tally(scores=["flux"], energy="all_groups")
+tally = mcdc.Tally(scores=["flux"], energy="all_groups")
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 70
-mcdc.settings.source_bank_buffer_ratio = 2.0
-mcdc.settings.census_bank_buffer_ratio = 3.0
-mcdc.settings.set_eigenmode(N_inactive=1, N_active=2)
+simulation.settings.N_particle = 70
+simulation.settings.source_bank_buffer_ratio = 2.0
+simulation.settings.census_bank_buffer_ratio = 3.0
+simulation.settings.set_eigenmode(N_inactive=1, N_active=2)
 
 # Techniques
-mcdc.simulation.population_control()
+simulation.population_control()
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/inf_shem361_td/input.py b/test/regression/inf_shem361_td/input.py
index 58b54f997..bb7bf1090 100644
--- a/test/regression/inf_shem361_td/input.py
+++ b/test/regression/inf_shem361_td/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Infinite SHEM-361 time dependent")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -38,30 +41,33 @@
 
 # Set cells
 c = mcdc.Cell(region=+s1 & -s2, fill=m)
+simulation.set_model([c])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     position=(0.0, 0.0, 0.0), isotropic=True, energy_group=np.array([[360], [1.0]])
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
 # ======================================================================================
 
 # Tallies
-mcdc.Tally(
+tally = mcdc.Tally(
     scores=["flux"],
     time=np.insert(np.logspace(-8, 1, 100), 0, 0.0),
     energy="all_groups",
 )
+simulation.set_tallies([tally])
 
-# Swttings
-mcdc.settings.N_particle = 50
-mcdc.settings.N_batch = 2
-mcdc.settings.active_bank_buffer = 1000
+# Settings
+simulation.settings.N_particle = 50
+simulation.settings.N_batch = 2
+simulation.settings.active_bank_buffer = 1000
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/inf_shem361_td_census/input.py b/test/regression/inf_shem361_td_census/input.py
index 525615b0e..06f685419 100644
--- a/test/regression/inf_shem361_td_census/input.py
+++ b/test/regression/inf_shem361_td_census/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Infinite SHEM-361 time-dependent census")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -38,36 +41,39 @@
 
 # Set cells
 c = mcdc.Cell(region=+s1 & -s2, fill=m)
+simulation.set_model([c])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     position=(0.0, 0.0, 0.0), isotropic=True, energy_group=np.array([[360], [1.0]])
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, techniques, and run MC/DC
 # ======================================================================================
 
 # Tallies
-mcdc.Tally(
+tally = mcdc.Tally(
     scores=["flux"],
     time=np.insert(np.logspace(-8, 1, 100), 0, 0.0),
     energy="all_groups",
 )
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 40
-mcdc.settings.N_batch = 2
-mcdc.settings.set_time_census(np.logspace(-5, 1, 6))
-mcdc.settings.active_bank_buffer = 1000
-mcdc.settings.census_bank_buffer_ratio = 5.0
-mcdc.settings.source_bank_buffer_ratio = 5.0
+simulation.settings.N_particle = 40
+simulation.settings.N_batch = 2
+simulation.settings.set_time_census(np.logspace(-5, 1, 6))
+simulation.settings.active_bank_buffer = 1000
+simulation.settings.census_bank_buffer_ratio = 5.0
+simulation.settings.source_bank_buffer_ratio = 5.0
 
 # Techniques
-mcdc.simulation.population_control()
+simulation.population_control()
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/kobayashi3-TD/input.py b/test/regression/kobayashi3-TD/input.py
index 09776f81c..418c6f819 100644
--- a/test/regression/kobayashi3-TD/input.py
+++ b/test/regression/kobayashi3-TD/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Kobayashi 3-D time dependent")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -41,13 +44,14 @@
 # Shield
 box = +sx1 & -sx5 & +sy1 & -sy5 & +sz1 & -sz5
 shield_cell = mcdc.Cell(region=box & ~void_channel, fill=m)
+simulation.set_model([source_cell, void_cell, shield_cell])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 # The source pulses in t=[0,5]
 
-mcdc.Source(
+source = mcdc.Source(
     x=[0.0, 10.0],
     y=[0.0, 10.0],
     z=[0.0, 10.0],
@@ -55,6 +59,7 @@
     energy_group=0,
     time=[0.0, 50.0],
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, techniques, and run MC/DC
@@ -62,18 +67,21 @@
 
 # Tallies
 time_grid = np.linspace(0.0, 200.0, 21)
-mcdc.Tally(cell=source_cell, scores=["flux"], time=time_grid)
-mcdc.Tally(cell=void_cell, scores=["flux"], time=time_grid)
-mcdc.Tally(cell=shield_cell, scores=["flux"], time=time_grid)
+source_tally = mcdc.Tally(cell=source_cell, scores=["flux"], time=time_grid)
+void_tally = mcdc.Tally(cell=void_cell, scores=["flux"], time=time_grid)
+shield_tally = mcdc.Tally(cell=shield_cell, scores=["flux"], time=time_grid)
 mesh = mcdc.MeshUniform(x=(0.0, 1.0, 60), y=(0.0, 1.0, 100))
-mcdc.Tally(mesh=mesh, scores=["flux"], time=time_grid)
-mcdc.Tally(scores=["density"], time=time_grid)
+mesh_tally = mcdc.Tally(mesh=mesh, scores=["flux"], time=time_grid)
+density_tally = mcdc.Tally(scores=["density"], time=time_grid)
+simulation.set_tallies(
+    [source_tally, void_tally, shield_tally, mesh_tally, density_tally]
+)
 
 # Settings
-mcdc.settings.N_particle = 25
+simulation.settings.N_particle = 25
 
 # Techniques
-mcdc.simulation.implicit_capture()
+simulation.implicit_capture()
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/kornreich/input.py b/test/regression/kornreich/input.py
index 309bcc431..248ecb548 100644
--- a/test/regression/kornreich/input.py
+++ b/test/regression/kornreich/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Kornreich")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -27,14 +30,16 @@
 s3 = mcdc.Surface.PlaneX(x=2.5, boundary_condition="vacuum")
 
 # Set cells
-mcdc.Cell(region=+s1 & -s2, fill=m1)
-mcdc.Cell(region=+s2 & -s3, fill=m2)
+cell_1 = mcdc.Cell(region=+s1 & -s2, fill=m1)
+cell_2 = mcdc.Cell(region=+s2 & -s3, fill=m2)
+simulation.set_model([cell_1, cell_2])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 
-mcdc.Source(x=[0.0, 2.5], isotropic=True, energy_group=0)
+source = mcdc.Source(x=[0.0, 2.5], isotropic=True, energy_group=0)
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
@@ -68,13 +73,14 @@
         ]
     )
 )
-mcdc.Tally(mesh=mesh, scores=["flux"])
+tally = mcdc.Tally(mesh=mesh, scores=["flux"])
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 100
-mcdc.settings.census_bank_buffer_ratio = 3.0
-mcdc.settings.source_bank_buffer_ratio = 3.0
-mcdc.settings.set_eigenmode(N_inactive=1, N_active=2, gyration_radius="only-x")
+simulation.settings.N_particle = 100
+simulation.settings.census_bank_buffer_ratio = 3.0
+simulation.settings.source_bank_buffer_ratio = 3.0
+simulation.settings.set_eigenmode(N_inactive=1, N_active=2, gyration_radius="only-x")
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/lockwood/input.py b/test/regression/lockwood/input.py
index 4784ed17b..cf407b54b 100644
--- a/test/regression/lockwood/input.py
+++ b/test/regression/lockwood/input.py
@@ -7,6 +7,9 @@
 # Set the XS library directory
 os.environ["MCDC_LIB"] = "../mcdc-regression_test_data/"
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Lockwood")
+
 # =============================================================================
 # Set problem parameters
 # =============================================================================
@@ -56,19 +59,21 @@
 
 s2 = mcdc.Surface.PlaneZ(z=L, boundary_condition="vacuum")
 
-mcdc.Cell(region=+s1 & -s2, fill=mat)
+cell = mcdc.Cell(region=+s1 & -s2, fill=mat)
+simulation.set_model([cell])
 
 # =============================================================================
 # Set source
 # =============================================================================
 # Parallel beam of 1 MeV electrons entering at z=0
 
-mcdc.Source(
+source = mcdc.Source(
     z=[z0 + TINY, z0 + TINY],
     particle_type="electron",
     energy=np.array([[ENERGY - 1, ENERGY + 1], [0.5, 0.5]]),
     direction=[math.sin(THETA), 0.0 + TINY, math.cos(THETA)],
 )
+simulation.set_sources([source])
 
 # =============================================================================
 # Set tally
@@ -77,20 +82,18 @@
 z_bins = np.linspace(0.0, L, N_LAYERS + 1)
 mesh = mcdc.MeshStructured(z=z_bins)
 
-mcdc.Tally(name="edep", mesh=mesh, scores=["energy_deposition"])
-
-mcdc.Tally(name="flux", scores=["flux"], mesh=mesh)
-
-mcdc.Tally(name="s1_current", surface=s1, scores=["current-net"])
-
-mcdc.Tally(name="s2_current", surface=s2, scores=["current-net"])
+edep_tally = mcdc.Tally(name="edep", mesh=mesh, scores=["energy_deposition"])
+flux_tally = mcdc.Tally(name="flux", scores=["flux"], mesh=mesh)
+s1_current = mcdc.Tally(name="s1_current", surface=s1, scores=["current-net"])
+s2_current = mcdc.Tally(name="s2_current", surface=s2, scores=["current-net"])
+simulation.set_tallies([edep_tally, flux_tally, s1_current, s2_current])
 
 # =============================================================================
 # Settings and run
 # =============================================================================
 
-mcdc.settings.set_transported_particles(["electron"])
-mcdc.settings.N_particle = N_PARTICLES
-mcdc.settings.active_bank_buffer = N_PARTICLES * 10
+simulation.settings.set_transported_particles(["electron"])
+simulation.settings.N_particle = N_PARTICLES
+simulation.settings.active_bank_buffer = N_PARTICLES * 10
 
-mcdc.run()
+simulation.run()
diff --git a/test/regression/moving_pellet/input.py b/test/regression/moving_pellet/input.py
index 77148b19f..ae97167a2 100644
--- a/test/regression/moving_pellet/input.py
+++ b/test/regression/moving_pellet/input.py
@@ -2,6 +2,9 @@
 
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Moving pellet")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -39,17 +42,18 @@
 
 # Make cells
 fuel_pellet_region = +bot_z & -top_z & -cylinder_z
-mcdc.Cell(region=fuel_pellet_region, fill=fuel)
-mcdc.Cell(
+fuel_cell = mcdc.Cell(region=fuel_pellet_region, fill=fuel)
+air_cell = mcdc.Cell(
     region=~fuel_pellet_region & +min_x & -max_x & +min_y & -max_y & +min_z & -max_z,
     fill=air,
 )
+simulation.set_model([fuel_cell, air_cell])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     x=[2.0, 3.0],
     y=[-0.5, 0.5],
     z=[-0.5, 0.5],
@@ -57,6 +61,7 @@
     energy_group=0,
     time=[0.0, 9.0],
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
@@ -67,24 +72,25 @@
     x=np.linspace(-5, 5, 101),
     z=np.linspace(-10, 10, 101),
 )
-mcdc.Tally(mesh=mesh, scores=["fission"], time=np.linspace(0, 9, 46))
+tally = mcdc.Tally(mesh=mesh, scores=["fission"], time=np.linspace(0, 9, 46))
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 50
-mcdc.settings.N_batch = 2
-mcdc.settings.active_bank_buffer = 1000
+simulation.settings.N_particle = 50
+simulation.settings.N_batch = 2
+simulation.settings.active_bank_buffer = 1000
 
 # Run (or visualize)
 visualize = False
 if not visualize:
-    mcdc.run()
+    simulation.run()
 else:
     colors = {
         fuel: "red",
         air: "blue",
     }
-    mcdc.visualize(
-        "xz",
+    simulation.visualize_model(
+        vis_plane="xz",
         y=0.0,
         x=[-5.0, 5.0],
         z=[-10, 10],
diff --git a/test/regression/moving_source/input.py b/test/regression/moving_source/input.py
index 9fa587501..219f41a60 100644
--- a/test/regression/moving_source/input.py
+++ b/test/regression/moving_source/input.py
@@ -2,6 +2,9 @@
 
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Moving source")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -22,7 +25,8 @@
 max_z = mcdc.Surface.PlaneZ(z=10.0, boundary_condition="vacuum")
 
 # Make cells
-mcdc.Cell(region=+min_x & -max_x & +min_y & -max_y & +min_z & -max_z, fill=air)
+cell = mcdc.Cell(region=+min_x & -max_x & +min_y & -max_y & +min_z & -max_z, fill=air)
+simulation.set_model([cell])
 
 # ======================================================================================
 # Set source
@@ -38,6 +42,7 @@
     time=[0.0, 10.0],
 )
 src.move([[1.0, 0.0, 0.0], [-0.5, 2.0, 0.0], [0.0, -3.0, 0.0]], [7.0, 2.0, 1.0])
+simulation.set_sources([src])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
@@ -48,12 +53,13 @@
     x=np.linspace(-5.0, 5.0, 21),
     y=np.linspace(-5.0, 5.0, 21),
 )
-mcdc.Tally(mesh=mesh, scores=["flux"], time=np.linspace(0, 10, 11))
+tally = mcdc.Tally(mesh=mesh, scores=["flux"], time=np.linspace(0, 10, 11))
+simulation.set_tallies([tally])
 
 
 # Settings
-mcdc.settings.N_particle = 1000
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 1000
+simulation.settings.N_batch = 2
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/pincell-energy_deposition/input.py b/test/regression/pincell-energy_deposition/input.py
index 9504e18ff..8fdbaf569 100644
--- a/test/regression/pincell-energy_deposition/input.py
+++ b/test/regression/pincell-energy_deposition/input.py
@@ -4,6 +4,9 @@
 
 os.environ["MCDC_LIB"] = "../mcdc-regression_test_data/"
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Pincell energy deposition")
+
 # Material
 fuel = mcdc.Material(
     nuclide_composition={
@@ -28,17 +31,19 @@
 y0 = mcdc.Surface.PlaneY(y=-pitch / 2, boundary_condition="reflective")
 y1 = mcdc.Surface.PlaneY(y=pitch / 2, boundary_condition="reflective")
 
-mcdc.Cell(-cylinder, fill=fuel)
-mcdc.Cell(+x0 & -x1 & +y0 & -y1 & +cylinder, fill=moderator)
+fuel_cell = mcdc.Cell(-cylinder, fill=fuel)
+moderator_cell = mcdc.Cell(+x0 & -x1 & +y0 & -y1 & +cylinder, fill=moderator)
+simulation.set_model([fuel_cell, moderator_cell])
 
 # Source
-mcdc.Source(position=[0.0, 0.0, 0.0], isotropic=True, time=0.0, energy=14.1e6)
+source = mcdc.Source(position=[0.0, 0.0, 0.0], isotropic=True, time=0.0, energy=14.1e6)
+simulation.set_sources([source])
 
 # Settings
-mcdc.settings.N_particle = 20
-mcdc.settings.N_batch = 2
-mcdc.settings.time_boundary = 1.0
-mcdc.settings.active_bank_buffer = 1000
+simulation.settings.N_particle = 20
+simulation.settings.N_batch = 2
+simulation.settings.time_boundary = 1.0
+simulation.settings.active_bank_buffer = 1000
 
 # Edep tally
 mesh = mcdc.MeshUniform(
@@ -46,6 +51,7 @@
     y=(-pitch / 2, pitch / 8, 8),
 )
 
-mcdc.Tally(name="edep_mesh", mesh=mesh, scores=["energy_deposition"])
+tally = mcdc.Tally(name="edep_mesh", mesh=mesh, scores=["energy_deposition"])
+simulation.set_tallies([tally])
 
-mcdc.run()
+simulation.run()
diff --git a/test/regression/pincell-k_eigenvalue/input.py b/test/regression/pincell-k_eigenvalue/input.py
index b497d7662..79f29aaf2 100644
--- a/test/regression/pincell-k_eigenvalue/input.py
+++ b/test/regression/pincell-k_eigenvalue/input.py
@@ -4,6 +4,9 @@
 
 os.environ["MCDC_LIB"] = "../mcdc-regression_test_data/"
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Pincell k-eigenvalue")
+
 # Material
 fuel = mcdc.Material(
     nuclide_composition={
@@ -28,24 +31,27 @@
 y0 = mcdc.Surface.PlaneY(y=-pitch / 2, boundary_condition="reflective")
 y1 = mcdc.Surface.PlaneY(y=pitch / 2, boundary_condition="reflective")
 #
-mcdc.Cell(-cylinder, fill=fuel)
-mcdc.Cell(+x0 & -x1 & +y0 & -y1 & +cylinder, fill=moderator)
+fuel_cell = mcdc.Cell(-cylinder, fill=fuel)
+moderator_cell = mcdc.Cell(+x0 & -x1 & +y0 & -y1 & +cylinder, fill=moderator)
+simulation.set_model([fuel_cell, moderator_cell])
 
 # Source
-mcdc.Source(position=[0.0, 0.0, 0.0], isotropic=True, energy=14.1e6)
+source = mcdc.Source(position=[0.0, 0.0, 0.0], isotropic=True, energy=14.1e6)
+simulation.set_sources([source])
 
 # Setting
-mcdc.settings.N_particle = 30
-mcdc.settings.active_bank_buffer = 1000
-mcdc.settings.census_bank_buffer_ratio = 3.0
-mcdc.settings.source_bank_buffer_ratio = 3.0
-mcdc.settings.set_eigenmode(N_inactive=1, N_active=2)
+simulation.settings.N_particle = 30
+simulation.settings.active_bank_buffer = 1000
+simulation.settings.census_bank_buffer_ratio = 3.0
+simulation.settings.source_bank_buffer_ratio = 3.0
+simulation.settings.set_eigenmode(N_inactive=1, N_active=2)
 
 # Tally
 e_min, e_max = 1e-5, 20.0e6
 groups = 500
 energies = np.logspace(np.log10(e_min), np.log10(e_max), groups + 1)
 
-mcdc.Tally(scores=["flux"], energy=energies)
+tally = mcdc.Tally(scores=["flux"], energy=energies)
+simulation.set_tallies([tally])
 
-mcdc.run()
+simulation.run()
diff --git a/test/regression/pincell/input.py b/test/regression/pincell/input.py
index 5b762177d..bbc8c9726 100644
--- a/test/regression/pincell/input.py
+++ b/test/regression/pincell/input.py
@@ -4,6 +4,9 @@
 
 os.environ["MCDC_LIB"] = "../mcdc-regression_test_data/"
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Pincell")
+
 # Material
 fuel = mcdc.Material(
     nuclide_composition={
@@ -28,17 +31,19 @@
 y0 = mcdc.Surface.PlaneY(y=-pitch / 2, boundary_condition="reflective")
 y1 = mcdc.Surface.PlaneY(y=pitch / 2, boundary_condition="reflective")
 #
-mcdc.Cell(-cylinder, fill=fuel)
-mcdc.Cell(+x0 & -x1 & +y0 & -y1 & +cylinder, fill=moderator)
+fuel_cell = mcdc.Cell(-cylinder, fill=fuel)
+moderator_cell = mcdc.Cell(+x0 & -x1 & +y0 & -y1 & +cylinder, fill=moderator)
+simulation.set_model([fuel_cell, moderator_cell])
 
 # Source
-mcdc.Source(position=[0.0, 0.0, 0.0], isotropic=True, time=0.0, energy=14.1e6)
+source = mcdc.Source(position=[0.0, 0.0, 0.0], isotropic=True, time=0.0, energy=14.1e6)
+simulation.set_sources([source])
 
 # Setting
-mcdc.settings.N_particle = 20
-mcdc.settings.N_batch = 2
-mcdc.settings.time_boundary = 1.0
-mcdc.settings.active_bank_buffer = 1000
+simulation.settings.N_particle = 20
+simulation.settings.N_batch = 2
+simulation.settings.time_boundary = 1.0
+simulation.settings.active_bank_buffer = 1000
 
 # Tally
 t_grid = np.insert(np.logspace(-9, -4, 200), 0, 0.0)
@@ -46,6 +51,7 @@
 groups = 500
 energies = np.logspace(np.log10(e_min), np.log10(e_max), groups + 1)
 
-mcdc.Tally(scores=["flux"], time=t_grid, energy=energies)
+tally = mcdc.Tally(scores=["flux"], time=t_grid, energy=energies)
+simulation.set_tallies([tally])
 
-mcdc.run()
+simulation.run()
diff --git a/test/regression/slab_absorbium/input.py b/test/regression/slab_absorbium/input.py
index e46df04da..2046ecfbd 100644
--- a/test/regression/slab_absorbium/input.py
+++ b/test/regression/slab_absorbium/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Slab absorbium")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -18,29 +21,36 @@
 s4 = mcdc.Surface.PlaneZ(z=6.0, boundary_condition="vacuum")
 
 # Set cells
-mcdc.Cell(region=+s1 & -s2, fill=m2)
-mcdc.Cell(region=+s2 & -s3, fill=m3)
-mcdc.Cell(region=+s3 & -s4, fill=m1)
+cell_1 = mcdc.Cell(region=+s1 & -s2, fill=m2)
+cell_2 = mcdc.Cell(region=+s2 & -s3, fill=m3)
+cell_3 = mcdc.Cell(region=+s3 & -s4, fill=m1)
+simulation.set_model([cell_1, cell_2, cell_3])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 # Uniform isotropic source throughout the domain
 
-mcdc.Source(z=[0.0, 6.0], isotropic=True, energy_group=0)
+source = mcdc.Source(z=[0.0, 6.0], isotropic=True, energy_group=0)
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, and run mcdc
 # ======================================================================================
 
 # Tallies
-mcdc.Tally(surface=s4, scores=["current-net"])
+surface_tally = mcdc.Tally(surface=s4, scores=["current-net"])
 mesh = mcdc.MeshStructured(z=np.linspace(0.0, 6.0, 61))
-mcdc.Tally(mesh=mesh, mu=np.linspace(-1.0, 1.0, 32 + 1), scores=["flux", "collision"])
+mesh_tally = mcdc.Tally(
+    mesh=mesh,
+    mu=np.linspace(-1.0, 1.0, 32 + 1),
+    scores=["flux", "collision"],
+)
+simulation.set_tallies([surface_tally, mesh_tally])
 
 # Settings
-mcdc.settings.N_particle = 100
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 100
+simulation.settings.N_batch = 2
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/slab_isobeam_td/input.py b/test/regression/slab_isobeam_td/input.py
index 63f1927b9..15c1e91a1 100644
--- a/test/regression/slab_isobeam_td/input.py
+++ b/test/regression/slab_isobeam_td/input.py
@@ -2,6 +2,9 @@
 
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Slab isotropic beam time dependent")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -15,19 +18,21 @@
 s2 = mcdc.Surface.PlaneX(x=5.0, boundary_condition="vacuum")
 
 # Set cells
-mcdc.Cell(region=+s1 & -s2, fill=m)
+cell = mcdc.Cell(region=+s1 & -s2, fill=m)
+simulation.set_model([cell])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 # Isotropic beam from left-end
 
-mcdc.Source(
+source = mcdc.Source(
     position=(0.0, 0.0, 0.0),
     white_direction=(1.0, 0.0, 0.0),
     energy_group=0,
     time=[0.0, 5.0],
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
@@ -35,15 +40,16 @@
 
 # Tallies
 mesh = mcdc.MeshUniform(x=(0.0, 0.1, 50))
-mcdc.Tally(
+tally = mcdc.Tally(
     mesh=mesh,
     scores=["flux"],
     time=np.linspace(0.0, 5.0, 51),
 )
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 100
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 100
+simulation.settings.N_batch = 2
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/slab_isobeam_td_census/input.py b/test/regression/slab_isobeam_td_census/input.py
index f665e5c78..d2b567e9c 100644
--- a/test/regression/slab_isobeam_td_census/input.py
+++ b/test/regression/slab_isobeam_td_census/input.py
@@ -2,6 +2,9 @@
 
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Slab isotropic beam time-dependent census")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -15,19 +18,21 @@
 s2 = mcdc.Surface.PlaneX(x=5.0, boundary_condition="vacuum")
 
 # Set cells
-mcdc.Cell(region=+s1 & -s2, fill=m)
+cell = mcdc.Cell(region=+s1 & -s2, fill=m)
+simulation.set_model([cell])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 # Isotropic beam from left-end
 
-mcdc.Source(
+source = mcdc.Source(
     position=(1e-10, 0.0, 0.0),
     white_direction=(1.0, 0.0, 0.0),
     energy_group=0,
     time=[0.0, 5.0],
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, techniques, and run MC/DC
@@ -35,20 +40,21 @@
 
 # Tallies
 mesh = mcdc.MeshUniform(x=(0.0, 0.1, 50))
-mcdc.Tally(
+tally = mcdc.Tally(
     mesh=mesh,
     scores=["flux"],
     time=np.linspace(0.0, 5.0, 51),
 )
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 100
-mcdc.settings.N_batch = 2
-mcdc.settings.source_bank_buffer_ratio = 5.0
-mcdc.settings.set_time_census(np.linspace(0.0, 5.0, 6)[1:])
+simulation.settings.N_particle = 100
+simulation.settings.N_batch = 2
+simulation.settings.source_bank_buffer_ratio = 5.0
+simulation.settings.set_time_census(np.linspace(0.0, 5.0, 6)[1:])
 
 # Techniques
-mcdc.simulation.population_control()
+simulation.population_control()
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/slab_reed/input.py b/test/regression/slab_reed/input.py
index e2dcd71b6..7d5bc908e 100644
--- a/test/regression/slab_reed/input.py
+++ b/test/regression/slab_reed/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Reed slab")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -21,21 +24,23 @@
 s5 = mcdc.Surface.PlaneZ(z=8.0, boundary_condition="vacuum")
 
 # Set cells
-mcdc.Cell(region=+s1 & -s2, fill=m1)
-mcdc.Cell(region=+s2 & -s3, fill=m2)
-mcdc.Cell(region=+s3 & -s4, fill=m3)
-mcdc.Cell(region=+s4 & -s5, fill=m4)
+cell_1 = mcdc.Cell(region=+s1 & -s2, fill=m1)
+cell_2 = mcdc.Cell(region=+s2 & -s3, fill=m2)
+cell_3 = mcdc.Cell(region=+s3 & -s4, fill=m3)
+cell_4 = mcdc.Cell(region=+s4 & -s5, fill=m4)
+simulation.set_model([cell_1, cell_2, cell_3, cell_4])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 
 # Isotropic source in the absorbing medium
-mcdc.Source(z=[0.0, 2.0], isotropic=True, energy_group=0, probability=50.0)
+source_1 = mcdc.Source(z=[0.0, 2.0], isotropic=True, energy_group=0, probability=50.0)
 
 # Isotropic source in the first half of the outermost medium,
 # with 1/100 strength
-mcdc.Source(z=[5.0, 6.0], isotropic=True, energy_group=0, probability=0.5)
+source_2 = mcdc.Source(z=[5.0, 6.0], isotropic=True, energy_group=0, probability=0.5)
+simulation.set_sources([source_1, source_2])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
@@ -43,11 +48,12 @@
 
 # Tallies
 mesh = mcdc.MeshStructured(z=np.linspace(0.0, 8.0, 81))
-mcdc.Tally(mesh=mesh, scores=["flux"])
+tally = mcdc.Tally(mesh=mesh, scores=["flux"])
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 4000
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 4000
+simulation.settings.N_batch = 2
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/test/regression/sphere_in_cube/input.py b/test/regression/sphere_in_cube/input.py
index 8bedb7bbc..9a5766d2a 100644
--- a/test/regression/sphere_in_cube/input.py
+++ b/test/regression/sphere_in_cube/input.py
@@ -1,6 +1,9 @@
 import numpy as np
 import mcdc
 
+# Create MC/DC simulation
+simulation = mcdc.Simulation("Sphere in cube")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -23,16 +26,17 @@
 
 # Set cells
 # Source
-mcdc.Cell(region=inside_box & ~inside_sphere, fill=pure_s)
+cube_cell = mcdc.Cell(region=inside_box & ~inside_sphere, fill=pure_s)
 
 # Sphere
 sphere_cell = mcdc.Cell(region=inside_sphere, fill=pure_f)
+simulation.set_model([cube_cell, sphere_cell])
 
 # =============================================================================
 # Set source
 # =============================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     x=[0.0, 4.0],
     y=[0.0, 4.0],
     z=[0.0, 4.0],
@@ -40,6 +44,7 @@
     energy_group=0,
     time=[0.0, 50.0],
 )
+simulation.set_sources([source])
 
 # =============================================================================
 # Set tallies, settings, techniques, and run MC/DC
@@ -47,18 +52,19 @@
 
 # Tallies
 mesh = mcdc.MeshUniform(x=(0.0, 4.0, 1), y=(0.0, 4.0, 1), z=(0.0, 4.0, 1))
-mcdc.Tally(
+mesh_tally = mcdc.Tally(
     mesh=mesh,
     scores=["fission"],
 )
-mcdc.Tally(cell=sphere_cell, scores=["fission"])
+cell_tally = mcdc.Tally(cell=sphere_cell, scores=["fission"])
+simulation.set_tallies([mesh_tally, cell_tally])
 
 # Settings
-mcdc.settings.N_particle = 100
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 100
+simulation.settings.N_batch = 2
 
 # Techniques
-mcdc.simulation.implicit_capture()
+simulation.implicit_capture()
 
 # Run
-mcdc.run()
+simulation.run()

From 7dfb5b22e584fc9e2371f2a27ed358902d39dd30 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 15:07:01 +0700
Subject: [PATCH 045/202] update recombine tally

---
 mcdc/__init__.py                             |   1 -
 mcdc/main.py                                 |   4 +
 mcdc/output.py                               | 144 ++++++++++---------
 test/regression/azurv1_census_tally/input.py |   3 -
 4 files changed, 78 insertions(+), 74 deletions(-)

diff --git a/mcdc/__init__.py b/mcdc/__init__.py
index 2685c44c8..bbcd4f153 100644
--- a/mcdc/__init__.py
+++ b/mcdc/__init__.py
@@ -22,4 +22,3 @@
 # ======================================================================================
 
 import mcdc.config
-from mcdc.output import recombine_tallies
diff --git a/mcdc/main.py b/mcdc/main.py
index 27feac275..41a2d9e5d 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -81,6 +81,10 @@ def run_simulation(simulationPy: Simulation):
     # Generate hdf5 output file
     output_module.generate_output(simulation, data, simulationPy)
 
+    # Combine per-batch, per-census tally files into the main output
+    if settings.use_census_based_tally:
+        output_module.recombine_tallies(simulationPy, simulation)
+
     # TIMER: output
     time_output_end = MPI.Wtime()
 
diff --git a/mcdc/output.py b/mcdc/output.py
index 1cf52f5da..74f89c852 100644
--- a/mcdc/output.py
+++ b/mcdc/output.py
@@ -39,6 +39,7 @@ def generate_output(mcdc, data, simulationPy):
 
     # No need to output tally if time census-based tally is used
     if mcdc["settings"]["use_census_based_tally"]:
+        file.close()
         return
 
     # Tallies
@@ -241,21 +242,26 @@ def replace_dataset(file, field, data):
     file.create_dataset(field, data=data)
 
 
-def recombine_tallies():
-    """Combine the tally output into a single file"""
-    import h5py
-    from mpi4py import MPI
+def recombine_tallies(simulationPy, simulation):
+    """Combine census-based tally files into the main output file.
+
+    Parameters
+    ----------
+    simulationPy : mcdc.Simulation
+        Python simulation object containing tally definitions and settings.
+    simulation : numpy.void
+        Packed runtime simulation state. Recombination is performed only by
+        its designated MPI master rank.
+    """
     from mcdc.object_.tally import decode_score_type
 
-    if MPI.COMM_WORLD.Get_rank() > 0:
+    if not simulation["mpi_master"]:
         return
 
-    # Get simulation and settings
-    from mcdc.object_.simulation import simulation
-
-    settings = simulation.settings
+    settings = simulationPy.settings
     if not settings.use_census_based_tally:
         print("Census-based tally is not used, nothing to recombine.")
+        return
 
     # Settings parameters
     base_name = settings.output_name
@@ -265,65 +271,63 @@ def recombine_tallies():
     Nt = frequency * (N_census - 1)
 
     # Append the tally dataset structure to the main output
-    main_file = h5py.File(f"{base_name}.h5", "a")
-    reference_file = h5py.File(f"{base_name}-batch_0-census_0.h5", "r")
-    tally_group = main_file.create_group("tallies")
-    for tally in simulation.tallies:
-        name = f"tallies/{tally.name}"
-        reference_file.copy(name, tally_group)
-    reference_file.close()
-
-    # Set the time grid
-    time_grid = np.zeros(Nt + 1)
-    for i in range(N_census - 1):
-        start = settings.census_time[i - 1] if i > 0 else 0.0
-        end = settings.census_time[i]
-        new_grid = np.linspace(start, end, frequency + 1)
-        offset = i * frequency + 1
-        time_grid[offset : offset + frequency] = new_grid[1:]
-    for tally in simulation.tallies:
-        name = f"tallies/{tally.name}/grid/time"
-        replace_dataset(main_file, name, time_grid)
-
-    # Combine the tallies
-    for tally in simulation.tallies:
-        # The combined shape
-        shape = tally.bin_shape
-        shape[3] = Nt
-
-        for score in tally.scores:
-            score_name = f"tallies/{tally.name}/{decode_score_type(score, True)}"
-
-            mean = np.zeros(shape)
-            sdev = np.zeros(shape)
-
-            # Selective squeeze
-            axes_to_squeeze = [x for x, size in enumerate(shape) if size == 1 and x > 3]
-            mean = np.squeeze(mean, axis=tuple(axes_to_squeeze))
-            sdev = np.squeeze(sdev, axis=tuple(axes_to_squeeze))
-
-            for i_census in range(N_census - 1):
-                # Accumulate sum and sum of square
-                for i_batch in range(N_batch):
-                    file_name = f"{base_name}-batch_{i_batch}-census_{i_census}.h5"
-                    file = h5py.File(file_name, "r")
+    with h5py.File(f"{base_name}.h5", "a") as main_file:
+        if "tallies" in main_file:
+            del main_file["tallies"]
+        tally_group = main_file.create_group("tallies")
+
+        with h5py.File(f"{base_name}-batch_0-census_0.h5", "r") as reference_file:
+            for tally in simulationPy.tallies:
+                name = f"tallies/{tally.name}"
+                reference_file.copy(name, tally_group)
+
+        # Set the time grid
+        time_grid = np.zeros(Nt + 1)
+        for i_census in range(N_census - 1):
+            start = settings.census_time[i_census - 1] if i_census > 0 else 0.0
+            end = settings.census_time[i_census]
+            new_grid = np.linspace(start, end, frequency + 1)
+            offset = i_census * frequency + 1
+            time_grid[offset : offset + frequency] = new_grid[1:]
+        for tally in simulationPy.tallies:
+            name = f"tallies/{tally.name}/grid/time"
+            replace_dataset(main_file, name, time_grid)
+
+        # Combine the tallies
+        for tally in simulationPy.tallies:
+            census_shape = tuple(int(size) for size in tally.bin_shape[:-1])
+            combined_shape = list(census_shape)
+            combined_shape[3] = Nt
+            combined_shape = tuple(combined_shape)
+
+            for score in tally.scores:
+                score_name = f"tallies/{tally.name}/{decode_score_type(score, True)}"
+                mean = np.zeros(combined_shape)
+                second_moment = np.zeros(combined_shape)
+
+                for i_census in range(N_census - 1):
                     offset = i_census * frequency
-
-                    score = file[f"{score_name}/mean"][()]
-                    mean[:, :, :, offset : offset + frequency] += score
-                    sdev[:, :, :, offset : offset + frequency] += score * score
-
-                    file.close()
-
-            # Squeeze
-            mean = np.squeeze(mean)
-            sdev = np.squeeze(sdev)
-
-            # Compute statistics
-            mean /= N_batch
-            sdev = np.sqrt((sdev / N_batch - np.square(mean)) / (N_batch - 1))
-
-            replace_dataset(main_file, f"{score_name}/mean", mean)
-            replace_dataset(main_file, f"{score_name}/sdev", sdev)
-
-    main_file.close()
+                    time_slice = [slice(None)] * len(combined_shape)
+                    time_slice[3] = slice(offset, offset + frequency)
+                    time_slice = tuple(time_slice)
+
+                    for i_batch in range(N_batch):
+                        file_name = f"{base_name}-batch_{i_batch}-census_{i_census}.h5"
+                        with h5py.File(file_name, "r") as file:
+                            score_data = np.asarray(
+                                file[f"{score_name}/mean"][()]
+                            ).reshape(census_shape)
+                        mean[time_slice] += score_data
+                        second_moment[time_slice] += np.square(score_data)
+
+                mean /= N_batch
+                if N_batch > 1:
+                    variance = (second_moment / N_batch - np.square(mean)) / (
+                        N_batch - 1
+                    )
+                    sdev = np.sqrt(np.maximum(variance, 0.0))
+                else:
+                    sdev = np.zeros_like(mean)
+
+                replace_dataset(main_file, f"{score_name}/mean", np.squeeze(mean))
+                replace_dataset(main_file, f"{score_name}/sdev", np.squeeze(sdev))
diff --git a/test/regression/azurv1_census_tally/input.py b/test/regression/azurv1_census_tally/input.py
index ce8459839..358cf705d 100644
--- a/test/regression/azurv1_census_tally/input.py
+++ b/test/regression/azurv1_census_tally/input.py
@@ -61,6 +61,3 @@
 
 # Run
 simulation.run()
-
-# Post-processing
-mcdc.recombine_tallies()

From 15b4fd122d15849dea0ecc763565f8df6fba33ed Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 15:12:56 +0700
Subject: [PATCH 046/202] update k-mode output

---
 mcdc/output.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/mcdc/output.py b/mcdc/output.py
index 74f89c852..5453ca25a 100644
--- a/mcdc/output.py
+++ b/mcdc/output.py
@@ -49,7 +49,7 @@ def generate_output(mcdc, data, simulationPy):
     if mcdc["settings"]["neutron_eigenvalue_mode"]:
         N_cycle = mcdc["settings"]["N_cycle"]
         file.create_dataset(
-            "k_cycle", data=mcdc_get.simulationPy.k_cycle_chunk(0, N_cycle, mcdc, data)
+            "k_cycle", data=mcdc_get.simulation.k_cycle_chunk(0, N_cycle, mcdc, data)
         )
         file.create_dataset("k_mean", data=mcdc["k_avg_running"])
         file.create_dataset("k_sdev", data=mcdc["k_sdv_running"])
@@ -62,9 +62,7 @@ def generate_output(mcdc, data, simulationPy):
         if mcdc["settings"]["use_gyration_radius"]:
             file.create_dataset(
                 "gyration_radius",
-                data=mcdc_get.simulationPy.gyration_radius_chunk(
-                    0, N_cycle, mcdc, data
-                ),
+                data=mcdc_get.simulation.gyration_radius_chunk(0, N_cycle, mcdc, data),
             )
 
     # Save particle?

From 2078fbdd0d23d3acedb1efa7cbfc7a96a9b2920d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 15:16:42 +0700
Subject: [PATCH 047/202] fix complement region bug

---
 mcdc/object_/cell.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index a1bffd266..53935d545 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -315,9 +315,7 @@ def generate_RPN_tokens(region, simulation):
             ):
                 stack += ["|", token.A, token.B]
 
-            elif token.type == "complement" and (
-                isinstance(A, Region) and isinstance(B, Region)
-            ):
+            elif token.type == "complement" and (isinstance(A, Region)):
                 stack += ["~", token.A]
 
             else:

From b8d0f5f1196568532bf33e1802a75e687b4e62ee Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 15:48:35 +0700
Subject: [PATCH 048/202] fix material/nuclide/element compilation

---
 mcdc/main.py                      |   6 +-
 mcdc/object_/distribution.py      |  31 +++++
 mcdc/object_/electron_reaction.py |  28 +++++
 mcdc/object_/element.py           |  42 +++++--
 mcdc/object_/material.py          | 190 ++++++++++++++----------------
 mcdc/object_/neutron_reaction.py  |  40 +++++--
 mcdc/object_/nuclide.py           |  54 ++++++---
 7 files changed, 250 insertions(+), 141 deletions(-)

diff --git a/mcdc/main.py b/mcdc/main.py
index 41a2d9e5d..3a18296d6 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -150,10 +150,10 @@ def prepare(simulationPy):
             continue
 
         if settings.neutron_transport and len(material.nuclides) == 0:
-            set_nuclides_from_elements(material)
+            set_nuclides_from_elements(material, simulationPy)
 
         if settings.electron_transport and len(material.elements) == 0:
-            set_elements_from_nuclides(material)
+            set_elements_from_nuclides(material, simulationPy)
 
     # Set nuclear and atomic data for transported particles
     if settings.neutron_transport:
@@ -166,7 +166,7 @@ def prepare(simulationPy):
 
     if settings.electron_transport:
         for element in simulationPy.elements:
-            element.set_electron_data()
+            element.set_electron_data(simulationPy)
 
     # Set physics mode
     if len(simulationPy.materials) == 0:
diff --git a/mcdc/object_/distribution.py b/mcdc/object_/distribution.py
index ca9adbc73..1837e0bf6 100644
--- a/mcdc/object_/distribution.py
+++ b/mcdc/object_/distribution.py
@@ -177,6 +177,12 @@ def __init__(
             aux=cdf_normalized,
         )
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        self.pdf._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self) -> str:
         text = super().__repr__()
 
@@ -286,6 +292,13 @@ def __init__(
 
             self.tables.append(table)
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        for table in self.tables:
+            table._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self) -> str:
         text = super().__repr__()
 
@@ -366,6 +379,12 @@ def __init__(
             interpolation_boundaries,
         )
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        self.nuclear_temperature._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self) -> str:
         text = super().__repr__()
 
@@ -414,6 +433,12 @@ def __init__(
             interpolation_boundaries,
         )
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        self.nuclear_temperature._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self) -> str:
         text = super().__repr__()
 
@@ -643,6 +668,12 @@ def __init__(
             aux=cdf_normalized,
         )
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        self.pdf._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self) -> str:
         text = super().__repr__()
 
diff --git a/mcdc/object_/electron_reaction.py b/mcdc/object_/electron_reaction.py
index 804605c65..43765a04a 100644
--- a/mcdc/object_/electron_reaction.py
+++ b/mcdc/object_/electron_reaction.py
@@ -151,6 +151,15 @@ def from_h5_group(cls, h5_group):
             subshell_product,
         )
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        for subshell_xs in self.subshell_xs:
+            subshell_xs._compile_into_simulation(simulation)
+        for subshell_product in self.subshell_product:
+            subshell_product._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Number of subshells: {self.N_subshell}\n"
@@ -220,6 +229,13 @@ def from_h5_group(cls, h5_group):
 
         return cls(MT, xs, xs_offset, reference_frame, xs_large, mu)
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        self.xs_large._compile_into_simulation(simulation)
+        self.mu._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Mu cut: {self.mu_cut}\n"
@@ -256,6 +272,12 @@ def from_h5_group(cls, h5_group):
 
         return cls(MT, xs, xs_offset, reference_frame, eloss)
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        self.eloss._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Energy loss: DataTable [ID: {self.eloss.ID}]\n"
@@ -290,6 +312,12 @@ def from_h5_group(cls, h5_group):
 
         return cls(MT, xs, xs_offset, reference_frame, eloss)
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        self.eloss._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Energy loss: DataTable [ID: {self.eloss.ID}]\n"
diff --git a/mcdc/object_/element.py b/mcdc/object_/element.py
index cc292c8cc..16148d8ee 100644
--- a/mcdc/object_/element.py
+++ b/mcdc/object_/element.py
@@ -14,10 +14,11 @@
     ElectronReactionExcitation,
     ElectronReactionIonization,
 )
+from mcdc.print_ import print_error
 
 
 class Element(MCDCObject):
-    """Element data loaded from the MC/DC HDF5 library.
+    """Element definition for the MC/DC HDF5 library.
 
     Parameters
     ----------
@@ -26,8 +27,10 @@ class Element(MCDCObject):
 
     Notes
     -----
-    Construction loads basic atomic properties. Electron reaction cross sections
-    and secondary distributions are loaded later by :meth:`set_electron_data`.
+    Construction records the element identity without accessing the data
+    library. Basic properties are loaded when the element is compiled into a
+    simulation. Electron reaction cross sections and secondary distributions
+    are loaded later by :meth:`set_electron_data`.
     """
 
     # MC/DC framework metadata
@@ -56,16 +59,28 @@ def __init__(self, element_name: str):
 
         self.name = element_name
 
-        # Basic properties
+    def _compile_into_simulation(self, simulation) -> bool:
+        """Load basic properties and register with the owning simulation."""
+        if self.compile_ID == simulation.compile_ID:
+            return False
+
         dir_name = os.getenv("MCDC_LIB")
-        file_name = f"{element_name}.h5"
-        file = h5py.File(f"{dir_name}/{file_name}", "r")
-        self.atomic_weight_ratio = float(file["atomic_weight_ratio"][()])
-        self.atomic_number = int(file["atomic_number"][()])
-        file.close()
+        if dir_name is None:
+            print_error("Environment variable MCDC_LIB is not set")
 
-    def set_electron_data(self):
-        """Load electron cross sections and reaction data from ``MCDC_LIB``."""
+        file_name = f"{self.name}.h5"
+        file_path = os.path.join(dir_name, file_name)
+        if not os.path.isfile(file_path):
+            print_error(f"Element {self.name} is not available in the library")
+
+        with h5py.File(file_path, "r") as file:
+            self.atomic_weight_ratio = float(file["atomic_weight_ratio"][()])
+            self.atomic_number = int(file["atomic_number"][()])
+
+        return super()._compile_into_simulation(simulation)
+
+    def set_electron_data(self, simulation):
+        """Load and register electron reaction data from ``MCDC_LIB``."""
         element_name = self.name
 
         # Load data library
@@ -164,6 +179,11 @@ def set_electron_data(self):
 
         file.close()
 
+        # Register data loaded after model compilation.
+        for reaction_container in rx_containers:
+            for reaction in reaction_container:
+                reaction._compile_into_simulation(simulation)
+
     def __repr__(self):
         text = "\n"
         text += f"Element\n"
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 727bf2f20..0e018432c 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -1,5 +1,4 @@
 import numpy as np
-import os
 
 from numpy import float64
 from numpy.typing import NDArray
@@ -73,8 +72,9 @@ class Material(MaterialBase):
     Notes
     -----
     Exactly one of ``nuclide_composition`` or ``element_composition`` must be
-    supplied. The ``MCDC_LIB`` environment variable must point to the directory
-    containing the corresponding HDF5 data-library files.
+    supplied. Nuclide and element objects are created immediately; their
+    data-library properties are loaded when the material is compiled into a
+    simulation.
 
     Examples
     --------
@@ -129,25 +129,6 @@ def __init__(
         # Temperature
         self.temperature = temperature
 
-        # Dictionary connecting nuclides to respective densities
-        self.nuclide_composition = {}
-
-        # Dictionary connecting elements to respective densities
-        self.element_composition = {}
-
-        # Numba representation of nuclide_composition
-        self.nuclides = []
-        self.nuclide_densities = np.zeros(len(nuclide_composition))
-
-        # Numba representation of element_composition
-        self.elements = []
-        self.element_densities = np.zeros(len(element_composition))
-
-        # Check if library directory is set
-        lib_dir = os.getenv("MCDC_LIB")
-        if lib_dir is None:
-            print_error("Environment variable MCDC_LIB is not set")
-
         # Check that only one composition is supplied
         if len(nuclide_composition) > 0 and len(element_composition) > 0:
             print_error(
@@ -159,65 +140,66 @@ def __init__(
                 "Must specify either nuclide_composition or element_composition"
             )
 
-        # Loop over the items in the elemental composition
-        for i, (key, value) in enumerate(element_composition.items()):
-            element_name = key
-            element_density = value
-
-            # Check if element is already created
-            found = False
-            for element in simulation.elements:
-                if element.name == element_name:
-                    found = True
-                    break
-
-            # Create the element object if needed
-            if not found:
-                element = Element(element_name)
-
-            # Register the element composition
-            self.elements.append(element)
-            self.element_densities[i] = element_density
-            self.element_composition[element] = element_density
-
-        # Loop over the items in the nuclide composition
-        for i, (key, value) in enumerate(nuclide_composition.items()):
-            nuclide_name = key
-            nuclide_density = value
-
-            # Get supported temperature
-            nearest_temperature = min(TEMPERATURES, key=lambda x: abs(x - temperature))
-
-            # Check if nuclide-temperature is available in the library
-            file_name = f"{nuclide_name}-{nearest_temperature}K.h5"
-            if not file_name in os.listdir(lib_dir):
-                print_error(
-                    f"Nuclide {nuclide_name} at temperature {nearest_temperature} K is not available in the library"
-                )
-
-            # Check if nuclide is already created
-            found = False
-            for nuclide in simulation.nuclides:
-                if (
-                    nuclide.name == nuclide_name
-                    and nearest_temperature == nuclide.temperature
-                ):
-                    found = True
-                    break
+        # Create lightweight composition objects. Library data and simulation
+        # registration are deferred to each object's compilation.
+        nearest_temperature = _get_supported_temperature(self.temperature)
+        self.nuclide_composition = {
+            Nuclide(name, nearest_temperature): density
+            for name, density in nuclide_composition.items()
+        }
+        self.element_composition = {
+            Element(name): density for name, density in element_composition.items()
+        }
+
+        # Numba representations of the compositions
+        self.nuclides = list(self.nuclide_composition)
+        self.elements = list(self.element_composition)
+        self.nuclide_densities = np.asarray(
+            list(self.nuclide_composition.values()), dtype=float
+        )
+        self.element_densities = np.asarray(
+            list(self.element_composition.values()), dtype=float
+        )
+
+    def _compile_into_simulation(self, simulation) -> bool:
+        """Resolve and register composition objects with the owning simulation."""
+        if not super()._compile_into_simulation(simulation):
+            return False
+
+        nuclide_composition = {}
+        element_composition = {}
+        self.fissionable = False
 
-            # Create the nuclide to objects if needed
-            if not found:
-                nuclide = Nuclide(nuclide_name, nearest_temperature)
+        # Replace locally created elements with canonical simulation objects.
+        for element, density in self.element_composition.items():
+            element = _get_or_create_element(element.name, simulation, element)
+            element._compile_into_simulation(simulation)
+            element_composition[element] = density
 
-            # Register the nuclide composition
-            self.nuclides.append(nuclide)
-            self.nuclide_densities[i] = nuclide_density
-            self.nuclide_composition[nuclide] = nuclide_density
+        # Replace locally created nuclides with canonical simulation objects.
+        for nuclide, density in self.nuclide_composition.items():
+            nuclide = _get_or_create_nuclide(
+                nuclide.name, nuclide.temperature, simulation, nuclide
+            )
+            nuclide._compile_into_simulation(simulation)
+            nuclide_composition[nuclide] = density
 
-            # Promote nuclide flags to material
             if nuclide.fissionable:
                 self.fissionable = True
 
+        self.nuclide_composition = nuclide_composition
+        self.element_composition = element_composition
+        self.nuclides = list(nuclide_composition)
+        self.elements = list(element_composition)
+        self.nuclide_densities = np.asarray(
+            list(nuclide_composition.values()), dtype=float
+        )
+        self.element_densities = np.asarray(
+            list(element_composition.values()), dtype=float
+        )
+
+        return True
+
     def __repr__(self):
         text = super().__repr__()
 
@@ -494,15 +476,15 @@ def __repr__(self):
         return text
 
 
-def set_nuclides_from_elements(material):
-    """Expand an elemental material composition into natural isotopes."""
+def set_nuclides_from_elements(material, simulation):
+    """Expand an elemental composition and register its natural isotopes."""
 
     material.nuclides = []
     material.nuclide_composition = {}
     nuclide_densities = []
 
     # Get supported temperature
-    nearest_temperature = min(TEMPERATURES, key=lambda x: abs(x - material.temperature))
+    nearest_temperature = _get_supported_temperature(material.temperature)
 
     for element, element_density in material.element_composition.items():
         # To make sure that the abundance is normalized
@@ -512,19 +494,10 @@ def set_nuclides_from_elements(material):
 
         # Loop over the nuclide composition
         for nuclide_name, abundance in ISOTOPIC_ABUNDANCE[element.name].items():
-            # Check if nuclide is already created
-            found = False
-            for nuclide in simulation.nuclides:
-                if (
-                    nuclide.name == nuclide_name
-                    and nearest_temperature == nuclide.temperature
-                ):
-                    found = True
-                    break
-
-            # Create the nuclide object if needed
-            if not found:
-                nuclide = Nuclide(nuclide_name, nearest_temperature)
+            nuclide = _get_or_create_nuclide(
+                nuclide_name, nearest_temperature, simulation
+            )
+            nuclide._compile_into_simulation(simulation)
 
             # Calculate nuclide density
             nuclide_density = element_density * abundance / norm
@@ -537,8 +510,8 @@ def set_nuclides_from_elements(material):
     material.nuclide_densities = np.array(nuclide_densities)
 
 
-def set_elements_from_nuclides(material):
-    """Collapse a nuclide composition into elemental atomic densities."""
+def set_elements_from_nuclides(material, simulation):
+    """Collapse a nuclide composition and register its elements."""
 
     material.elements = []
     material.element_composition = {}
@@ -555,16 +528,8 @@ def set_elements_from_nuclides(material):
 
     # Iterate over all named elements
     for i, element_name in enumerate(element_names):
-        # Check if element is already created
-        found = False
-        for element in simulation.elements:
-            if element.name == element_name:
-                found = True
-                break
-
-        # Create the element object if needed
-        if not found:
-            element = Element(element_name)
+        element = _get_or_create_element(element_name, simulation)
+        element._compile_into_simulation(simulation)
 
         material.elements.append(element)
 
@@ -584,6 +549,25 @@ def set_elements_from_nuclides(material):
     material.element_densities = element_densities
 
 
+def _get_supported_temperature(temperature):
+    return min(TEMPERATURES, key=lambda value: abs(value - temperature))
+
+
+def _get_or_create_element(element_name, simulation, candidate=None):
+    for element in simulation.elements:
+        if element.name == element_name:
+            return element
+    return candidate or Element(element_name)
+
+
+def _get_or_create_nuclide(nuclide_name, temperature, simulation, candidate=None):
+    for nuclide in simulation.nuclides:
+        if nuclide.name == nuclide_name and nuclide.temperature == temperature:
+            return nuclide
+
+    return candidate or Nuclide(nuclide_name, temperature)
+
+
 def update_fissionable_from_nuclides(material):
     """Update a material's fissionable flag from its constituent nuclides."""
 
diff --git a/mcdc/object_/neutron_reaction.py b/mcdc/object_/neutron_reaction.py
index 2fe64fdd2..1fdb672d9 100644
--- a/mcdc/object_/neutron_reaction.py
+++ b/mcdc/object_/neutron_reaction.py
@@ -54,6 +54,7 @@ class NeutronReactionBase(MCDCPolymorphic):
     q_value: float64
 
     def __init__(self, MT, xs, xs_offset, reference_frame, q_value):
+        super().__init__()
         self.MT = MT
         self.xs = xs
         self.xs_offset_ = xs_offset
@@ -99,12 +100,20 @@ def __init__(self, MT, xs, xs_offset, reference_frame, mu):
         self.mu_table = mu
 
     @classmethod
-    def from_h5_group(cls, h5_group):
+    def from_h5_group(cls, h5_group, simulation):
         """Build an elastic-scattering reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame, _ = set_basic_properties(h5_group)
-        _, mu = set_angular_distribution(h5_group["angular_cosine_distribution"])
+        _, mu = set_angular_distribution(
+            h5_group["angular_cosine_distribution"], simulation
+        )
         return cls(MT, xs, xs_offset, reference_frame, mu)
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        self.mu_table._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Scattering cosine: {distribution.decode_type(self.mu_table.type)} [ID: {self.mu_table.ID}]\n"
@@ -127,7 +136,7 @@ def __init__(self, MT, xs, xs_offset, reference_frame, q_value):
         super().__init__(MT, xs, xs_offset, reference_frame, q_value)
 
     @classmethod
-    def from_h5_group(cls, h5_group):
+    def from_h5_group(cls, h5_group, simulation):
         """Build a capture reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame, q_value = set_basic_properties(h5_group)
         return cls(MT, xs, xs_offset, reference_frame, q_value)
@@ -182,13 +191,13 @@ def __init__(
         self.energy_spectra = energy_spectra
 
     @classmethod
-    def from_h5_group(cls, h5_group):
+    def from_h5_group(cls, h5_group, simulation):
         """Build an inelastic-scattering reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame, q_value = set_basic_properties(h5_group)
         multiplicity = int(h5_group["multiplicity"][()])
 
         angle_type, mu = set_angular_distribution(
-            h5_group["angular_cosine_distribution"]
+            h5_group["angular_cosine_distribution"], simulation
         )
 
         # Energy spectra
@@ -215,6 +224,14 @@ def from_h5_group(cls, h5_group):
             energy_spectra,
         )
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        self.mu._compile_into_simulation(simulation)
+        for spectrum in self.energy_spectra:
+            spectrum._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self):
         text = super().__repr__()
         if self.angle_type == ANGLE_ISOTROPIC:
@@ -263,13 +280,13 @@ def __init__(
         self.spectrum = spectrum
 
     @classmethod
-    def from_h5_group(cls, h5_group):
+    def from_h5_group(cls, h5_group, simulation):
         """Build a fission reaction from a library HDF5 group."""
         MT, xs, xs_offset, reference_frame, q_value = set_basic_properties(h5_group)
 
         # Prompt angular distribution
         angle_type, mu = set_angular_distribution(
-            h5_group["angular_cosine_distribution"]
+            h5_group["angular_cosine_distribution"], simulation
         )
 
         # Prompt spectrum
@@ -282,6 +299,13 @@ def from_h5_group(cls, h5_group):
             MT, xs, xs_offset, reference_frame, q_value, angle_type, mu, spectrum
         )
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        if not super()._compile_into_simulation(simulation):
+            return False
+        self.mu._compile_into_simulation(simulation)
+        self.spectrum._compile_into_simulation(simulation)
+        return True
+
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Prompt neutron\n"
@@ -316,7 +340,7 @@ def set_basic_properties(h5_group):
     return MT, xs, xs_offset, reference_frame, q_value
 
 
-def set_angular_distribution(h5_group):
+def set_angular_distribution(h5_group, simulation):
     """Create the packed angle type and distribution from an HDF5 group."""
 
     mu_type = h5_group.attrs["type"]
diff --git a/mcdc/object_/nuclide.py b/mcdc/object_/nuclide.py
index 91d83814c..603c415aa 100644
--- a/mcdc/object_/nuclide.py
+++ b/mcdc/object_/nuclide.py
@@ -26,7 +26,7 @@
 
 
 class Nuclide(MCDCObject):
-    """Temperature-specific nuclide data from the MC/DC HDF5 library.
+    """Temperature-specific nuclide definition for the MC/DC HDF5 library.
 
     Parameters
     ----------
@@ -37,17 +37,15 @@ class Nuclide(MCDCObject):
 
     Notes
     -----
-    Construction loads basic nuclide properties. Neutron cross sections,
-    reactions, multiplicities, and delayed-neutron data are loaded later by
-    :meth:`set_neutron_data`.
+    Construction records the nuclide identity without accessing the data
+    library. Basic properties are loaded when the nuclide is compiled into a
+    simulation. Neutron cross sections, reactions, multiplicities, and
+    delayed-neutron data are loaded later by :meth:`set_neutron_data`.
     """
 
     # MC/DC framework metadata
     label = "nuclide"
 
-    # Annotations for Numba mode
-    label: str = "nuclide"
-    #
     name: str
     temperature: float
     atomic_number: int
@@ -81,16 +79,31 @@ def __init__(self, nuclide_name, temperature):
         self.name = nuclide_name
         self.temperature = temperature
 
-        # Basic properties
+    def _compile_into_simulation(self, simulation) -> bool:
+        """Load basic properties and register with the owning simulation."""
+        if self.compile_ID == simulation.compile_ID:
+            return False
+
         dir_name = os.getenv("MCDC_LIB")
-        file_name = f"{nuclide_name}-{temperature}K.h5"
-        file = h5py.File(f"{dir_name}/{file_name}", "r")
-        self.atomic_number = int(file["atomic_number"][()])
-        self.mass_number = int(file["mass_number"][()])
-        self.atomic_weight_ratio = file["atomic_weight_ratio"][()]
-        self.fissionable = bool(file["fissionable"][()])
-        self.excitation_level = int(file["excitation_level"][()])
-        file.close()
+        if dir_name is None:
+            print_error("Environment variable MCDC_LIB is not set")
+
+        file_name = f"{self.name}-{self.temperature}K.h5"
+        file_path = os.path.join(dir_name, file_name)
+        if not os.path.isfile(file_path):
+            print_error(
+                f"Nuclide {self.name} at temperature {self.temperature} K "
+                "is not available in the library"
+            )
+
+        with h5py.File(file_path, "r") as file:
+            self.atomic_number = int(file["atomic_number"][()])
+            self.mass_number = int(file["mass_number"][()])
+            self.atomic_weight_ratio = file["atomic_weight_ratio"][()]
+            self.fissionable = bool(file["fissionable"][()])
+            self.excitation_level = int(file["excitation_level"][()])
+
+        return super()._compile_into_simulation(simulation)
 
     def set_neutron_data(self, simulation):
         """Load and attach neutron physics data from ``MCDC_LIB``.
@@ -238,6 +251,15 @@ def set_neutron_data(self, simulation):
 
         file.close()
 
+        # Register data loaded after model compilation.
+        for reaction_container in rx_containers:
+            for reaction in reaction_container:
+                reaction._compile_into_simulation(simulation)
+        self.neutron_fission_prompt_multiplicity._compile_into_simulation(simulation)
+        self.neutron_fission_delayed_multiplicity._compile_into_simulation(simulation)
+        for spectrum in self.neutron_fission_delayed_spectra:
+            spectrum._compile_into_simulation(simulation)
+
     def __repr__(self):
         text = "\n"
         text += f"Nuclide\n"

From 8bf59b4246d6f27ed71faa0136127229825e8a42 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 16:00:03 +0700
Subject: [PATCH 049/202] update lattice

---
 mcdc/object_/universe.py           | 23 ++++++++++++++++----
 test/unit/geometry/test_lattice.py | 35 ++++++++++++++++++++++++++++++
 2 files changed, 54 insertions(+), 4 deletions(-)
 create mode 100644 test/unit/geometry/test_lattice.py

diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index 14a7cb4bf..1a1ac359d 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -212,15 +212,30 @@ def __init__(
             self.dz = z[1]
             self.Nz = z[2]
 
+        self._set_universe_IDs()
+
+    def _compile_into_simulation(self, simulation) -> bool:
+        """Compile contained universes and rebuild their lattice IDs."""
+        if not super()._compile_into_simulation(simulation):
+            return False
+
+        for universe in flatten(self.universes):
+            universe._compile_into_simulation(simulation)
+
+        self._set_universe_IDs()
+        return True
+
+    def _set_universe_IDs(self) -> None:
+        """Build the packed universe-ID array from the universe layout."""
         # Set universe IDs
         get_ID = np.vectorize(lambda obj: obj.ID)
-        universe_IDs = get_ID(universes)
+        universe_IDs = get_ID(self.universes)
         ax_expand = []
-        if x is None:
+        if self.dx == 2 * INF:
             ax_expand.append(2)
-        if y is None:
+        if self.dy == 2 * INF:
             ax_expand.append(1)
-        if z is None:
+        if self.dz == 2 * INF:
             ax_expand.append(0)
         for ax in ax_expand:
             universe_IDs = np.expand_dims(universe_IDs, axis=ax)
diff --git a/test/unit/geometry/test_lattice.py b/test/unit/geometry/test_lattice.py
new file mode 100644
index 000000000..d2331153e
--- /dev/null
+++ b/test/unit/geometry/test_lattice.py
@@ -0,0 +1,35 @@
+import numpy as np
+
+import mcdc
+
+
+def test_lattice_compiles_contained_universes():
+    lower_left = mcdc.Universe(name="Lower left")
+    lower_right = mcdc.Universe(name="Lower right")
+    upper_left = mcdc.Universe(name="Upper left")
+    upper_right = mcdc.Universe(name="Upper right")
+
+    lattice = mcdc.Lattice(
+        x=(-1.0, 1.0, 2),
+        y=(-1.0, 1.0, 2),
+        universes=[
+            [lower_left, lower_right],
+            [upper_left, upper_right],
+        ],
+    )
+
+    simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell(fill=lattice)])
+    simulation.compile()
+
+    assert simulation.universes == [
+        simulation.root_universe,
+        lower_left,
+        lower_right,
+        upper_left,
+        upper_right,
+    ]
+    np.testing.assert_array_equal(
+        lattice.universe_IDs,
+        np.array([[[3], [1]], [[4], [2]]]),
+    )

From de337cc4c31757d12057464877aa100a414e4881 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 16:15:25 +0700
Subject: [PATCH 050/202] update unit tests

---
 mcdc/code_factory/python_objects_compiler.py  |  4 ++
 test/unit/conftest.py                         | 30 +++++++++
 test/unit/distributions/test_evaporation.py   | 11 +++-
 test/unit/distributions/test_maxwellian.py    | 12 +++-
 test/unit/distributions/test_multi_table.py   | 37 ++++++-----
 .../distributions/test_nbody_correlated.py    | 47 ++++----------
 .../test_tabulated_distribution.py            | 23 +++----
 test/unit/geometry/surface/conftest.py        | 17 ++---
 test/unit/geometry/surface/test_torus.py      | 12 ++--
 test/unit/tally/conftest.py                   | 25 ++++---
 .../tally/test_cell_filter_interior_plane.py  | 42 ++++++++----
 test/unit/tally/test_cell_tally.py            | 65 +++++++++++++------
 test/unit/tally/test_collision_tally.py       |  3 +
 .../tally/test_nonbounded_surface_tally.py    | 23 ++++---
 test/unit/tally/test_tally_factory.py         | 14 ++--
 test/unit/tally/test_tracklength_tally.py     |  6 ++
 test/unit/technique/test_weight_windows.py    | 33 ++++++----
 17 files changed, 248 insertions(+), 156 deletions(-)

diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index 5e0985d32..97367e620 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -48,6 +48,10 @@ def compile_simulation(simulation: Simulation):
     for tally in tallies:
         tally._compile_into_simulation(simulation)
 
+    # Compile model objects owned by transport techniques.
+    if simulation.weight_windows.active:
+        simulation.weight_windows.mesh._compile_into_simulation(simulation)
+
     # Apply settings as needed
     settings = simulation.settings
     if simulation.settings.neutron_eigenvalue_mode:
diff --git a/test/unit/conftest.py b/test/unit/conftest.py
index 339f2e7f9..30a7ac01f 100644
--- a/test/unit/conftest.py
+++ b/test/unit/conftest.py
@@ -5,6 +5,36 @@
 import pytest
 
 
+@pytest.fixture
+def prepare_simulation():
+    """Compile and pack an explicit simulation for kernel-level unit tests."""
+    from mcdc.main import prepare
+    from mcdc.object_.simulation import Simulation
+
+    def _prepare(
+        *,
+        cells=(),
+        tallies=(),
+        sources=(),
+        objects=(),
+        configure=None,
+    ):
+        simulation = Simulation()
+        simulation.set_model(cells)
+        simulation.set_tallies(tallies)
+        simulation.set_sources(sources)
+        if configure is not None:
+            configure(simulation)
+
+        simulation.compile()
+        for object_ in objects:
+            object_._compile_into_simulation(simulation)
+
+        return prepare(simulation)
+
+    return _prepare
+
+
 def pytest_addoption(parser):
     parser.addoption(
         "--mode",
diff --git a/test/unit/distributions/test_evaporation.py b/test/unit/distributions/test_evaporation.py
index f3b71c102..8b6f65084 100644
--- a/test/unit/distributions/test_evaporation.py
+++ b/test/unit/distributions/test_evaporation.py
@@ -4,6 +4,7 @@
 import mcdc.numba_types as type_
 import mcdc.transport.distribution as dist
 
+from mcdc.constant import DATA_TABLE
 from .test_data import make_test_table_data_constant
 
 
@@ -17,9 +18,17 @@ def test_evaporation_sample(mock_rng_sequence, make_distribution_record):
     )
     data = np.asarray(data, dtype=np.float64)
 
-    simulation_dtype = np.dtype([("table_data", type_.table_data, (1,))])
+    simulation_dtype = np.dtype(
+        [
+            ("data", type_.data, (1,)),
+            ("polynomial_data", type_.polynomial_data, (1,)),
+            ("table_data", type_.table_data, (1,)),
+        ]
+    )
     simulation_container = np.zeros(1, dtype=simulation_dtype)
     simulation = simulation_container[0]
+    simulation["data"][0]["sub_type"] = DATA_TABLE
+    simulation["data"][0]["sub_ID"] = 0
     simulation["table_data"][0] = table
 
     xi1, xi2 = 0.1, 0.2
diff --git a/test/unit/distributions/test_maxwellian.py b/test/unit/distributions/test_maxwellian.py
index 6d51f0c3d..78a05ad88 100644
--- a/test/unit/distributions/test_maxwellian.py
+++ b/test/unit/distributions/test_maxwellian.py
@@ -3,7 +3,7 @@
 
 import mcdc.numba_types as type_
 import mcdc.transport.distribution as dist
-from mcdc.constant import PI
+from mcdc.constant import DATA_TABLE, PI
 
 from .test_data import make_test_table_data_constant
 
@@ -18,9 +18,17 @@ def test_maxwellian_sample(mock_rng_sequence, make_distribution_record):
     )
     data = np.asarray(data, dtype=np.float64)
 
-    simulation_dtype = np.dtype([("table_data", type_.table_data, (1,))])
+    simulation_dtype = np.dtype(
+        [
+            ("data", type_.data, (1,)),
+            ("polynomial_data", type_.polynomial_data, (1,)),
+            ("table_data", type_.table_data, (1,)),
+        ]
+    )
     simulation_container = np.zeros(1, dtype=simulation_dtype)
     simulation = simulation_container[0]
+    simulation["data"][0]["sub_type"] = DATA_TABLE
+    simulation["data"][0]["sub_ID"] = 0
     simulation["table_data"][0] = table
 
     xi1, xi2, xi3 = 0.9, 0.9, 0.0
diff --git a/test/unit/distributions/test_multi_table.py b/test/unit/distributions/test_multi_table.py
index 6c335da26..2f63bf794 100644
--- a/test/unit/distributions/test_multi_table.py
+++ b/test/unit/distributions/test_multi_table.py
@@ -1,32 +1,38 @@
-import math
 import numpy as np
 
-import mcdc.numba_types as type_
 import mcdc.transport.distribution as dist
+from mcdc.object_.distribution import DistributionMultiTable
 
-from .test_data import make_test_multi_table_data
 
-
-def test_multi_table_distribution_sample(mock_rng_sequence, make_distribution_record):
-    """
+def test_multi_table_distribution_sample(mock_rng_sequence, prepare_simulation):
     # MCNP Theory & User Manual §2.4.3.5.4.4 (Law 4: Tabular Distribution)
-    multi_table_dict, data = make_test_multi_table_data()
-    multi_table = make_distribution_record(
-        type_.multi_table_distribution, multi_table_dict
+    distribution = DistributionMultiTable(
+        grid=[1.0, 3.0],
+        offset=[0, 3],
+        value=[10.0, 20.0, 30.0, 100.0, 200.0, 300.0],
+        cdf=[0.0, 0.5, 1.0, 0.0, 0.6, 1.0],
     )
-    data = np.asarray(data, dtype=np.float64)
+    simulation_container, data = prepare_simulation(objects=[distribution])
+    simulation = simulation_container[0]
+    multi_table = simulation["multi_table_distributions"][distribution.sub_ID]
+
     # For E_in = 2.0 on the grid [1, 3], Eq. (2.62) gives r = 0.5.
     # xi_1 = 0.3 < r, so Eq. (2.64) selects l = i + 1, i.e. the second table.
     xi1, xi2 = 0.3, 0.2
     mock_rng = mock_rng_sequence(xi1, xi2)
 
-    sampled_E = dist._sample_multi_table(2.0, mock_rng, multi_table, data, scale=True)
+    sampled_E = dist._sample_multi_table(
+        2.0,
+        mock_rng,
+        multi_table,
+        simulation,
+        data,
+        scale=True,
+    )
 
     # In the selected table, xi_2 = 0.2 falls in the first continuous bin.
-    # Eq. (2.65) gives E' = E_l,k + (xi_2 - c_l,k) / p_l,k = 100 + 0.2 / 0.01 = 120.
-    # The test data use constant p within the bin, so the linear-linear form in
-    # Eq. (2.66) reduces to the same result.
-    E_prime = 100.0 + (xi2 - 0.0) / 0.01
+    # The CDF rises from 0.0 to 0.6 over [100, 200], giving p = 0.006.
+    E_prime = 100.0 + (xi2 - 0.0) / 0.006
     # Eq. (2.67) and Eq. (2.68) give the scaled bounds:
     #   E_1 = 10 + 0.5 * (100 - 10) = 55
     #   E_K = 30 + 0.5 * (300 - 30) = 165
@@ -36,4 +42,3 @@ def test_multi_table_distribution_sample(mock_rng_sequence, make_distribution_re
     expected_E = 55.0 + (E_prime - 100.0) * (165.0 - 55.0) / (300.0 - 100.0)
 
     np.testing.assert_allclose(sampled_E, expected_E, rtol=0.0, atol=1e-12)
-    """
diff --git a/test/unit/distributions/test_nbody_correlated.py b/test/unit/distributions/test_nbody_correlated.py
index 65718bf13..b3ae02c39 100644
--- a/test/unit/distributions/test_nbody_correlated.py
+++ b/test/unit/distributions/test_nbody_correlated.py
@@ -1,39 +1,18 @@
-import math
 import numpy as np
 
-import mcdc.numba_types as type_
 import mcdc.transport.distribution as dist
-from mcdc.constant import DISTRIBUTION_N_BODY
+from mcdc.object_.distribution import DistributionNBody
 
-from .test_data import make_test_tabulated_data
 
-
-def test_nbody_sample_correlated(mock_rng_sequence, make_distribution_record):
-    """
+def test_nbody_sample_correlated(mock_rng_sequence, prepare_simulation):
     # MCNP Theory & User Manual §2.4.3.5.4.13 (Law 66: N-body Phase Space Distribution)
-    table_dict, data = make_test_tabulated_data([2.0, 4.0, 6.0], [0.0, 0.4, 1.0])
-    nbody = make_distribution_record(type_.nbody_distribution, table_dict)
-    distribution = make_distribution_record(
-        type_.distribution, {"child_type": DISTRIBUTION_N_BODY, "child_ID": 0}
-    )
-    data = np.asarray(data, dtype=np.float64)
-
-    # Numba compiles all correlated-branch field accesses, so this container needs
-    # the three correlated distribution arrays even though this test uses N-body only.
-    simulation_dtype = np.dtype(
-        [
-            ("kalbach_mann_distributions", type_.kalbach_mann_distribution, (1,)),
-            (
-                "tabulated_energy_angle_distributions",
-                type_.tabulated_energy_angle_distribution,
-                (1,),
-            ),
-            ("nbody_distributions", type_.nbody_distribution, (1,)),
-        ]
+    distribution = DistributionNBody(
+        values=[2.0, 4.0, 6.0],
+        probabilities=[1.0, 1.0, 1.0],
     )
-    simulation_container = np.zeros(1, dtype=simulation_dtype)
+    simulation_container, data = prepare_simulation(objects=[distribution])
     simulation = simulation_container[0]
-    simulation["nbody_distributions"][0] = nbody
+    distribution_base = simulation["distributions"][distribution.ID]
 
     # First value samples energy, second value samples isotropic cosine.
     xi1, xi2 = 0.2, 0.75
@@ -41,7 +20,7 @@ def test_nbody_sample_correlated(mock_rng_sequence, make_distribution_record):
 
     sampled_E, sampled_mu = dist.sample_correlated_distribution(
         2.0,
-        distribution,
+        distribution_base,
         mock_rng,
         simulation,
         data,
@@ -51,12 +30,12 @@ def test_nbody_sample_correlated(mock_rng_sequence, make_distribution_record):
     # samples the cosine isotropically. This test is therefore checking the current
     # reduced implementation, not reconstructing the full Law 66 rejection sampler
     # from Eq. (2.103) through Eq. (2.106).
-    # For the tabulated-energy part, xi_1 = 0.2 gives linear interpolation in the first
-    # bin. For the angular part, MCNP Eq. (2.107) gives mu = 2 * xi_10 - 1 for
-    # isotropic center-of-mass sampling.
-    expected_E = 2.0 + (xi1 - 0.0) * (4.0 - 2.0) / (0.4 - 0.0)
+    # The constant PDF is normalized to 0.25 over [2, 6], so inverse-CDF sampling
+    # in the first bin gives E_out = 2 + xi_1 / 0.25.
+    # For the angular part, MCNP Eq. (2.107) gives mu = 2 * xi_10 - 1 for isotropic
+    # center-of-mass sampling.
+    expected_E = 2.0 + xi1 / 0.25
     expected_mu = 2.0 * xi2 - 1.0
 
     np.testing.assert_allclose(sampled_E, expected_E, rtol=0.0, atol=1e-12)
     np.testing.assert_allclose(sampled_mu, expected_mu, rtol=0.0, atol=1e-12)
-    """
diff --git a/test/unit/distributions/test_tabulated_distribution.py b/test/unit/distributions/test_tabulated_distribution.py
index 4733ee5ac..7fab4df59 100644
--- a/test/unit/distributions/test_tabulated_distribution.py
+++ b/test/unit/distributions/test_tabulated_distribution.py
@@ -1,26 +1,27 @@
-import math
 import numpy as np
 
-import mcdc.numba_types as type_
 import mcdc.transport.distribution as dist
+from mcdc.object_.distribution import DistributionTabulated
 
-from .test_data import make_test_tabulated_data
 
-
-def test_tabulated_distribution_sample(mock_rng_sequence, make_distribution_record):
-    """
+def test_tabulated_distribution_sample(mock_rng_sequence, prepare_simulation):
     # MCNP Theory & User Manual §2.4.3.5.4.4 (Law 4: Tabular Distribution)
-    table_dict, data = make_test_tabulated_data([1.0, 3.0, 7.0], [0.0, 0.4, 1.0])
-    table = make_distribution_record(type_.tabulated_distribution, table_dict)
-    data = np.asarray(data, dtype=np.float64)
+    distribution = DistributionTabulated(
+        value=[1.0, 3.0, 7.0],
+        cdf=[0.0, 0.4, 1.0],
+    )
+    simulation_container, data = prepare_simulation(objects=[distribution])
+    simulation = simulation_container[0]
+    table = simulation["tabulated_distributions"][distribution.sub_ID]
+
     xi1 = 0.2
     mock_rng = mock_rng_sequence(xi1)
 
-    sampled_E = dist.sample_tabulated(table, mock_rng, data)
+    sampled_E = dist.sample_tabulated(table, mock_rng, simulation, data)
+
     # This is the single-table inverse-CDF interpolation used by the tabulated sampler:
     # xi_1 = 0.2 lies in the first bin, so linear interpolation between
     # (c_0, E_0) = (0.0, 1.0) and (c_1, E_1) = (0.4, 3.0) gives the expected value.
     expected_E = 1.0 + (xi1 - 0.0) * (3.0 - 1.0) / (0.4 - 0.0)
 
     np.testing.assert_allclose(sampled_E, expected_E, rtol=0.0, atol=1e-12)
-    """
diff --git a/test/unit/geometry/surface/conftest.py b/test/unit/geometry/surface/conftest.py
index 97263e989..3a03147f3 100644
--- a/test/unit/geometry/surface/conftest.py
+++ b/test/unit/geometry/surface/conftest.py
@@ -1,21 +1,12 @@
 import pytest
 
 
-@pytest.fixture(autouse=True)
-def reset_simulation():
-    from mcdc.object_.simulation import simulation
-
-    simulation.__init__()
-    yield
-    simulation.__init__()
-
-
 @pytest.fixture
-def compile_surfaces():
+def compile_surfaces(prepare_simulation):
     def _compile(static_surface_obj, moving_surface_obj):
-        from mcdc.main import preparation
-
-        structure_container, data = preparation()
+        structure_container, data = prepare_simulation(
+            objects=[static_surface_obj, moving_surface_obj]
+        )
         structure = structure_container[0]
         static_surface = structure["surfaces"][static_surface_obj.ID]
         moving_surface = structure["surfaces"][moving_surface_obj.ID]
diff --git a/test/unit/geometry/surface/test_torus.py b/test/unit/geometry/surface/test_torus.py
index 09d9b07ad..bf6541db3 100644
--- a/test/unit/geometry/surface/test_torus.py
+++ b/test/unit/geometry/surface/test_torus.py
@@ -26,7 +26,7 @@
 
 
 @pytest.fixture(autouse=True)
-def setup_geometry_case():
+def setup_geometry_case(prepare_simulation):
     global axis_aligned_surface, reference_surface, oblique_surface
     global data, particle_container, particle
 
@@ -47,9 +47,13 @@ def setup_geometry_case():
         r=r,
     )
 
-    from mcdc.main import preparation
-
-    structure_container, data = preparation()
+    structure_container, data = prepare_simulation(
+        objects=[
+            axis_aligned_surface_obj,
+            reference_surface_obj,
+            oblique_surface_obj,
+        ]
+    )
     structure = structure_container[0]
     axis_aligned_surface = structure["surfaces"][axis_aligned_surface_obj.ID]
     reference_surface = structure["surfaces"][reference_surface_obj.ID]
diff --git a/test/unit/tally/conftest.py b/test/unit/tally/conftest.py
index cb276f87d..3d0e2e67b 100644
--- a/test/unit/tally/conftest.py
+++ b/test/unit/tally/conftest.py
@@ -4,16 +4,6 @@
 import mcdc
 import mcdc.numba_types as type_
 from mcdc.constant import PARTICLE_NEUTRON
-from mcdc.main import preparation
-from mcdc.object_.simulation import simulation
-
-
-@pytest.fixture(autouse=True)
-def reset_simulation():
-    # Keep simulation state isolated per test.
-    simulation.__init__()
-    yield
-    simulation.__init__()
 
 
 @pytest.fixture
@@ -54,7 +44,11 @@ def slab_plane_x(material_mg):
     s_right = mcdc.Surface.PlaneX(x=1.0, boundary_condition="vacuum")
     c_left = mcdc.Cell(region=+s_left & -s_mid, fill=material_mg)
     c_right = mcdc.Cell(region=+s_mid & -s_right, fill=material_mg)
+    simulation = mcdc.Simulation()
+    simulation.set_model([c_left, c_right])
+    simulation.compile()
     return {
+        "simulation": simulation,
         "s_left": s_left,
         "s_mid": s_mid,
         "s_right": s_right,
@@ -64,18 +58,21 @@ def slab_plane_x(material_mg):
 
 
 @pytest.fixture
-def surface_crossing_tally_context(slab_plane_x):
+def surface_crossing_tally_context(slab_plane_x, prepare_simulation):
     s_mid = slab_plane_x["s_mid"]
 
     unbounded_tally_obj = mcdc.Tally(surface=s_mid, scores=["current-net"])
 
     # Build compiled structures.
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[slab_plane_x["c_left"], slab_plane_x["c_right"]],
+        tallies=[unbounded_tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
 
     # Compiled tally handles.
     unbounded_tally = mcdc_struct["surface_crossing_tallies"][
-        unbounded_tally_obj.child_ID
+        unbounded_tally_obj.sub_ID
     ]
 
     # Particle for direct crossing-based tally-kernel testing.
@@ -106,7 +103,7 @@ def surface_crossing_tally_context(slab_plane_x):
 @pytest.fixture
 def bin_value():
     def _value(surface_crossing_tally, mcdc_struct, data):
-        tally_base = mcdc_struct["tallies"][surface_crossing_tally["parent_ID"]]
+        tally_base = mcdc_struct["tallies"][surface_crossing_tally["base_ID"]]
         return data[tally_base["bin_offset"]]
 
     return _value
diff --git a/test/unit/tally/test_cell_filter_interior_plane.py b/test/unit/tally/test_cell_filter_interior_plane.py
index b2efded7f..5bff26d1a 100644
--- a/test/unit/tally/test_cell_filter_interior_plane.py
+++ b/test/unit/tally/test_cell_filter_interior_plane.py
@@ -1,32 +1,37 @@
 import numpy as np
 
 import mcdc
-from mcdc.main import preparation
 from mcdc.transport.simulation import surface_crossing
 
 
 def _bin_value_score(tally, mcdc_struct, data, score_idx):
-    tally_base = mcdc_struct["tallies"][tally["parent_ID"]]
+    tally_base = mcdc_struct["tallies"][tally["base_ID"]]
     return data[tally_base["bin_offset"] + score_idx]
 
 
 def test_cell_filter_ignores_redundant_interior_surface_crossing(
-    material_mg, crossing_particle
+    material_mg, crossing_particle, prepare_simulation
 ):
     s3 = mcdc.Surface.PlaneX(x=3.0)
     s5 = mcdc.Surface.PlaneX(x=5.0)
 
     # This region is equivalent to x < 5, but the expression includes a surface at s3.
     c = mcdc.Cell(region=(-s5) | (-s3), fill=material_mg)
-    mcdc.Cell(region=+s5, fill=material_mg)
+    outside = mcdc.Cell(region=+s5, fill=material_mg)
+    simulation = mcdc.Simulation()
+    simulation.set_model([c, outside])
+    simulation.compile()
     tally_obj = mcdc.Tally(
         cell=c,
         scores=["current-net", "current-in", "current-out"],
     )
 
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[c, outside],
+        tallies=[tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
-    tally = mcdc_struct["surface_crossing_tallies"][tally_obj.child_ID]
+    tally = mcdc_struct["surface_crossing_tallies"][tally_obj.sub_ID]
 
     # The particle crosses s3, but it remains inside c before and after crossing
     particle_container = crossing_particle(s3.ID, x=3.0, ux=0.5, cell_ID=c.ID)
@@ -53,21 +58,30 @@ def _build_cube_with_interior_plane(material_mg):
     outside_region = -x_min | +x_max | -y_min | +y_max | -z_min | +z_max
     outside = mcdc.Cell(region=outside_region, fill=material_mg)
 
+    simulation = mcdc.Simulation()
+    simulation.set_model([cube, outside])
+    simulation.compile()
+
     return {"cube": cube, "outside": outside, "x_min": x_min, "x_mid": x_mid}
 
 
-def _cube_current_tally(geom):
+def _cube_current_tally(geom, prepare_simulation):
     tally_obj = mcdc.Tally(
         cell=geom["cube"],
         scores=["current-net", "current-in", "current-out"],
     )
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[geom["cube"], geom["outside"]],
+        tallies=[tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
-    tally = mcdc_struct["surface_crossing_tallies"][tally_obj.child_ID]
+    tally = mcdc_struct["surface_crossing_tallies"][tally_obj.sub_ID]
     return tally, mcdc_struct, data
 
 
-def test_cell_filter_ignores_interior_plane_crossing(material_mg, crossing_particle):
+def test_cell_filter_ignores_interior_plane_crossing(
+    material_mg, crossing_particle, prepare_simulation
+):
     """
     A particle crossing the cube's interior plane while remaining inside the
     cube does not cross the cell boundary, so current-net/in/out must all be 0.
@@ -78,7 +92,7 @@ def test_cell_filter_ignores_interior_plane_crossing(material_mg, crossing_parti
     (net = +w, in = +w, out = +w instead of 0).
     """
     geom = _build_cube_with_interior_plane(material_mg)
-    tally, mcdc_struct, data = _cube_current_tally(geom)
+    tally, mcdc_struct, data = _cube_current_tally(geom, prepare_simulation)
 
     # The particle crosses the cube's interior plane but remains in the cube.
     particle_container = crossing_particle(
@@ -94,7 +108,9 @@ def test_cell_filter_ignores_interior_plane_crossing(material_mg, crossing_parti
     assert np.isclose(_bin_value_score(tally, mcdc_struct, data, 2), 0.0)
 
 
-def test_cell_filter_scores_real_face_entry(material_mg, crossing_particle):
+def test_cell_filter_scores_real_face_entry(
+    material_mg, crossing_particle, prepare_simulation
+):
     """
     Contrast case on the same geometry: entering the cube through a real outer
     face (x_min) from the outside cell is a genuine boundary crossing, so it
@@ -102,7 +118,7 @@ def test_cell_filter_scores_real_face_entry(material_mg, crossing_particle):
     convention).
     """
     geom = _build_cube_with_interior_plane(material_mg)
-    tally, mcdc_struct, data = _cube_current_tally(geom)
+    tally, mcdc_struct, data = _cube_current_tally(geom, prepare_simulation)
 
     # Entering through a real outer face should score incoming current.
     particle_container = crossing_particle(
diff --git a/test/unit/tally/test_cell_tally.py b/test/unit/tally/test_cell_tally.py
index ae6a78840..40b2a83ad 100644
--- a/test/unit/tally/test_cell_tally.py
+++ b/test/unit/tally/test_cell_tally.py
@@ -2,27 +2,29 @@
 
 import mcdc
 
-from mcdc.main import preparation
 from mcdc.transport.simulation import surface_crossing
 
 
 def _bin_value(surface_crossing_tally, mcdc_struct, data):
-    tally_base = mcdc_struct["tallies"][surface_crossing_tally["parent_ID"]]
+    tally_base = mcdc_struct["tallies"][surface_crossing_tally["base_ID"]]
     return data[tally_base["bin_offset"]]
 
 
 def _bin_value_score(surface_crossing_tally, mcdc_struct, data, score_idx):
-    tally_base = mcdc_struct["tallies"][surface_crossing_tally["parent_ID"]]
+    tally_base = mcdc_struct["tallies"][surface_crossing_tally["base_ID"]]
     return data[tally_base["bin_offset"] + score_idx]
 
 
 def test_surface_cell_filter_current_net_is_incoming_negative_outgoing_positive(
-    slab_plane_x, crossing_particle
+    slab_plane_x, crossing_particle, prepare_simulation
 ):
     current_tally_obj = mcdc.Tally(cell=slab_plane_x["c_right"], scores=["current-net"])
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[slab_plane_x["c_left"], slab_plane_x["c_right"]],
+        tallies=[current_tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
-    current_tally = mcdc_struct["surface_crossing_tallies"][current_tally_obj.child_ID]
+    current_tally = mcdc_struct["surface_crossing_tallies"][current_tally_obj.sub_ID]
 
     # Left -> right across the shared interior surface: incoming to c_right (-)
     particle_container = crossing_particle(
@@ -46,15 +48,18 @@ def test_surface_cell_filter_current_net_is_incoming_negative_outgoing_positive(
 
 
 def test_surface_cell_filter_current_records_in_and_out_separately(
-    slab_plane_x, crossing_particle
+    slab_plane_x, crossing_particle, prepare_simulation
 ):
     current_tally_obj = mcdc.Tally(
         cell=slab_plane_x["c_right"],
         scores=["current-net", "current-in", "current-out"],
     )
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[slab_plane_x["c_left"], slab_plane_x["c_right"]],
+        tallies=[current_tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
-    current_tally = mcdc_struct["surface_crossing_tallies"][current_tally_obj.child_ID]
+    current_tally = mcdc_struct["surface_crossing_tallies"][current_tally_obj.sub_ID]
 
     # One incoming and one outgoing crossing.
     particle_container = crossing_particle(
@@ -80,15 +85,18 @@ def test_surface_cell_filter_current_records_in_and_out_separately(
 
 
 def test_surface_cell_filter_current_counts_outgoing_to_vacuum(
-    slab_plane_x, crossing_particle
+    slab_plane_x, crossing_particle, prepare_simulation
 ):
     current_tally_obj = mcdc.Tally(
         cell=slab_plane_x["c_right"],
         scores=["current-net", "current-in", "current-out"],
     )
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[slab_plane_x["c_left"], slab_plane_x["c_right"]],
+        tallies=[current_tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
-    current_tally = mcdc_struct["surface_crossing_tallies"][current_tally_obj.child_ID]
+    current_tally = mcdc_struct["surface_crossing_tallies"][current_tally_obj.sub_ID]
 
     # c_right -> vacuum across the right boundary: outgoing (+)
     particle_container = crossing_particle(
@@ -106,19 +114,25 @@ def test_surface_cell_filter_current_counts_outgoing_to_vacuum(
 
 
 def test_surface_cell_filter_current_ignores_reflective_crossing(
-    material_mg, crossing_particle
+    material_mg, crossing_particle, prepare_simulation
 ):
     s_left = mcdc.Surface.PlaneX(x=-1.0, boundary_condition="vacuum")
     s_right = mcdc.Surface.PlaneX(x=1.0, boundary_condition="reflective")
     c_mid = mcdc.Cell(region=+s_left & -s_right, fill=material_mg)
+    simulation = mcdc.Simulation()
+    simulation.set_model([c_mid])
+    simulation.compile()
     current_tally_obj = mcdc.Tally(
         cell=c_mid,
         scores=["current-net", "current-in", "current-out"],
     )
 
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[c_mid],
+        tallies=[current_tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
-    current_tally = mcdc_struct["surface_crossing_tallies"][current_tally_obj.child_ID]
+    current_tally = mcdc_struct["surface_crossing_tallies"][current_tally_obj.sub_ID]
 
     particle_container = crossing_particle(s_right.ID, x=1.0, ux=0.5)
     particle = particle_container[0]
@@ -131,19 +145,25 @@ def test_surface_cell_filter_current_ignores_reflective_crossing(
 
 
 def test_surface_cell_filter_current_scores_curved_boundary(
-    material_mg, crossing_particle
+    material_mg, crossing_particle, prepare_simulation
 ):
     s_cyl = mcdc.Surface.CylinderZ(center=(0.0, 0.0), radius=1.0)
     c_inner = mcdc.Cell(region=-s_cyl, fill=material_mg)
     c_outer = mcdc.Cell(region=+s_cyl, fill=material_mg)
+    simulation = mcdc.Simulation()
+    simulation.set_model([c_inner, c_outer])
+    simulation.compile()
     current_tally_obj = mcdc.Tally(
         cell=c_inner,
         scores=["current-net", "current-in", "current-out"],
     )
 
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[c_inner, c_outer],
+        tallies=[current_tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
-    current_tally = mcdc_struct["surface_crossing_tallies"][current_tally_obj.child_ID]
+    current_tally = mcdc_struct["surface_crossing_tallies"][current_tally_obj.sub_ID]
 
     # Inner -> outer across the cylindrical surface: outgoing from c_inner (+)
     particle_container = crossing_particle(
@@ -173,7 +193,7 @@ def test_surface_cell_filter_current_scores_curved_boundary(
 
 
 def test_surface_cell_filter_scores_only_selected_surface(
-    slab_plane_x, crossing_particle
+    slab_plane_x, crossing_particle, prepare_simulation
 ):
     tally_obj = mcdc.Tally(
         surface=slab_plane_x["s_mid"],
@@ -181,9 +201,12 @@ def test_surface_cell_filter_scores_only_selected_surface(
         scores=["current-net", "current-in", "current-out"],
     )
 
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[slab_plane_x["c_left"], slab_plane_x["c_right"]],
+        tallies=[tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
-    tally = mcdc_struct["surface_crossing_tallies"][tally_obj.child_ID]
+    tally = mcdc_struct["surface_crossing_tallies"][tally_obj.sub_ID]
 
     particle_container = crossing_particle(
         slab_plane_x["s_right"].ID,
diff --git a/test/unit/tally/test_collision_tally.py b/test/unit/tally/test_collision_tally.py
index fcb4ca857..265565d01 100644
--- a/test/unit/tally/test_collision_tally.py
+++ b/test/unit/tally/test_collision_tally.py
@@ -10,6 +10,9 @@ def test_collision_tally_with_mesh_filter():
         z=(-1.0, 1.0, 1),
     )
     tally = mcdc.Tally(mesh=mesh, scores=["energy_deposition"])
+    simulation = mcdc.Simulation()
+    simulation.set_tallies([tally])
+    simulation.compile()
 
     assert isinstance(tally, TallyCollision)
     assert not tally.cell_filtered
diff --git a/test/unit/tally/test_nonbounded_surface_tally.py b/test/unit/tally/test_nonbounded_surface_tally.py
index 0d1eafa26..10ea8db9d 100644
--- a/test/unit/tally/test_nonbounded_surface_tally.py
+++ b/test/unit/tally/test_nonbounded_surface_tally.py
@@ -2,7 +2,6 @@
 import pytest
 
 import mcdc
-from mcdc.main import preparation
 from mcdc.transport.simulation import surface_crossing
 
 
@@ -53,16 +52,19 @@ def test_unbounded_surface_crossing_tally_scoring(
 
 
 def test_surface_crossing_tally_scores_vacuum_boundary(
-    material_mg, bin_value, crossing_particle
+    material_mg, bin_value, crossing_particle, prepare_simulation
 ):
     s_left = mcdc.Surface.PlaneX(x=-1.0, boundary_condition="vacuum")
     s_right = mcdc.Surface.PlaneX(x=1.0, boundary_condition="vacuum")
-    mcdc.Cell(region=+s_left & -s_right, fill=material_mg)
+    cell = mcdc.Cell(region=+s_left & -s_right, fill=material_mg)
     tally_obj = mcdc.Tally(surface=s_right, scores=["current-net"])
 
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[cell],
+        tallies=[tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
-    tally = mcdc_struct["surface_crossing_tallies"][tally_obj.child_ID]
+    tally = mcdc_struct["surface_crossing_tallies"][tally_obj.sub_ID]
 
     particle_container = crossing_particle(s_right.ID, x=1.0, ux=0.5)
     particle = particle_container[0]
@@ -74,16 +76,19 @@ def test_surface_crossing_tally_scores_vacuum_boundary(
 
 
 def test_surface_crossing_tally_scores_after_reflective_boundary(
-    material_mg, bin_value, crossing_particle
+    material_mg, bin_value, crossing_particle, prepare_simulation
 ):
     s_left = mcdc.Surface.PlaneX(x=-1.0, boundary_condition="vacuum")
     s_right = mcdc.Surface.PlaneX(x=1.0, boundary_condition="reflective")
-    mcdc.Cell(region=+s_left & -s_right, fill=material_mg)
+    cell = mcdc.Cell(region=+s_left & -s_right, fill=material_mg)
     tally_obj = mcdc.Tally(surface=s_right, scores=["current-net"])
 
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(
+        cells=[cell],
+        tallies=[tally_obj],
+    )
     mcdc_struct = mcdc_container[0]
-    tally = mcdc_struct["surface_crossing_tallies"][tally_obj.child_ID]
+    tally = mcdc_struct["surface_crossing_tallies"][tally_obj.sub_ID]
 
     particle_container = crossing_particle(s_right.ID, x=1.0, ux=0.5)
     particle = particle_container[0]
diff --git a/test/unit/tally/test_tally_factory.py b/test/unit/tally/test_tally_factory.py
index be95c7af0..24f977374 100644
--- a/test/unit/tally/test_tally_factory.py
+++ b/test/unit/tally/test_tally_factory.py
@@ -75,16 +75,20 @@ def test_tally_factory_allows_combined_supported_filters(slab_plane_x):
         cell=slab_plane_x["c_right"],
         scores=["current-net"],
     )
-    assert surface_cell_tally.surface_filtered
-    assert surface_cell_tally.surface_filter_ID == slab_plane_x["s_mid"].ID
-    assert surface_cell_tally.cell_filtered
-    assert surface_cell_tally.cell_filter_ID == slab_plane_x["c_right"].ID
-
     cell_mesh_tally = mcdc.Tally(
         cell=slab_plane_x["c_right"],
         mesh=mesh,
         scores=["flux"],
     )
+
+    simulation = slab_plane_x["simulation"]
+    simulation.set_tallies([surface_cell_tally, cell_mesh_tally])
+    simulation.compile()
+
+    assert surface_cell_tally.surface_filtered
+    assert surface_cell_tally.surface_filter_ID == slab_plane_x["s_mid"].ID
+    assert surface_cell_tally.cell_filtered
+    assert surface_cell_tally.cell_filter_ID == slab_plane_x["c_right"].ID
     assert cell_mesh_tally.cell_filtered
     assert cell_mesh_tally.cell_filter_ID == slab_plane_x["c_right"].ID
     assert cell_mesh_tally.mesh_filtered
diff --git a/test/unit/tally/test_tracklength_tally.py b/test/unit/tally/test_tracklength_tally.py
index 820d826a2..678447fee 100644
--- a/test/unit/tally/test_tracklength_tally.py
+++ b/test/unit/tally/test_tracklength_tally.py
@@ -4,6 +4,9 @@
 
 def test_tracklength_tally_with_cell_filter(slab_plane_x):
     tally = mcdc.Tally(cell=slab_plane_x["c_left"], scores=["flux", "capture"])
+    simulation = slab_plane_x["simulation"]
+    simulation.set_tallies([tally])
+    simulation.compile()
 
     assert isinstance(tally, TallyTracklength)
     assert tally.cell_filtered
@@ -20,6 +23,9 @@ def test_tracklength_tally_with_mesh_filter():
         z=(-1.0, 1.0, 1),
     )
     tally = mcdc.Tally(mesh=mesh, scores=["flux"])
+    simulation = mcdc.Simulation()
+    simulation.set_tallies([tally])
+    simulation.compile()
 
     assert isinstance(tally, TallyTracklength)
     assert not tally.cell_filtered
diff --git a/test/unit/technique/test_weight_windows.py b/test/unit/technique/test_weight_windows.py
index 5f0c64a00..b12a598cd 100644
--- a/test/unit/technique/test_weight_windows.py
+++ b/test/unit/technique/test_weight_windows.py
@@ -2,7 +2,6 @@
 import numpy as np
 import pytest
 
-from mcdc.main import preparation
 import mcdc.numba_types as type_
 from mcdc.transport.technique import (
     weight_roulette,
@@ -34,7 +33,13 @@ def make_mesh():
     return mesh, N
 
 
-def make_ww_model_params(lower=0.1, target=1.0, upper=1.0, mess_up_size=False):
+def make_ww_model_params(
+    prepare_simulation,
+    lower=0.1,
+    target=1.0,
+    upper=1.0,
+    mess_up_size=False,
+):
     mesh, N = make_mesh()
     Ne = 1
 
@@ -47,13 +52,14 @@ def make_ww_model_params(lower=0.1, target=1.0, upper=1.0, mess_up_size=False):
         ww_array[..., 1] = target
         ww_array[..., 2] = upper
 
-    mcdc.simulation.weight_windows(ww_array, mesh=mesh)
+    def configure(simulation):
+        simulation.weight_windows(ww_array, mesh=mesh)
 
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(configure=configure)
     return mcdc_container[0], data
 
 
-def make_ww_model_distinct():
+def make_ww_model_distinct(prepare_simulation):
     mesh, N = make_mesh()
     energy = np.linspace(0.0, 6.0, 7)
     Ne = 6
@@ -70,9 +76,10 @@ def make_ww_model_distinct():
                     ww_array[e, i, j, k, 1] = 10000 + val
                     ww_array[e, i, j, k, 2] = 20000 + val
 
-    mcdc.simulation.weight_windows(ww_array, mesh=mesh, energy=energy)
+    def configure(simulation):
+        simulation.weight_windows(ww_array, mesh=mesh, energy=energy)
 
-    mcdc_container, data = preparation()
+    mcdc_container, data = prepare_simulation(configure=configure)
     return mcdc_container[0], data
 
 
@@ -106,9 +113,9 @@ def make_ww_model_distinct():
         ),
     ],
 )
-def test_error_throw(capsys, kwargs, expected_msg):
+def test_error_throw(prepare_simulation, capsys, kwargs, expected_msg):
     with pytest.raises(SystemExit):
-        make_ww_model_params(**kwargs)
+        make_ww_model_params(prepare_simulation, **kwargs)
 
     out = capsys.readouterr().out
     assert expected_msg in out
@@ -133,8 +140,8 @@ def test_roulette_from_weight_bounds():
         assert p["w"] == target or not p["alive"]
 
 
-def test_split_from_weight_window():
-    program, data = make_ww_model_distinct()
+def test_split_from_weight_window(prepare_simulation):
+    program, data = make_ww_model_distinct(prepare_simulation)
 
     def run_split(initial_weight, w_upper=1.0, w_target=0.5, w_lower=0.0):
         particles = np.zeros(1, type_.particle)
@@ -188,10 +195,10 @@ def run_split(initial_weight, w_upper=1.0, w_target=0.5, w_lower=0.0):
     assert total_banked < maximum_bank
 
 
-def test_query_weight_window():
+def test_query_weight_window(prepare_simulation):
     p = np.zeros(1, type_.particle_data)
 
-    program, data = make_ww_model_distinct()
+    program, data = make_ww_model_distinct(prepare_simulation)
     simulation = util.access_simulation(program)
     simulation["settings"]["neutron_multigroup_mode"] = False
     # hardcode mesh params

From b842853f6f7ced5bb58890f29dd93caf1cdd316c Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 19:53:18 +0700
Subject: [PATCH 051/202] fix bug on source. update docstring

---
 mcdc/object_/cell.py     |   7 +++
 mcdc/object_/material.py |   4 +-
 mcdc/object_/source.py   | 117 ++++++++++++++++++++++++++++-----------
 mcdc/object_/universe.py |   6 ++
 test/unit/test_source.py |  99 +++++++++++++++++++++++++++++++++
 5 files changed, 201 insertions(+), 32 deletions(-)
 create mode 100644 test/unit/test_source.py

diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 53935d545..9a716db56 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -143,6 +143,13 @@ class Cell(MCDCObject):
     ...     fill=material,
     ... )
 
+    Fill the complement of that union:
+
+    >>> outside_spheres = mcdc.Cell(
+    ...     region=~(-left_sphere | -right_sphere),
+    ...     fill=material,
+    ... )
+
     Place a reusable universe with a translation and rotation:
 
     >>> assembly = mcdc.Universe(name="Assembly", cells=[cell])
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 0e018432c..8e00e6c95 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -74,7 +74,9 @@ class Material(MaterialBase):
     Exactly one of ``nuclide_composition`` or ``element_composition`` must be
     supplied. Nuclide and element objects are created immediately; their
     data-library properties are loaded when the material is compiled into a
-    simulation.
+    simulation. Construction therefore does not access the data library.
+    Before compiling, visualizing, or running the model, ``MCDC_LIB`` must
+    identify the directory containing the required HDF5 files.
 
     Examples
     --------
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 594a5266b..a0fc268fa 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -1,7 +1,8 @@
 import numpy as np
 
-from numpy import float64, int64
-from numpy.typing import NDArray
+from numbers import Integral, Real
+from numpy import float64
+from numpy.typing import ArrayLike, NDArray
 from types import NoneType
 from typing import Annotated, Sequence
 
@@ -20,6 +21,34 @@
 from mcdc.print_ import print_error
 
 
+def _distribution_pair(
+    value: ArrayLike, name: str
+) -> tuple[NDArray[float64], NDArray[float64]]:
+    """Normalize a two-row distribution input and validate its shape."""
+    try:
+        array = np.asarray(value, dtype=float64)
+    except (TypeError, ValueError):
+        print_error(f"{name} distribution must be a rectangular array")
+
+    if array.ndim != 2 or array.shape[0] != 2:
+        print_error(f"{name} distribution must have shape (2, N)")
+
+    return array[0], array[1]
+
+
+def _time_range(value: ArrayLike) -> NDArray[float64]:
+    """Normalize and validate a source time interval."""
+    try:
+        array = np.asarray(value, dtype=float64)
+    except (TypeError, ValueError):
+        print_error("Source time interval must be an array with shape (2,)")
+
+    if array.shape != (2,):
+        print_error("Source time interval must have shape (2,)")
+
+    return array
+
+
 def decode_particle_type(type_):
     """Return the display name for a packed particle-type code."""
 
@@ -72,18 +101,23 @@ class Source(MCDCObject):
         Bounds for the sampled azimuthal angle,
         ``[azi_min, azi_max]`` in radians, measured about ``direction``.
         Defaults to ``[0.0, 2π]``.
-    energy : float or two-item sequence, optional
-        Source energy in eV. A float defines a mono-energetic source. A sequence
-        ``[values, pdf]`` defines a tabulated energy distribution. Defaults to a
+    energy : real or array_like of float, optional
+        Source energy in eV. A real scalar, including a NumPy scalar, defines a
+        mono-energetic source. An array-like value with shape ``(2, N)`` defines
+        a tabulated distribution: the first row contains energy values and the
+        second row contains their probability density. Defaults to a
         mono-energetic source at **1 MeV**.
-    energy_group : int or two-item sequence, optional
-        Source energy group. An integer defines a mono-group source. A sequence
-        ``[groups, probabilities]`` defines a discrete probability mass
-        function. In multigroup simulations, the default is **group 0**.
-    time : float or array_like of float, optional
-        Emission time in seconds. A float defines a discrete emission time.
-        A two-entry array-like value defines a time interval
-        ``[t_min, t_max]``. Defaults to ``0.0``.
+    energy_group : int or array_like, optional
+        Source energy group. A Python or NumPy integer defines a mono-group
+        source. An array-like value with shape ``(2, N)`` defines a discrete
+        probability mass function: the first row contains group IDs and the
+        second row contains their probabilities. In multigroup simulations,
+        the default is **group 0**.
+    time : real or array_like of float, optional
+        Emission time in seconds. A real scalar, including a NumPy scalar,
+        defines a discrete emission time. An array-like value with shape
+        ``(2,)`` defines a uniform interval ``[t_min, t_max]``. Defaults to
+        ``0.0``.
     particle_type : {"neutron", "electron", "proton"}, optional
         Type of emitted particle. Defaults to ``"neutron"``.
     probability : float, optional
@@ -107,6 +141,7 @@ class Source(MCDCObject):
     - otherwise, the default direction behavior is used.
 
     ``energy_group`` takes precedence over ``energy`` when both are provided.
+    Array-like inputs may be supplied as lists, tuples, or NumPy arrays.
 
     Examples
     --------
@@ -156,6 +191,26 @@ class Source(MCDCObject):
     ...     energy_group=3,
     ... )
 
+    Sample a continuous-energy source from a tabulated probability density:
+
+    >>> electron_source = mcdc.Source(
+    ...     particle_type="electron",
+    ...     energy=np.array([
+    ...         [9_999.0, 10_001.0],
+    ...         [0.5, 0.5],
+    ...     ]),
+    ...     direction=[0.0, 0.0, 1.0],
+    ... )
+
+    Sample between two multigroup energy groups:
+
+    >>> multigroup_source = mcdc.Source(
+    ...     energy_group=(
+    ...         [0, 1],
+    ...         [0.25, 0.75],
+    ...     ),
+    ... )
+
     Time-dependent source:
 
     >>> src = mcdc.Source(
@@ -222,10 +277,10 @@ def __init__(
         polar_cosine: Sequence[float] | NoneType = None,
         azimuthal: Sequence[float] | NoneType = None,
         #
-        energy: float | NDArray[float64] | NoneType = None,
-        energy_group: int | NDArray[int64] | NoneType = None,
+        energy: ArrayLike | NoneType = None,
+        energy_group: ArrayLike | NoneType = None,
         #
-        time: float | Sequence[float] = 0.0,
+        time: ArrayLike = 0.0,
         #
         particle_type: str = "neutron",
         #
@@ -316,28 +371,28 @@ def __init__(
 
         # Energy
         if energy_group is not None:
-            if type(energy_group) == int:
-                self.energy_group = energy_group
-            elif isinstance(energy_group, Sequence):
+            if isinstance(energy_group, Integral) and not isinstance(
+                energy_group, (bool, np.bool_)
+            ):
+                self.energy_group = int(energy_group)
+            else:
+                values, probabilities = _distribution_pair(energy_group, "Energy-group")
                 self.mono_energetic = False
-                self.energy_group_pmf = DistributionPMF(
-                    energy_group[0], energy_group[1]
-                )
+                self.energy_group_pmf = DistributionPMF(values, probabilities)
         elif energy is not None:
-            if type(energy) == float:
-                self.energy = energy
-            elif isinstance(energy, Sequence):
+            if isinstance(energy, Real) and not isinstance(energy, (bool, np.bool_)):
+                self.energy = float(energy)
+            else:
+                values, pdf = _distribution_pair(energy, "Energy")
                 self.mono_energetic = False
-                self.energy_pdf = DistributionTabulated(
-                    np.array(energy[0]), np.array(energy[1])
-                )
+                self.energy_pdf = DistributionTabulated(values, pdf)
 
         # Time
-        if type(time) == float:
-            self.time = time
+        if isinstance(time, Real) and not isinstance(time, (bool, np.bool_)):
+            self.time = float(time)
         else:
             self.discrete_time = False
-            self.time_range = np.array(time)
+            self.time_range = _time_range(time)
 
         # Particle type
         if particle_type == "neutron":
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index 1a1ac359d..cf94c8ee5 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -118,6 +118,12 @@ class Lattice(MCDCObject):
         Universe layout supplied in ``[z][y][x]`` order. The y and z axes are
         reversed internally to match MC/DC's Cartesian indexing convention.
 
+    Notes
+    -----
+    A lattice retains the supplied :class:`Universe` objects. When the owning
+    simulation is compiled, those universes are registered and the packed
+    lattice IDs are rebuilt from their simulation-local IDs.
+
     Examples
     --------
     Place two universes next to each other along x:
diff --git a/test/unit/test_source.py b/test/unit/test_source.py
new file mode 100644
index 000000000..3ffd4d4c2
--- /dev/null
+++ b/test/unit/test_source.py
@@ -0,0 +1,99 @@
+import numpy as np
+import pytest
+
+import mcdc
+
+
+@pytest.mark.parametrize(
+    "energy",
+    [
+        10_000,
+        10_000.0,
+        np.int64(10_000),
+        np.float64(10_000.0),
+    ],
+)
+def test_scalar_energy(energy):
+    source = mcdc.Source(energy=energy)
+
+    assert source.mono_energetic
+    assert source.energy == 10_000.0
+
+
+@pytest.mark.parametrize(
+    "energy",
+    [
+        [[9_999.0, 10_001.0], [0.5, 0.5]],
+        ([9_999.0, 10_001.0], [0.5, 0.5]),
+        np.array([[9_999.0, 10_001.0], [0.5, 0.5]]),
+    ],
+)
+def test_energy_distribution(energy):
+    source = mcdc.Source(energy=energy)
+
+    assert not source.mono_energetic
+    np.testing.assert_array_equal(source.energy_pdf.pdf.x, [9_999.0, 10_001.0])
+
+
+@pytest.mark.parametrize("energy_group", [3, np.int64(3)])
+def test_scalar_energy_group(energy_group):
+    source = mcdc.Source(energy_group=energy_group)
+
+    assert source.mono_energetic
+    assert source.energy_group == 3
+
+
+@pytest.mark.parametrize(
+    "energy_group",
+    [
+        [[1, 3], [0.25, 0.75]],
+        ([1, 3], [0.25, 0.75]),
+        np.array([[1, 3], [0.25, 0.75]]),
+    ],
+)
+def test_energy_group_distribution(energy_group):
+    source = mcdc.Source(energy_group=energy_group)
+
+    assert not source.mono_energetic
+    np.testing.assert_array_equal(source.energy_group_pmf.value, [1, 3])
+
+
+@pytest.mark.parametrize("time", [2, 2.0, np.int64(2), np.float64(2.0)])
+def test_scalar_time(time):
+    source = mcdc.Source(time=time)
+
+    assert source.discrete_time
+    assert source.time == 2.0
+
+
+@pytest.mark.parametrize(
+    "time",
+    [
+        [1.0, 2.0],
+        (1.0, 2.0),
+        np.array([1.0, 2.0]),
+    ],
+)
+def test_time_interval(time):
+    source = mcdc.Source(time=time)
+
+    assert not source.discrete_time
+    np.testing.assert_array_equal(source.time_range, [1.0, 2.0])
+
+
+@pytest.mark.parametrize(
+    "kwargs, expected_message",
+    [
+        ({"energy": [1.0, 2.0, 3.0]}, "Energy distribution must have shape (2, N)"),
+        (
+            {"energy_group": [1, 2, 3]},
+            "Energy-group distribution must have shape (2, N)",
+        ),
+        ({"time": [1.0, 2.0, 3.0]}, "Source time interval must have shape (2,)"),
+    ],
+)
+def test_invalid_distribution_shape(kwargs, expected_message, capsys):
+    with pytest.raises(SystemExit):
+        mcdc.Source(**kwargs)
+
+    assert expected_message in capsys.readouterr().out

From 405d53eba34993b70adde4de0ded8e1fd5708322 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 19:56:07 +0700
Subject: [PATCH 052/202] rearrange functions

---
 mcdc/object_/source.py | 84 ++++++++++++++++++++++--------------------
 1 file changed, 44 insertions(+), 40 deletions(-)

diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index a0fc268fa..8356902c6 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -20,46 +20,6 @@
 from mcdc.object_.util import move_object
 from mcdc.print_ import print_error
 
-
-def _distribution_pair(
-    value: ArrayLike, name: str
-) -> tuple[NDArray[float64], NDArray[float64]]:
-    """Normalize a two-row distribution input and validate its shape."""
-    try:
-        array = np.asarray(value, dtype=float64)
-    except (TypeError, ValueError):
-        print_error(f"{name} distribution must be a rectangular array")
-
-    if array.ndim != 2 or array.shape[0] != 2:
-        print_error(f"{name} distribution must have shape (2, N)")
-
-    return array[0], array[1]
-
-
-def _time_range(value: ArrayLike) -> NDArray[float64]:
-    """Normalize and validate a source time interval."""
-    try:
-        array = np.asarray(value, dtype=float64)
-    except (TypeError, ValueError):
-        print_error("Source time interval must be an array with shape (2,)")
-
-    if array.shape != (2,):
-        print_error("Source time interval must have shape (2,)")
-
-    return array
-
-
-def decode_particle_type(type_):
-    """Return the display name for a packed particle-type code."""
-
-    if type_ == PARTICLE_NEUTRON:
-        return "Neutron"
-    elif type_ == PARTICLE_ELECTRON:
-        return "Electron"
-    elif type_ == PARTICLE_PROTON:
-        return "Proton"
-
-
 # ======================================================================================
 # Source
 # ======================================================================================
@@ -518,3 +478,47 @@ def move(self, velocities, durations):
         ... )
         """
         move_object(self, velocities, durations)
+
+
+def decode_particle_type(type_):
+    """Return the display name for a packed particle-type code."""
+
+    if type_ == PARTICLE_NEUTRON:
+        return "Neutron"
+    elif type_ == PARTICLE_ELECTRON:
+        return "Electron"
+    elif type_ == PARTICLE_PROTON:
+        return "Proton"
+
+
+# ======================================================================================
+# Helper functions
+# ======================================================================================
+
+
+def _distribution_pair(
+    value: ArrayLike, name: str
+) -> tuple[NDArray[float64], NDArray[float64]]:
+    """Normalize a two-row distribution input and validate its shape."""
+    try:
+        array = np.asarray(value, dtype=float64)
+    except (TypeError, ValueError):
+        print_error(f"{name} distribution must be a rectangular array")
+
+    if array.ndim != 2 or array.shape[0] != 2:
+        print_error(f"{name} distribution must have shape (2, N)")
+
+    return array[0], array[1]
+
+
+def _time_range(value: ArrayLike) -> NDArray[float64]:
+    """Normalize and validate a source time interval."""
+    try:
+        array = np.asarray(value, dtype=float64)
+    except (TypeError, ValueError):
+        print_error("Source time interval must be an array with shape (2,)")
+
+    if array.shape != (2,):
+        print_error("Source time interval must have shape (2,)")
+
+    return array

From abd6fc7253a0e79d1c7905af36c4ef61ae1474c0 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 20:28:34 +0700
Subject: [PATCH 053/202] Fix all-groups tally bin allocation for multigroup
 simulations

---
 mcdc/object_/tally.py                 | 11 ++++++++---
 test/unit/tally/test_tally_factory.py | 22 ++++++++++++++++++++++
 2 files changed, 30 insertions(+), 3 deletions(-)

diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 337599d40..65c03d86d 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -301,6 +301,7 @@ def __init__(
         self.filter_direction = False
         self.filter_energy = False
         self.filter_time = False
+        self.energy_all_groups = False
         if mu is not None:
             self.mu = np.array(mu)
             self.filter_direction = True
@@ -314,6 +315,7 @@ def __init__(
             )
         if energy is not None:
             if type(energy) == str and energy == "all_groups":
+                self.energy_all_groups = True
                 self.energy = np.array([0])  # A placeholder
             else:
                 self.energy = np.array(energy)
@@ -377,7 +379,7 @@ def _phasespace_filter_text(self):
         if self.filter_time:
             text += f"    - Time {print_1d_array(self.time)} s\n"
         if self.filter_energy:
-            if len(self.energy) == 1:
+            if self.energy_all_groups:
                 text += f"    - Energy: All groups\n"
             else:
                 text += f"    - Energy {print_1d_array(self.energy)} eV\n"
@@ -393,10 +395,13 @@ def _compile_into_simulation(self, simulation) -> bool:
         if not super()._compile_into_simulation(simulation):
             return False
 
-        # Set "all_group" energy filter
-        if len(self.energy) == 1:
+        # Resolve the "all_groups" energy filter and resize its tally bins.
+        if self.energy_all_groups:
             G = simulation.materials[0].G
             self.energy = np.linspace(0, G, G + 1) - 0.5
+            shape = list(self.bin_shape)
+            shape[2] = G
+            self._set_bin_shape_and_strides(tuple(shape))
 
         return True
 
diff --git a/test/unit/tally/test_tally_factory.py b/test/unit/tally/test_tally_factory.py
index 24f977374..6a01a75b6 100644
--- a/test/unit/tally/test_tally_factory.py
+++ b/test/unit/tally/test_tally_factory.py
@@ -1,3 +1,4 @@
+import numpy as np
 import pytest
 
 import mcdc
@@ -95,6 +96,27 @@ def test_tally_factory_allows_combined_supported_filters(slab_plane_x):
     assert cell_mesh_tally.mesh_filter_ID == mesh.ID
 
 
+def test_all_groups_filter_resizes_compiled_tally_bins(prepare_simulation):
+    material = mcdc.MaterialMG(capture=np.ones(3))
+    cell = mcdc.Cell(fill=material)
+    tally = mcdc.Tally(scores=["flux"], energy="all_groups")
+
+    simulation_container, data = prepare_simulation(cells=[cell], tallies=[tally])
+    simulation = simulation_container[0]
+    tally_record = simulation["tallies"][tally.ID]
+
+    np.testing.assert_array_equal(tally.energy, [-0.5, 0.5, 1.5, 2.5])
+    assert tally.bin_shape == [1, 1, 3, 1, 1]
+    assert tally.stride_energy == 1
+    assert tally.stride_azi == 3
+    assert tally.stride_mu == 3
+    assert tally_record["bin_length"] == 3
+
+    bin_start = tally_record["bin_offset"]
+    bin_stop = bin_start + tally_record["bin_length"]
+    assert len(data[bin_start:bin_stop]) == 3
+
+
 def test_tally_factory_rejects_mixed_estimator_scores(capsys):
     with pytest.raises(SystemExit):
         mcdc.Tally(scores=["flux", "energy_deposition"])

From ae608edddd3660a1c618411617d18c794861e2f9 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 20:52:37 +0700
Subject: [PATCH 054/202] update changelog

---
 CHANGELOG.md | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 1515c1663..17ec3adcd 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -11,6 +11,12 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/2.0.0/),
 ### Changed
 
 - Move regression tests from the custom `run.py` harness to pytest-based collection and reporting from [@massimolarsen]
+- **Breaking:** Redesign model construction around explicit `mcdc.Simulation`
+  instances, replacing the global simulation, settings, run, and visualization
+  interfaces. Each simulation now owns and compiles its complete object graph,
+  handles associated input and output workflows, and can be independently
+  visualized or run. Regression problems, public API documentation, and unit
+  tests have been updated for the new workflow from [@ilhamv]
 
 ### Deprecated
 

From aa8f6540369e61a167a8d543abe5cc3b11013c5e Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 21:12:11 +0700
Subject: [PATCH 055/202] Python 3.10 compatibile f strings

---
 mcdc/object_/cell.py     | 2 +-
 mcdc/object_/tally.py    | 4 +---
 mcdc/object_/universe.py | 2 +-
 3 files changed, 3 insertions(+), 5 deletions(-)

diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 9a716db56..a27027ac6 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -261,7 +261,7 @@ def __repr__(self):
         else:
             text += f"  - {self.region}\n"
         if self.fill:
-            text += f"  - Fill [{self.fill.label.title().replace("_"," ")}]: {self.fill.name}\n"
+            text += f"  - Fill [{self.fill.label.title().replace('_', ' ')}]: {self.fill.name}\n"
         else:
             text += f"  - Fill [None]"
         if self.fill_translated:
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 815a90d22..d7f89a4e9 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -371,9 +371,7 @@ def _use_census_based_tally(self, frequency: int, simulation):
 
     def _phasespace_filter_text(self):
         text = ""
-        text += (
-            f"  - Scores: {", ".join([decode_score_type(x) for x in self.scores])}\n"
-        )
+        text += f"  - Scores: {', '.join(decode_score_type(x) for x in self.scores)}\n"
         if self.filter_time or self.filter_energy or self.filter_direction:
             text += f"  - Phase-space filters\n"
         if self.filter_time:
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index cf94c8ee5..d30b2d98a 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -95,7 +95,7 @@ def __repr__(self):
         text = super().__repr__()
 
         text += f"  - Name: {self.name}\n"
-        text += f"  - Cells: {", ".join([x.name for x in self.cells])}\n"
+        text += f"  - Cells: {', '.join(x.name for x in self.cells)}\n"
         return text
 
 

From 43869065b73b7e74905072187f86c0ba813046d3 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 27 Jul 2026 22:36:26 +0700
Subject: [PATCH 056/202] fix bug in getting inelastic scattering multiplicity

---
 mcdc/transport/physics/neutron/native.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/mcdc/transport/physics/neutron/native.py b/mcdc/transport/physics/neutron/native.py
index 7bd2583d9..916b290e6 100644
--- a/mcdc/transport/physics/neutron/native.py
+++ b/mcdc/transport/physics/neutron/native.py
@@ -189,9 +189,12 @@ def _neutron_inelastic_scattering_production_xs(particle_container, simulation,
                 )
             )
             reaction = simulation["neutron_reactions"][reaction_ID]
+            inelastic_scattering = simulation["neutron_inelastic_scattering_reactions"][
+                reaction["sub_ID"]
+            ]
 
             xs = reaction_micro_xs(E, reaction, nuclide, data)
-            nu = reaction["multiplicity"]
+            nu = inelastic_scattering["multiplicity"]
             total += nuclide_density * nu * xs
 
     return total

From d3f32c3ce74ca0996cd8f5565ced0142e2fe9c33 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 28 Jul 2026 06:08:18 +0700
Subject: [PATCH 057/202] Update examples

---
 examples/c5g7/k-eigenvalue/input.py   | 26 ++++++++++++----------
 examples/c5g7/transient/input.py      | 22 +++++++++++--------
 examples/fuel_array_packaged/input.py | 31 ++++++++++++++++++---------
 examples/kobayashi-TD/input.py        | 27 +++++++++++++----------
 examples/kobayashi/input.py           | 25 +++++++++++----------
 examples/moving_pellet/input.py       | 25 ++++++++++++---------
 examples/moving_source/input.py       | 15 ++++++++-----
 examples/sphere_in_cube/input.py      | 21 ++++++++++++------
 8 files changed, 118 insertions(+), 74 deletions(-)

diff --git a/examples/c5g7/k-eigenvalue/input.py b/examples/c5g7/k-eigenvalue/input.py
index 15ecfdc2e..9d69f9e11 100644
--- a/examples/c5g7/k-eigenvalue/input.py
+++ b/examples/c5g7/k-eigenvalue/input.py
@@ -3,6 +3,8 @@
 
 import mcdc
 
+simulation = mcdc.Simulation("C5G7 k-eigenvalue")
+
 # =============================================================================
 # Materials
 # =============================================================================
@@ -255,9 +257,9 @@ def set_mat(mat):
 reflector_south = mcdc.Cell(+x0 & -x3 & +y0 & -y1 & +z1 & -z2, mat_mod)
 reflector_east = mcdc.Cell(+x2 & -x3 & +y1 & -y3 & +z1 & -z2, mat_mod)
 
-# Root universe
-mcdc.simulation.set_root_universe(
-    cells=[
+# Set model
+simulation.set_model(
+    [
         assembly_1,
         assembly_2,
         assembly_3,
@@ -265,20 +267,21 @@ def set_mat(mat):
         reflector_bottom,
         reflector_south,
         reflector_east,
-    ],
+    ]
 )
 
 # =============================================================================
 # Set source
 # =============================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     x=[0.0, pitch * 17 * 2],
     y=[-pitch * 17 * 2, 0.0],
     z=[-core_height / 2, core_height / 2],
     isotropic=True,
     energy_group=0,  # Highest energy
 )
+simulation.set_sources([source])
 
 # =============================================================================
 # Set tallies, settings, techniques and run MC/DC
@@ -292,15 +295,16 @@ def set_mat(mat):
 )
 g_grid = np.array([-0.5, 3.5, 6.5])  # Collapsing to fast (1-4) and slow (5-7)
 mesh = mcdc.MeshStructured(x=x_grid, y=y_grid, z=z_grid)
-mcdc.Tally(mesh=mesh, scores=["flux"], energy=g_grid)
+tally = mcdc.Tally(mesh=mesh, scores=["flux"], energy=g_grid)
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 50
-mcdc.settings.census_bank_buffer_ratio = 4.0
-mcdc.settings.set_eigenmode(N_inactive=5, N_active=10, gyration_radius="all")
+simulation.settings.N_particle = 50
+simulation.settings.census_bank_buffer_ratio = 4.0
+simulation.settings.set_eigenmode(N_inactive=5, N_active=10, gyration_radius="all")
 
 # Techniques
-mcdc.simulation.population_control()
+simulation.population_control()
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/examples/c5g7/transient/input.py b/examples/c5g7/transient/input.py
index 2381f8c00..06e398c2d 100644
--- a/examples/c5g7/transient/input.py
+++ b/examples/c5g7/transient/input.py
@@ -3,6 +3,8 @@
 
 import mcdc
 
+simulation = mcdc.Simulation("C5G7 transient")
+
 # =============================================================================
 # Materials
 # =============================================================================
@@ -314,9 +316,9 @@ def set_mat(mat):
 reflector_south = mcdc.Cell(+x0 & -x3 & +y0 & -y1 & +z1 & -z2, mat_mod)
 reflector_east = mcdc.Cell(+x2 & -x3 & +y1 & -y3 & +z1 & -z2, mat_mod)
 
-# Root universe
-mcdc.simulation.set_root_universe(
-    cells=[
+# Set model
+simulation.set_model(
+    [
         assembly_1,
         assembly_2,
         assembly_3,
@@ -324,7 +326,7 @@ def set_mat(mat):
         reflector_bottom,
         reflector_south,
         reflector_east,
-    ],
+    ]
 )
 
 # =============================================================================
@@ -341,6 +343,7 @@ def set_mat(mat):
     energy_group=0,  # Highest energy
     time=[0.0, 15.0],
 )
+simulation.set_sources([source])
 
 # =============================================================================
 # Set tallies, settings, techniques and run MC/DC
@@ -356,12 +359,13 @@ def set_mat(mat):
 y = np.linspace(-pitch * 17 * 2, 0.0, Ny + 1)
 z = np.linspace(-core_height / 2, core_height / 2, Nz + 1)
 mesh = mcdc.MeshStructured(x=x, y=y, z=z)
-mcdc.Tally(mesh=mesh, scores=["fission"], time=t)
+tally = mcdc.Tally(mesh=mesh, scores=["fission"], time=t)
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 10000
-mcdc.settings.N_batch = 2
-mcdc.settings.active_bank_buffer = 1000
+simulation.settings.N_particle = 10000
+simulation.settings.N_batch = 2
+simulation.settings.active_bank_buffer = 1000
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/examples/fuel_array_packaged/input.py b/examples/fuel_array_packaged/input.py
index c507a0096..b8c7f9dfe 100644
--- a/examples/fuel_array_packaged/input.py
+++ b/examples/fuel_array_packaged/input.py
@@ -1,6 +1,8 @@
 import numpy as np
 import mcdc
 
+simulation = mcdc.Simulation("Packaged fuel array")
+
 # ======================================================================================
 # Materials
 # ======================================================================================
@@ -68,14 +70,15 @@
     region=container_right, fill=assembly, translation=[+5, 0, 0], rotation=[0, 10, 0]
 )
 
-# Root universe
-mcdc.simulation.set_root_universe(cells=[assembly_left, assembly_right])
+# Set model
+simulation.set_model([assembly_left, assembly_right])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 
-mcdc.Source(x=[-0.1, 0.1], isotropic=True, energy_group=0)
+source = mcdc.Source(x=[-0.1, 0.1], isotropic=True, energy_group=0)
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
@@ -86,23 +89,31 @@
     x=np.linspace(-10, 10, 201),
     z=np.linspace(-5, 5, 101),
 )
-mcdc.Tally(mesh=mesh, scores=["fission"])
+tally = mcdc.Tally(mesh=mesh, scores=["fission"])
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 1000
-mcdc.settings.N_batch = 2
-mcdc.settings.active_bank_buffer = 1000
+simulation.settings.N_particle = 1000
+simulation.settings.N_batch = 2
+simulation.settings.active_bank_buffer = 1000
 
 # Run (or visualize)
 visualize = False
 if not visualize:
-    mcdc.run()
+    simulation.run()
 else:
     colors = {
         fuel: "red",
         cover: "gray",
         water: "blue",
     }
-    mcdc.visualize(
-        "xz", y=0.0, x=[-11.0, 11.0], z=[-6, 6], pixels=(400, 400), colors=colors
+    simulation.visualize_model(
+        vis_plane="xz",
+        y=0.0,
+        x=[-11.0, 11.0],
+        z=[-6, 6],
+        pixels=(400, 400),
+        colors=colors,
+        time=[0.0],
+        save_as=None,
     )
diff --git a/examples/kobayashi-TD/input.py b/examples/kobayashi-TD/input.py
index 05e4808aa..dc939d8d6 100644
--- a/examples/kobayashi-TD/input.py
+++ b/examples/kobayashi-TD/input.py
@@ -1,6 +1,8 @@
 import numpy as np
 import mcdc
 
+simulation = mcdc.Simulation("Time-dependent Kobayashi dog-leg benchmark")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -30,24 +32,25 @@
 
 # Set cells
 # Source
-mcdc.Cell(region=+sx1 & -sx2 & +sy1 & -sy2 & +sz1 & -sz2, fill=m)
+source_cell = mcdc.Cell(region=+sx1 & -sx2 & +sy1 & -sy2 & +sz1 & -sz2, fill=m)
 # Voids
 channel_1 = +sx1 & -sx2 & +sy2 & -sy3 & +sz1 & -sz2
 channel_2 = +sx1 & -sx3 & +sy3 & -sy4 & +sz1 & -sz2
 channel_3 = +sx3 & -sx4 & +sy3 & -sy4 & +sz1 & -sz3
 channel_4 = +sx3 & -sx4 & +sy3 & -sy5 & +sz3 & -sz4
 void_channel = channel_1 | channel_2 | channel_3 | channel_4
-mcdc.Cell(region=void_channel, fill=m_void)
+void_cell = mcdc.Cell(region=void_channel, fill=m_void)
 # Shield
 box = +sx1 & -sx5 & +sy1 & -sy5 & +sz1 & -sz5
-mcdc.Cell(region=box & ~void_channel, fill=m)
+shield_cell = mcdc.Cell(region=box & ~void_channel, fill=m)
+simulation.set_model([source_cell, void_cell, shield_cell])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
-# The source pulses in t=[0,5]
+# The source pulses in t=[0, 50]
 
-mcdc.Source(
+source = mcdc.Source(
     x=[0.0, 10.0],
     y=[0.0, 10.0],
     z=[0.0, 10.0],
@@ -55,6 +58,7 @@
     energy_group=0,
     time=[0.0, 50.0],
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, techniques, and run MC/DC
@@ -63,15 +67,16 @@
 # Tallies
 time_grid = np.linspace(0.0, 200.0, 21)
 mesh = mcdc.MeshUniform(x=(0.0, 1.0, 60), y=(0.0, 1.0, 100))
-mcdc.Tally(mesh=mesh, scores=["flux"], time=time_grid)
-mcdc.Tally(scores=["density"], time=time_grid)
+flux_tally = mcdc.Tally(mesh=mesh, scores=["flux"], time=time_grid)
+density_tally = mcdc.Tally(scores=["density"], time=time_grid)
+simulation.set_tallies([flux_tally, density_tally])
 
 # Settings
-mcdc.settings.N_particle = 100
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 100
+simulation.settings.N_batch = 2
 
 # Techniques
-mcdc.simulation.implicit_capture()
+simulation.implicit_capture()
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/examples/kobayashi/input.py b/examples/kobayashi/input.py
index 3f6f11929..b34d40b9d 100644
--- a/examples/kobayashi/input.py
+++ b/examples/kobayashi/input.py
@@ -1,6 +1,8 @@
 import numpy as np
 import mcdc
 
+simulation = mcdc.Simulation("Kobayashi dog-leg benchmark")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -30,30 +32,30 @@
 
 # Set cells
 # Source
-mcdc.Cell(region=+sx1 & -sx2 & +sy1 & -sy2 & +sz1 & -sz2, fill=m)
+source_cell = mcdc.Cell(region=+sx1 & -sx2 & +sy1 & -sy2 & +sz1 & -sz2, fill=m)
 # Voids
 channel_1 = +sx1 & -sx2 & +sy2 & -sy3 & +sz1 & -sz2
 channel_2 = +sx1 & -sx3 & +sy3 & -sy4 & +sz1 & -sz2
 channel_3 = +sx3 & -sx4 & +sy3 & -sy4 & +sz1 & -sz3
 channel_4 = +sx3 & -sx4 & +sy3 & -sy5 & +sz3 & -sz4
 void_channel = channel_1 | channel_2 | channel_3 | channel_4
-mcdc.Cell(region=void_channel, fill=m_void)
+void_cell = mcdc.Cell(region=void_channel, fill=m_void)
 # Shield
 box = +sx1 & -sx5 & +sy1 & -sy5 & +sz1 & -sz5
-mcdc.Cell(region=box & ~void_channel, fill=m)
+shield_cell = mcdc.Cell(region=box & ~void_channel, fill=m)
+simulation.set_model([source_cell, void_cell, shield_cell])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
-# The source pulses in t=[0,5]
-
-mcdc.Source(
+source = mcdc.Source(
     x=[0.0, 10.0],
     y=[0.0, 10.0],
     z=[0.0, 10.0],
     isotropic=True,
     energy_group=0,
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, techniques, and run MC/DC
@@ -61,14 +63,15 @@
 
 # Tallies
 mesh = mcdc.MeshUniform(x=(0.0, 1.0, 60), y=(0.0, 1.0, 100), z=(0.0, 1.0, 60))
-mcdc.Tally(mesh=mesh, scores=["flux"])
+tally = mcdc.Tally(mesh=mesh, scores=["flux"])
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 1000
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 1000
+simulation.settings.N_batch = 2
 
 # Techniques
-mcdc.simulation.implicit_capture()
+simulation.implicit_capture()
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/examples/moving_pellet/input.py b/examples/moving_pellet/input.py
index addcb050e..e1c5c6e33 100644
--- a/examples/moving_pellet/input.py
+++ b/examples/moving_pellet/input.py
@@ -2,6 +2,8 @@
 
 import mcdc
 
+simulation = mcdc.Simulation("Moving pellet")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -39,17 +41,18 @@
 
 # Make cells
 fuel_pellet_region = +bot_z & -top_z & -cylinder_z
-mcdc.Cell(region=fuel_pellet_region, fill=fuel)
-mcdc.Cell(
+fuel_cell = mcdc.Cell(region=fuel_pellet_region, fill=fuel)
+air_cell = mcdc.Cell(
     region=~fuel_pellet_region & +min_x & -max_x & +min_y & -max_y & +min_z & -max_z,
     fill=air,
 )
+simulation.set_model([fuel_cell, air_cell])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     x=[2.0, 3.0],
     y=[-0.5, 0.5],
     z=[-0.5, 0.5],
@@ -57,6 +60,7 @@
     energy_group=0,
     time=[0.0, 9.0],
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
@@ -67,24 +71,25 @@
     x=np.linspace(-5, 5, 201),
     z=np.linspace(-10, 10, 201),
 )
-mcdc.Tally(mesh=mesh, scores=["fission"], time=np.linspace(0, 9, 46))
+tally = mcdc.Tally(mesh=mesh, scores=["fission"], time=np.linspace(0, 9, 46))
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 100000
-mcdc.settings.N_batch = 2
-mcdc.settings.active_bank_buffer = 1000
+simulation.settings.N_particle = 100000
+simulation.settings.N_batch = 2
+simulation.settings.active_bank_buffer = 1000
 
 # Run (or visualize)
 visualize = False
 if not visualize:
-    mcdc.run()
+    simulation.run()
 else:
     colors = {
         fuel: "red",
         air: "blue",
     }
-    mcdc.visualize(
-        "xz",
+    simulation.visualize_model(
+        vis_plane="xz",
         y=0.0,
         x=[-5.0, 5.0],
         z=[-10, 10],
diff --git a/examples/moving_source/input.py b/examples/moving_source/input.py
index c11ae3e8e..a739c542d 100644
--- a/examples/moving_source/input.py
+++ b/examples/moving_source/input.py
@@ -2,6 +2,8 @@
 
 import mcdc
 
+simulation = mcdc.Simulation("Moving source")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -22,7 +24,8 @@
 max_z = mcdc.Surface.PlaneZ(z=10.0, boundary_condition="vacuum")
 
 # Make cells
-mcdc.Cell(region=+min_x & -max_x & +min_y & -max_y & +min_z & -max_z, fill=air)
+cell = mcdc.Cell(region=+min_x & -max_x & +min_y & -max_y & +min_z & -max_z, fill=air)
+simulation.set_model([cell])
 
 # ======================================================================================
 # Set source
@@ -45,6 +48,7 @@
     ],
     durations=[7.0, 2.0, 1.0],
 )
+simulation.set_sources([src])
 
 # ======================================================================================
 # Set tallies, settings, and run MC/DC
@@ -55,11 +59,12 @@
     x=np.linspace(-5.0, 5.0, 201),
     y=np.linspace(-5.0, 5.0, 201),
 )
-mcdc.Tally(mesh=mesh, scores=["flux"], time=np.linspace(0, 10, 46))
+tally = mcdc.Tally(mesh=mesh, scores=["flux"], time=np.linspace(0, 10, 46))
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 100000
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 100000
+simulation.settings.N_batch = 2
 
 # Run
-mcdc.run()
+simulation.run()
diff --git a/examples/sphere_in_cube/input.py b/examples/sphere_in_cube/input.py
index 6b9b4da2e..d047062b4 100644
--- a/examples/sphere_in_cube/input.py
+++ b/examples/sphere_in_cube/input.py
@@ -1,6 +1,8 @@
 import numpy as np
 import mcdc
 
+simulation = mcdc.Simulation("Sphere in cube")
+
 # ======================================================================================
 # Set model
 # ======================================================================================
@@ -22,14 +24,15 @@
 inside_box = +sx1 & -sx2 & +sy1 & -sy2 & +sz1 & -sz2
 
 # Set cells
-mcdc.Cell(name="Box cover", region=inside_box & ~inside_sphere, fill=pure_s)
+box_cell = mcdc.Cell(name="Box cover", region=inside_box & ~inside_sphere, fill=pure_s)
 sphere_cell = mcdc.Cell(name="The sphere", region=inside_sphere, fill=pure_f)
+simulation.set_model([box_cell, sphere_cell])
 
 # ======================================================================================
 # Set source
 # ======================================================================================
 
-mcdc.Source(
+source = mcdc.Source(
     x=[0.0, 4.0],
     y=[0.0, 4.0],
     z=[0.0, 4.0],
@@ -37,20 +40,24 @@
     energy_group=0,
     time=[0.0, 50.0],
 )
+simulation.set_sources([source])
 
 # ======================================================================================
 # Set tallies, settings, techniques, and run MC/DC
 # ======================================================================================
 
 # Tallies
-mcdc.Tally(name="Spherical fission detector", cell=sphere_cell, scores=["fission"])
+tally = mcdc.Tally(
+    name="Spherical fission detector", cell=sphere_cell, scores=["fission"]
+)
+simulation.set_tallies([tally])
 
 # Settings
-mcdc.settings.N_particle = 1000
-mcdc.settings.N_batch = 2
+simulation.settings.N_particle = 1000
+simulation.settings.N_batch = 2
 
 # Techniques
-mcdc.simulation.implicit_capture()
+simulation.implicit_capture()
 
 # Run
-mcdc.run()
+simulation.run()

From ca3af8d442b42504c8a2a930df842a4fe97c9253 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 30 Jul 2026 13:01:19 +0700
Subject: [PATCH 058/202] Refactor object compilation to traverse model members

---
 mcdc/code_factory/python_objects_compiler.py |  18 ++--
 mcdc/object_/base.py                         |  77 ++++++++++++--
 mcdc/object_/distribution.py                 |  31 ------
 mcdc/object_/electron_reaction.py            |  28 -----
 mcdc/object_/material.py                     |  25 +++--
 mcdc/object_/neutron_reaction.py             |  21 ----
 mcdc/object_/simulation.py                   |  10 +-
 mcdc/object_/source.py                       |  11 --
 mcdc/object_/surface.py                      |   7 --
 mcdc/object_/universe.py                     |  11 --
 test/unit/test_object_compilation.py         | 101 +++++++++++++++++++
 11 files changed, 203 insertions(+), 137 deletions(-)
 create mode 100644 test/unit/test_object_compilation.py

diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index 97367e620..0b7aff469 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -21,8 +21,16 @@
 
 
 def compile_simulation(simulation: Simulation):
+    # Preserve explicitly configured roots before resetting their registered
+    # object lists. Geometry members may reference these objects and compile
+    # them while the model graph is traversed.
+    sources = simulation.sources
+    tallies = simulation.tallies
+
     # Reset model
     simulation._reset_model()
+    simulation.sources = []
+    simulation.tallies = []
 
     # Reserved ojects
     none_data = DataNone()
@@ -37,20 +45,16 @@ def compile_simulation(simulation: Simulation):
     root_universe._compile_into_simulation(simulation)
 
     # Compile source
-    sources = simulation.sources
-    simulation.sources = []
     for source in sources:
         source._compile_into_simulation(simulation)
 
     # Compile tally
-    tallies = simulation.tallies
-    simulation.tallies = []
     for tally in tallies:
         tally._compile_into_simulation(simulation)
 
-    # Compile model objects owned by transport techniques.
-    if simulation.weight_windows.active:
-        simulation.weight_windows.mesh._compile_into_simulation(simulation)
+    # Compile remaining object members, including those owned by embedded
+    # simulation configuration objects such as transport techniques.
+    simulation._compile_members_into_simulation(simulation)
 
     # Apply settings as needed
     settings = simulation.settings
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index 25aa5dd20..ca50a6ef2 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -6,44 +6,96 @@ class MCDCBase:
 
     Subclasses declare a :attr:`label` and type-annotated fields. Assignments to
     annotated fields are checked at runtime so invalid model data is rejected
-    before the simulation is packed for transport.
+    before the simulation is packed for transport. ``compile_ID`` records the
+    simulation compilation in which an object most recently participated,
+    providing shared recompilation and cycle-prevention behavior for both
+    embedded configuration objects and registered model objects.
     """
 
     label: str
+    compile_ID: int = 0
+    non_numba = ()
 
     def __init_subclass__(cls):
+        # Require metadata used by the object and Numba-layer factories
         if not hasattr(cls, "label"):
             raise NotImplementedError(
                 f"MC/DC class '{cls.__name__}' must have 'label' class attribute."
             )
 
     def __setattr__(self, key, value):
+        # Validate annotated fields before updating the object
         hints = getattr(self.__class__, "__annotations__", {})
         if key in hints and not check_type(value, hints[key], self.__class__, self):
             print_error(f"{key} must be {hints[key]!r}, got {value!r}")
         super().__setattr__(key, value)
 
+    def _compile_into_simulation(self, simulation) -> bool:
+        """Compile an embedded object for the current simulation.
+
+        Embedded ``MCDCBase`` objects participate in compilation without being
+        registered in a simulation object collection. Registered
+        :class:`MCDCObject` subclasses extend this lifecycle with an object ID.
+        """
+        # Compile each embedded object once per simulation compilation
+        if self.compile_ID == simulation.compile_ID:
+            return False
+        self.compile_ID = simulation.compile_ID
+
+        # Compile all members represented in the Numba layer
+        self._compile_members_into_simulation(simulation)
+        return True
+
+    def _compile_members_into_simulation(self, simulation) -> None:
+        """Compile object members represented in the Numba layer.
+
+        ``MCDCObject`` members are registered with ``simulation``. Embedded
+        ``MCDCBase`` members and lists are compiled recursively. Members listed
+        in ``non_numba`` are intentionally left to the owning class because
+        they generally require a custom packed representation.
+        """
+        # Compile members represented in the Numba layer
+        excluded = getattr(self, "non_numba", ())
+        for name, value in vars(self).items():
+            if name in excluded:
+                continue
+            self._compile_member_value(value, simulation)
+
+    @staticmethod
+    def _compile_member_value(value, simulation) -> None:
+        # Register direct object members
+        if isinstance(value, MCDCObject):
+            value._compile_into_simulation(simulation)
+
+        # Compile embedded configuration objects
+        elif isinstance(value, MCDCBase):
+            value._compile_into_simulation(simulation)
+
+        # Compile object members stored in lists
+        elif isinstance(value, list):
+            for item in value:
+                MCDCBase._compile_member_value(item, simulation)
+
 
 class MCDCObject(MCDCBase):
     """Base class for model objects registered during simulation compilation.
 
     ``ID`` identifies an object in its heterogeneous simulation collection.
-    ``compile_ID`` records the compilation pass in which the object was most
-    recently registered, preventing duplicate registration when objects are
-    shared by multiple parts of a model.
+    The inherited ``compile_ID`` prevents duplicate registration when an
+    object is shared by multiple parts of a model.
     """
 
     # MC/DC framework metadata
     label = "object"
 
     ID: int
-    compile_ID: int
 
     def __init__(self):
+        # Initialize the object as unregistered
         self.ID = -1
-        self.compile_ID = 0
 
     def __repr__(self) -> str:
+        # Build the shared object-registration summary
         nice_label = self.label.replace("_", " ").title()
         text = "\n"
         text += f"{nice_label}\n"
@@ -55,7 +107,13 @@ def __repr__(self) -> str:
     def _compile_into_simulation(self, simulation) -> bool:
         from mcdc.code_factory.python_objects_compiler import register_object
 
-        return register_object(self, simulation)
+        # Register once for the current simulation compilation
+        if not register_object(self, simulation):
+            return False
+
+        # Compile all members represented in the Numba layer
+        self._compile_members_into_simulation(simulation)
+        return True
 
 
 class MCDCPolymorphic(MCDCObject):
@@ -73,19 +131,24 @@ class MCDCPolymorphic(MCDCObject):
     sub_ID: int
 
     def __init_subclass__(cls):
+        # Apply the common object metadata requirements
         super().__init_subclass__()
 
+        # Require the code used for polymorphic Numba dispatch
         if not hasattr(cls, "sub_type"):
             raise NotImplementedError(
                 f"MC/DC class '{cls.__name__}' must have 'sub_type' class attribute."
             )
 
     def __init__(self):
+        # Initialize common object registration state
         super().__init__()
 
+        # Initialize the object as unregistered within its subtype
         self.sub_ID = -1
 
     def __repr__(self) -> str:
+        # Build the shared polymorphic registration summary
         nice_label = self.label.replace("_", " ").title()
         text = "\n"
         text += f"{nice_label}\n"
diff --git a/mcdc/object_/distribution.py b/mcdc/object_/distribution.py
index 1837e0bf6..ca9adbc73 100644
--- a/mcdc/object_/distribution.py
+++ b/mcdc/object_/distribution.py
@@ -177,12 +177,6 @@ def __init__(
             aux=cdf_normalized,
         )
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        self.pdf._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self) -> str:
         text = super().__repr__()
 
@@ -292,13 +286,6 @@ def __init__(
 
             self.tables.append(table)
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        for table in self.tables:
-            table._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self) -> str:
         text = super().__repr__()
 
@@ -379,12 +366,6 @@ def __init__(
             interpolation_boundaries,
         )
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        self.nuclear_temperature._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self) -> str:
         text = super().__repr__()
 
@@ -433,12 +414,6 @@ def __init__(
             interpolation_boundaries,
         )
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        self.nuclear_temperature._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self) -> str:
         text = super().__repr__()
 
@@ -668,12 +643,6 @@ def __init__(
             aux=cdf_normalized,
         )
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        self.pdf._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self) -> str:
         text = super().__repr__()
 
diff --git a/mcdc/object_/electron_reaction.py b/mcdc/object_/electron_reaction.py
index 43765a04a..804605c65 100644
--- a/mcdc/object_/electron_reaction.py
+++ b/mcdc/object_/electron_reaction.py
@@ -151,15 +151,6 @@ def from_h5_group(cls, h5_group):
             subshell_product,
         )
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        for subshell_xs in self.subshell_xs:
-            subshell_xs._compile_into_simulation(simulation)
-        for subshell_product in self.subshell_product:
-            subshell_product._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Number of subshells: {self.N_subshell}\n"
@@ -229,13 +220,6 @@ def from_h5_group(cls, h5_group):
 
         return cls(MT, xs, xs_offset, reference_frame, xs_large, mu)
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        self.xs_large._compile_into_simulation(simulation)
-        self.mu._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Mu cut: {self.mu_cut}\n"
@@ -272,12 +256,6 @@ def from_h5_group(cls, h5_group):
 
         return cls(MT, xs, xs_offset, reference_frame, eloss)
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        self.eloss._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Energy loss: DataTable [ID: {self.eloss.ID}]\n"
@@ -312,12 +290,6 @@ def from_h5_group(cls, h5_group):
 
         return cls(MT, xs, xs_offset, reference_frame, eloss)
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        self.eloss._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Energy loss: DataTable [ID: {self.eloss.ID}]\n"
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 8e00e6c95..dda0762b5 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -164,31 +164,29 @@ def __init__(
         )
 
     def _compile_into_simulation(self, simulation) -> bool:
-        """Resolve and register composition objects with the owning simulation."""
-        if not super()._compile_into_simulation(simulation):
+        """Canonicalize the composition and register it with the simulation."""
+        # Skip composition work when this material is already compiled
+        if self.compile_ID == simulation.compile_ID:
             return False
 
+        # Resolve composition objects before generic member traversal so only
+        # canonical simulation objects are registered.
         nuclide_composition = {}
         element_composition = {}
-        self.fissionable = False
 
-        # Replace locally created elements with canonical simulation objects.
+        # Replace locally created elements with canonical simulation objects
         for element, density in self.element_composition.items():
             element = _get_or_create_element(element.name, simulation, element)
-            element._compile_into_simulation(simulation)
             element_composition[element] = density
 
-        # Replace locally created nuclides with canonical simulation objects.
+        # Replace locally created nuclides with canonical simulation objects
         for nuclide, density in self.nuclide_composition.items():
             nuclide = _get_or_create_nuclide(
                 nuclide.name, nuclide.temperature, simulation, nuclide
             )
-            nuclide._compile_into_simulation(simulation)
             nuclide_composition[nuclide] = density
 
-            if nuclide.fissionable:
-                self.fissionable = True
-
+        # Synchronize the packed composition fields with the canonical objects
         self.nuclide_composition = nuclide_composition
         self.element_composition = element_composition
         self.nuclides = list(nuclide_composition)
@@ -200,6 +198,13 @@ def _compile_into_simulation(self, simulation) -> bool:
             list(element_composition.values()), dtype=float
         )
 
+        # Register the material and compile its canonical composition members
+        if not super()._compile_into_simulation(simulation):
+            return False
+
+        # Resolve derived properties after nuclide library data has been loaded
+        self.fissionable = any(nuclide.fissionable for nuclide in self.nuclides)
+
         return True
 
     def __repr__(self):
diff --git a/mcdc/object_/neutron_reaction.py b/mcdc/object_/neutron_reaction.py
index 1fdb672d9..6e1dc87a3 100644
--- a/mcdc/object_/neutron_reaction.py
+++ b/mcdc/object_/neutron_reaction.py
@@ -108,12 +108,6 @@ def from_h5_group(cls, h5_group, simulation):
         )
         return cls(MT, xs, xs_offset, reference_frame, mu)
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        self.mu_table._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Scattering cosine: {distribution.decode_type(self.mu_table.type)} [ID: {self.mu_table.ID}]\n"
@@ -224,14 +218,6 @@ def from_h5_group(cls, h5_group, simulation):
             energy_spectra,
         )
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        self.mu._compile_into_simulation(simulation)
-        for spectrum in self.energy_spectra:
-            spectrum._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self):
         text = super().__repr__()
         if self.angle_type == ANGLE_ISOTROPIC:
@@ -299,13 +285,6 @@ def from_h5_group(cls, h5_group, simulation):
             MT, xs, xs_offset, reference_frame, q_value, angle_type, mu, spectrum
         )
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        if not super()._compile_into_simulation(simulation):
-            return False
-        self.mu._compile_into_simulation(simulation)
-        self.spectrum._compile_into_simulation(simulation)
-        return True
-
     def __repr__(self):
         text = super().__repr__()
         text += f"  - Prompt neutron\n"
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 2bf7ed5c6..89495480a 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -139,7 +139,6 @@ class Simulation(MCDCBase):
     non_numba = [
         "_next_compile_ID",
         "compiled",
-        "compile_ID",
         "regions",
         "root_universe",
         "bank_active",
@@ -151,7 +150,6 @@ class Simulation(MCDCBase):
 
     # Basic parameters
     name: str
-    compile_ID: int  # Non-Numba
     compiled: bool  # Non-Numba
 
     # Physics
@@ -243,7 +241,6 @@ class Simulation(MCDCBase):
     source_seed: int
 
     def __init__(self, name: str = "") -> None:
-        self.compile_ID = 0
         self.compiled = False
 
         self.name = name or "(Unnamed simulation)"
@@ -374,7 +371,12 @@ def set_tallies(self, tallies: Sequence[Tally]) -> None:
     # ==================================================================================
 
     def compile(self) -> None:
-        """Compile the Python object graph into registered simulation objects."""
+        """Compile the Python object graph into a new simulation snapshot.
+
+        A globally unique ``compile_ID`` identifies the snapshot. Every
+        embedded or registered :class:`~mcdc.object_.base.MCDCBase` reached
+        during compilation records that ID.
+        """
         from mcdc.code_factory.python_objects_compiler import compile_simulation
 
         self.compile_ID = type(self)._next_compile_ID
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 8356902c6..8b4b513b1 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -373,17 +373,6 @@ def __init__(
         self.move_time_grid = np.array([0.0, INF])
         self.move_translations = np.zeros((2, 3))
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        # Already compiled?
-        if not super()._compile_into_simulation(simulation):
-            return False
-
-        # Compile distributions
-        self.energy_group_pmf._compile_into_simulation(simulation)
-        self.energy_pdf._compile_into_simulation(simulation)
-
-        return True
-
     def __repr__(self):
         text = super().__repr__()
 
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index cdda32d53..261fee5b1 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -180,13 +180,6 @@ def __init__(self, type_, name, boundary_condition):
         # Surface-crossing tallies
         self.surface_crossing_tallies = []
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        # Already compiled?
-        if not super()._compile_into_simulation(simulation):
-            return False
-
-        return True
-
     def __repr__(self):
         text = super().__repr__()
 
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index d30b2d98a..0252af10c 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -80,17 +80,6 @@ def __init__(self, name: str = "", cells: list[Cell] = []):
         self.name = name or "(Unnamed universe)"
         self.cells = cells
 
-    def _compile_into_simulation(self, simulation) -> bool:
-        # Already compiled?
-        if not super()._compile_into_simulation(simulation):
-            return False
-
-        # Compile cells
-        for cell in self.cells:
-            cell._compile_into_simulation(simulation)
-
-        return True
-
     def __repr__(self):
         text = super().__repr__()
 
diff --git a/test/unit/test_object_compilation.py b/test/unit/test_object_compilation.py
new file mode 100644
index 000000000..3f44408df
--- /dev/null
+++ b/test/unit/test_object_compilation.py
@@ -0,0 +1,101 @@
+import numpy as np
+
+import mcdc
+
+from mcdc.object_.base import MCDCBase, MCDCObject
+from mcdc.object_.data import DataPolynomial
+from mcdc.object_.nuclide import Nuclide
+from mcdc.object_.universe import Universe
+
+
+class ObjectOwner(Universe):
+    child: DataPolynomial
+    children: list[DataPolynomial]
+    ignored: DataPolynomial
+
+    non_numba = ["ignored"]
+
+    def __init__(self, child, children, ignored):
+        super().__init__()
+        self.child = child
+        self.children = children
+        self.ignored = ignored
+
+
+class EmbeddedConfiguration(MCDCBase):
+    label = "embedded_configuration"
+
+    def __init__(self):
+        self.member = None
+
+
+def test_mcdc_object_compiles_object_members_and_lists():
+    child = DataPolynomial(np.array([1.0]))
+    children = [
+        DataPolynomial(np.array([2.0])),
+        DataPolynomial(np.array([3.0])),
+    ]
+    ignored = DataPolynomial(np.array([4.0]))
+    simulation = mcdc.Simulation()
+    simulation.root_universe = ObjectOwner(child, children, ignored)
+
+    simulation.compile()
+
+    assert simulation.data[1:] == [child, *children]
+    assert ignored.compile_ID == 0
+
+
+def test_simulation_compiles_objects_owned_by_embedded_configuration():
+    mesh = mcdc.MeshUniform()
+    weight_windows = np.ones((1, 1, 1, 1, 3))
+    simulation = mcdc.Simulation()
+    simulation.weight_windows(weight_windows, mesh=mesh)
+
+    simulation.compile()
+
+    assert simulation.meshes == [mesh]
+    assert simulation.weight_windows.compile_ID == simulation.compile_ID
+
+
+def test_embedded_compile_id_prevents_cycles_and_supports_recompilation():
+    configuration_a = EmbeddedConfiguration()
+    configuration_b = EmbeddedConfiguration()
+    configuration_a.member = configuration_b
+    configuration_b.member = configuration_a
+    simulation = mcdc.Simulation()
+    simulation.configuration = configuration_a
+
+    simulation.compile()
+    first_compile_ID = simulation.compile_ID
+
+    assert configuration_a.compile_ID == first_compile_ID
+    assert configuration_b.compile_ID == first_compile_ID
+
+    simulation.compile()
+
+    assert simulation.compile_ID != first_compile_ID
+    assert configuration_a.compile_ID == simulation.compile_ID
+    assert configuration_b.compile_ID == simulation.compile_ID
+
+
+def test_material_canonicalizes_composition_before_member_compilation(monkeypatch):
+    # Replace library loading with the minimal state needed for this unit test
+    def compile_nuclide(nuclide, simulation):
+        nuclide.fissionable = nuclide.name == "U235"
+        return MCDCObject._compile_into_simulation(nuclide, simulation)
+
+    monkeypatch.setattr(Nuclide, "_compile_into_simulation", compile_nuclide)
+
+    material_a = mcdc.Material(nuclide_composition={"U235": 1.0})
+    material_b = mcdc.Material(nuclide_composition={"U235": 2.0})
+    simulation = mcdc.Simulation()
+    simulation.compile()
+
+    material_a._compile_into_simulation(simulation)
+    material_b._compile_into_simulation(simulation)
+
+    assert len(simulation.nuclides) == 1
+    assert material_a.nuclides == simulation.nuclides
+    assert material_b.nuclides == simulation.nuclides
+    assert material_a.fissionable
+    assert material_b.fissionable

From 5af659506227c2b92d62bd2f3a03e1f504dfdb55 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 30 Jul 2026 13:45:40 +0700
Subject: [PATCH 059/202] update Python API docs

---
 README.md                       |   2 +-
 docs/source/index.rst           |   2 +-
 docs/source/pythonapi/index.rst | 134 +++++++++++++++++++-------------
 3 files changed, 83 insertions(+), 55 deletions(-)

diff --git a/README.md b/README.md
index b88b7588a..c4d4000ff 100644
--- a/README.md
+++ b/README.md
@@ -45,7 +45,7 @@ Complete documentation is available on
 
 - [Installation](https://mcdc.readthedocs.io/en/latest/install.html)
 - [User Guide](https://mcdc.readthedocs.io/en/latest/user/index.html)
-- [API Reference](https://mcdc.readthedocs.io/en/latest/pythonapi/index.html)
+- [Python API Reference](https://mcdc.readthedocs.io/en/latest/pythonapi/index.html)
 - [Contribution Guide](https://mcdc.readthedocs.io/en/latest/contribution/index.html)
 
 ## Citing
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 8a908ff7f..337bf0d30 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -71,7 +71,7 @@ Contents
 
    install
    user/index
-   pythonapi/index
+   Python API Reference <pythonapi/index>
    examples/index
 
 .. toctree::
diff --git a/docs/source/pythonapi/index.rst b/docs/source/pythonapi/index.rst
index 57b28006a..19dd0af87 100644
--- a/docs/source/pythonapi/index.rst
+++ b/docs/source/pythonapi/index.rst
@@ -1,50 +1,80 @@
 .. _pythonapi:
 
-================
-Input Definition
-================
+====================
+Python API Reference
+====================
 
-Full API documentation.
+The MC/DC public API is centered on :class:`mcdc.Simulation`. A simulation owns
+the model geometry and material, sources, tallies, settings, transport
+techniques, and runtime state needed for one calculation.
 
+Build the model with the public objects listed below, attach its root cells,
+sources, and tallies to a simulation, and then visualize or run that simulation:
 
-Defining materials
-------------------
+.. code-block:: python
+
+   simulation = mcdc.Simulation(name="Example")
+   simulation.set_model([cell])
+   simulation.set_sources([source])
+   simulation.set_tallies([tally])
+   simulation.settings.N_particle = 10_000
+   simulation.run()
+
+The complete public interfaces and additional examples are documented on each
+linked API page.
+
+
+Simulation
+----------
 
 .. autosummary::
    :toctree: generated
    :nosignatures:
    :template: omcclass.rst
 
-   mcdc.Material
-   mcdc.MaterialMG
+   mcdc.Simulation
+
 
+Model building blocks
+---------------------
 
-Defining geometry
------------------
+Materials
+^^^^^^^^^
+
+Materials define the interaction data used by cells. Use
+:class:`mcdc.Material` for continuous-energy transport and
+:class:`mcdc.MaterialMG` for multigroup transport.
 
 .. autosummary::
    :toctree: generated
    :nosignatures:
    :template: omcclass.rst
 
-   mcdc.Cell
-   mcdc.Lattice
-   mcdc.Surface
-   mcdc.Universe
+   mcdc.Material
+   mcdc.MaterialMG
 
-Defining meshes
----------------
+
+Geometry
+^^^^^^^^
+
+Surfaces bound spatial regions, cells pair those regions with materials or
+universes, and universes and lattices organize repeated geometry.
 
 .. autosummary::
    :toctree: generated
    :nosignatures:
    :template: omcclass.rst
 
-   mcdc.MeshUniform
-   mcdc.MeshStructured
+   mcdc.Surface
+   mcdc.Cell
+   mcdc.Universe
+   mcdc.Lattice
+
 
-Defining sources
-----------------
+Sources
+^^^^^^^
+
+Sources describe the initial particle population.
 
 .. autosummary::
    :toctree: generated
@@ -53,8 +83,12 @@ Defining sources
 
    mcdc.Source
 
-Defining tallies
-----------------
+
+Tallies
+^^^^^^^
+
+Tallies define the quantities to score and the filters over which those scores
+are accumulated.
 
 .. autosummary::
    :toctree: generated
@@ -63,48 +97,42 @@ Defining tallies
 
    mcdc.Tally
 
-Defining simulation settings
------------------------------
-
-Settings are configured by assigning attributes on the ``mcdc.settings`` singleton.
-Key attributes include:
 
-- ``mcdc.settings.N_particle`` — Number of particles.
-- ``mcdc.settings.N_batch`` — Number of batches.
-- ``mcdc.settings.rng_seed`` — RNG seed.
-- ``mcdc.settings.output_name`` — Output file name (default: ``"output"``).
-- ``mcdc.settings.time_boundary`` — Time boundary.
+Meshes
+^^^^^^
 
-Methods:
-
-- ``mcdc.settings.set_eigenmode(N_inactive=..., N_active=..., k_init=...)`` — Enable k-eigenvalue mode.
-- ``mcdc.settings.set_time_census(time, tally_frequency=...)`` — Set time census parameters.
-- ``mcdc.settings.set_source_file(source_file_name)`` — Load source particles from file.
-
-Defining techniques
--------------------
-
-Techniques are enabled by calling methods on the ``mcdc.simulation`` singleton:
-
-- ``mcdc.simulation.implicit_capture(active=True)``
-- ``mcdc.simulation.global_weight_roulette(weight_threshold=0.0, weight_target=1.0)``
-- ``mcdc.simulation.population_control(active=True)``
-- ``mcdc.simulation.weighted_emission(active=True, weight_target=1.0)``
-- ``mcdc.simulation.weight_windows(weight_windows, mesh=None, energy=None)``
-
-Running simulations
--------------------
+Meshes provide spatial bins for mesh-filtered tallies and transport
+techniques.
 
 .. autosummary::
    :toctree: generated
    :nosignatures:
    :template: omcclass.rst
 
-   mcdc.Simulation
-
+   mcdc.MeshUniform
+   mcdc.MeshStructured
 
 
+Configuration and execution
+---------------------------
 
+Each :class:`mcdc.Simulation` owns its settings at ``simulation.settings``.
+Settings control particle histories, batches, random-number generation,
+transport modes, census times, particle banks, output, and GPU execution.
+Specialized modes are configured through methods such as
+``simulation.settings.set_eigenmode(...)`` and
+``simulation.settings.set_time_census(...)``.
 
+Transport techniques are also configured on the simulation instance:
 
+- ``simulation.implicit_capture(...)``
+- ``simulation.weighted_emission(...)``
+- ``simulation.global_weight_roulette(...)``
+- ``simulation.weight_windows(...)``
+- ``simulation.population_control(...)``
 
+Calling ``simulation.run()`` compiles the current Python object graph when
+needed, executes particle transport, and writes the configured output.
+``simulation.visualize_model(...)`` similarly compiles when needed before
+rendering the model. Use ``simulation.compile()`` when an explicit compiled
+snapshot is required before either operation.

From 70a3aa7a2fe67e075e813cbd7749ebdb325239d8 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 30 Jul 2026 15:38:29 +0700
Subject: [PATCH 060/202] update python API docs

---
 docs/source/_ext/simulation_members.py     | 178 +++++++++++++++++++++
 docs/source/_static/custom.css             |   5 +
 docs/source/_templates/simulationclass.rst |   9 ++
 docs/source/conf.py                        |   4 +
 docs/source/pythonapi/index.rst            |  21 ++-
 mcdc/object_/settings.py                   |  90 +++++++++--
 mcdc/object_/simulation.py                 | 148 +++++++++--------
 mcdc/object_/technique.py                  | 123 ++++++++++++--
 8 files changed, 481 insertions(+), 97 deletions(-)
 create mode 100644 docs/source/_ext/simulation_members.py
 create mode 100644 docs/source/_templates/simulationclass.rst

diff --git a/docs/source/_ext/simulation_members.py b/docs/source/_ext/simulation_members.py
new file mode 100644
index 000000000..abedab80c
--- /dev/null
+++ b/docs/source/_ext/simulation_members.py
@@ -0,0 +1,178 @@
+"""Sphinx directive for documenting Simulation-owned configuration interfaces."""
+
+from __future__ import annotations
+
+import inspect
+from dataclasses import fields
+
+from docutils import nodes
+from docutils.statemachine import ViewList
+from sphinx.ext.napoleon.docstring import NumpyDocstring
+from sphinx.pycode import ModuleAnalyzer
+from sphinx.util.docutils import SphinxDirective
+
+from mcdc.object_.settings import Settings
+from mcdc.object_.technique import (
+    GlobalWeightRoulette,
+    ImplicitCapture,
+    PopulationControl,
+    WeightedEmission,
+    WeightWindows,
+)
+
+DIRECT_SETTINGS = (
+    "N_particle",
+    "N_batch",
+    "rng_seed",
+    "time_boundary",
+    "output_name",
+    "use_progress_bar",
+    "active_bank_buffer",
+    "census_bank_buffer_ratio",
+    "source_bank_buffer_ratio",
+    "future_bank_buffer_ratio",
+)
+
+SETTINGS_METHODS = (
+    "set_time_census",
+    "set_eigenmode",
+    "set_source_file",
+    "set_transported_particles",
+)
+
+TECHNIQUES = (
+    ("implicit_capture", ImplicitCapture),
+    ("weighted_emission", WeightedEmission),
+    ("global_weight_roulette", GlobalWeightRoulette),
+    ("weight_windows", WeightWindows),
+    ("population_control", PopulationControl),
+)
+
+
+def setup(app):
+    app.add_directive("simulation-members", SimulationMembersDirective)
+    return {
+        "parallel_read_safe": True,
+        "parallel_write_safe": True,
+    }
+
+
+class SimulationMembersDirective(SphinxDirective):
+    """Render internal configuration docstrings as public Simulation members."""
+
+    has_content = False
+
+    def run(self):
+        lines = ViewList()
+        settings_fields = {field.name: field for field in fields(Settings)}
+        attribute_docs = ModuleAnalyzer.for_module(Settings.__module__).find_attr_docs()
+
+        _append_line(lines, ".. rubric:: Settings")
+        _append_line(lines)
+
+        for name in DIRECT_SETTINGS:
+            field = settings_fields[name]
+            _append_line(lines, f".. py:attribute:: settings.{name}")
+            _append_line(lines, "   :module:")
+            _append_line(
+                lines,
+                f"   :canonical: mcdc.Simulation.settings.{name}",
+            )
+            _append_line(lines, f"   :type: {_public_type(field.type)}")
+            _append_line(lines, f"   :value: {field.default!r}")
+            _append_line(lines)
+            _append_content(
+                lines,
+                attribute_docs[("Settings", name)],
+                indent="   ",
+            )
+            _append_line(lines)
+
+        for name in SETTINGS_METHODS:
+            method = getattr(Settings, name)
+            public_name = f"Simulation.settings.{name}"
+            _append_line(
+                lines,
+                f".. py:method:: settings.{name}{_public_signature(method)}",
+            )
+            _append_line(lines, "   :module:")
+            _append_line(
+                lines,
+                f"   :canonical: mcdc.Simulation.settings.{name}",
+            )
+            _append_line(lines)
+            _append_content(
+                lines,
+                _converted_docstring(self, method, public_name),
+                indent="   ",
+            )
+            _append_line(lines)
+
+        _append_line(lines, ".. rubric:: Transport techniques")
+        _append_line(lines)
+
+        for name, technique in TECHNIQUES:
+            method = technique.__call__
+            public_name = f"Simulation.{name}"
+            _append_line(
+                lines,
+                f".. py:method:: {name}{_public_signature(method)}",
+            )
+            _append_line(lines, "   :module:")
+            _append_line(
+                lines,
+                f"   :canonical: mcdc.Simulation.{name}",
+            )
+            _append_line(lines)
+            _append_content(
+                lines,
+                _converted_docstring(self, method, public_name),
+                indent="   ",
+            )
+            _append_line(lines)
+
+        container = nodes.container(classes=["simulation-members"])
+        self.state.nested_parse(lines, self.content_offset, container)
+        return [container]
+
+
+def _append_line(lines: ViewList, line: str = "") -> None:
+    lines.append(line, "<simulation-members>")
+
+
+def _append_content(lines: ViewList, content: list[str], indent: str = "") -> None:
+    for line in content:
+        _append_line(lines, f"{indent}{line}" if line else "")
+
+
+def _converted_docstring(
+    directive: SphinxDirective, obj, public_name: str
+) -> list[str]:
+    docstring = inspect.getdoc(obj) or ""
+    return str(
+        NumpyDocstring(
+            docstring,
+            config=directive.env.config,
+            app=directive.env.app,
+            what="method",
+            name=public_name,
+            obj=obj,
+        )
+    ).splitlines()
+
+
+def _public_signature(function) -> str:
+    signature = inspect.signature(function)
+    parameters = tuple(signature.parameters.values())[1:]
+    return str(
+        signature.replace(
+            parameters=parameters,
+            return_annotation=inspect.Signature.empty,
+        )
+    )
+
+
+def _public_type(annotation) -> str:
+    if isinstance(annotation, type):
+        return annotation.__name__
+    return str(annotation).removeprefix("typing.")
diff --git a/docs/source/_static/custom.css b/docs/source/_static/custom.css
index 67b0574f9..025e49129 100644
--- a/docs/source/_static/custom.css
+++ b/docs/source/_static/custom.css
@@ -5,6 +5,11 @@ dt.sig.sig-object.py > em.property {
     display: none;
 }
 
+/* Align Simulation-owned settings and techniques with regular class members. */
+.simulation-members {
+    margin-left: 30px;
+}
+
 /* Container styling */
 .admonition.tip {
     border-left: 5px solid #ffde57; /* Python Yellow border */
diff --git a/docs/source/_templates/simulationclass.rst b/docs/source/_templates/simulationclass.rst
new file mode 100644
index 000000000..d38c66ab9
--- /dev/null
+++ b/docs/source/_templates/simulationclass.rst
@@ -0,0 +1,9 @@
+{{ fullname | escape | underline}}
+
+.. currentmodule:: {{ module }}
+
+.. autoclass:: {{ objname }}
+   :members:
+   :no-special-members:
+
+.. simulation-members::
diff --git a/docs/source/conf.py b/docs/source/conf.py
index 63c0d3f9b..7cbd2f32f 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -18,6 +18,9 @@
 PROJECT_ROOT = os.path.abspath(os.path.join(HERE, "..", ".."))
 if PROJECT_ROOT not in sys.path:
     sys.path.insert(0, PROJECT_ROOT)
+EXTENSIONS_ROOT = os.path.join(HERE, "_ext")
+if EXTENSIONS_ROOT not in sys.path:
+    sys.path.insert(0, EXTENSIONS_ROOT)
 
 # -- Project information -----------------------------------------------------
 project = "MC/DC"
@@ -40,6 +43,7 @@
     "sphinx_toolbox.github",
     "sphinx_toolbox.sidebar_links",
     "sphinx.ext.autosectionlabel",
+    "simulation_members",
 ]
 autosummary_generate = True
 autosectionlabel_prefix_document = True
diff --git a/docs/source/pythonapi/index.rst b/docs/source/pythonapi/index.rst
index 19dd0af87..c59fd01b8 100644
--- a/docs/source/pythonapi/index.rst
+++ b/docs/source/pythonapi/index.rst
@@ -30,7 +30,7 @@ Simulation
 .. autosummary::
    :toctree: generated
    :nosignatures:
-   :template: omcclass.rst
+   :template: simulationclass.rst
 
    mcdc.Simulation
 
@@ -116,20 +116,25 @@ techniques.
 Configuration and execution
 ---------------------------
 
+Simulation settings
+^^^^^^^^^^^^^^^^^^^
+
 Each :class:`mcdc.Simulation` owns its settings at ``simulation.settings``.
 Settings control particle histories, batches, random-number generation,
 transport modes, census times, particle banks, output, and GPU execution.
 Specialized modes are configured through methods such as
 ``simulation.settings.set_eigenmode(...)`` and
-``simulation.settings.set_time_census(...)``.
+``simulation.settings.set_time_census(...)``. See :class:`mcdc.Simulation` for
+the complete settings interface.
+
+Transport techniques
+^^^^^^^^^^^^^^^^^^^^
 
-Transport techniques are also configured on the simulation instance:
+Transport techniques are configured directly on the simulation instance. See
+:class:`mcdc.Simulation` for their signatures and examples.
 
-- ``simulation.implicit_capture(...)``
-- ``simulation.weighted_emission(...)``
-- ``simulation.global_weight_roulette(...)``
-- ``simulation.weight_windows(...)``
-- ``simulation.population_control(...)``
+Compiling and running
+^^^^^^^^^^^^^^^^^^^^^
 
 Calling ``simulation.run()`` compiles the current Python object graph when
 needed, executes particle transport, and writes the configured output.
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index fcba8d895..7b6421e90 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -19,20 +19,20 @@
 
 @dataclass
 class Settings(MCDCBase):
-    """Simulation controls compiled into the transport state.
-
-    Settings are owned by a :class:`~mcdc.object_.simulation.Simulation` and
-    configure histories, batches, random-number generation, time censuses,
-    eigenvalue mode, transported particle species, output, particle banks, and
-    GPU execution.
-    """
+    """Execution and transport settings owned by a simulation."""
 
     # MC/DC framework metadata
     label = "settings"
 
     # Basic
+    #: Number of particle histories simulated per batch or eigenvalue cycle.
+    #: The default is ``0``.
     N_particle: int = 0
+    #: Number of statistically independent fixed-source batches. The default
+    #: is ``1``.
     N_batch: int = 1
+    #: Seed used to initialize the pseudorandom-number generator. The default
+    #: is ``1``.
     rng_seed: int = 1
 
     # k-eigenvalue
@@ -48,8 +48,12 @@ class Settings(MCDCBase):
     source_file_name: str = ""
 
     # Misc.
+    #: Time in seconds at which particle transport terminates. The default is
+    #: infinity.
     time_boundary: float = np.inf
+    #: Base name used for the HDF5 output file. The default is ``"output"``.
     output_name: str = "output"
+    #: Whether to display transport progress. The default is ``True``.
     use_progress_bar: bool = True
 
     # Time census
@@ -60,9 +64,17 @@ class Settings(MCDCBase):
 
     # Particle bank-related
     save_particle: bool = False
+    #: Additional particle capacity allocated for the active bank. The default
+    #: is ``100``.
     active_bank_buffer: int = 100
+    #: Capacity multiplier used when allocating the census bank. The default
+    #: is ``2.0``.
     census_bank_buffer_ratio: float = 2.0
+    #: Capacity multiplier used when allocating the source bank. The default
+    #: is ``2.0``.
     source_bank_buffer_ratio: float = 2.0
+    #: Capacity multiplier used when allocating the future bank. The default
+    #: is ``1.5``.
     future_bank_buffer_ratio: float = 1.5
 
     # Multi-particle options
@@ -88,8 +100,25 @@ def set_time_census(self, time, tally_frequency=None):
             Positive, nondecreasing census times in seconds. An infinite final
             census is appended automatically.
         tally_frequency : int, optional
-            Number of tally intervals per census period. A positive value enables
-            census-based tally output.
+            Number of tally intervals per census period. A positive value
+            enables census-based tally output.
+
+        Examples
+        --------
+        Configure explicit census times:
+
+        >>> import mcdc
+        >>> simulation = mcdc.Simulation()
+        >>> simulation.settings.set_time_census(
+        ...     time=[1.0e-6, 2.0e-6, 5.0e-6],
+        ... )
+
+        Enable census-based tallies with ten intervals per census period:
+
+        >>> simulation.settings.set_time_census(
+        ...     time=[1.0e-6, 2.0e-6, 5.0e-6],
+        ...     tally_frequency=10,
+        ... )
         """
         # Make sure that the time grid points are sorted
         if not is_sorted(time):
@@ -136,6 +165,27 @@ def set_eigenmode(
             or ``"only-z"``.
         save_particle : bool, optional
             Whether to save source-bank particles.
+
+        Examples
+        --------
+        Configure a standard eigenvalue calculation:
+
+        >>> import mcdc
+        >>> simulation = mcdc.Simulation()
+        >>> simulation.settings.set_eigenmode(
+        ...     N_inactive=20,
+        ...     N_active=100,
+        ...     k_init=1.0,
+        ... )
+
+        Score the source gyration radius and save source particles:
+
+        >>> simulation.settings.set_eigenmode(
+        ...     N_inactive=20,
+        ...     N_active=100,
+        ...     gyration_radius="all",
+        ...     save_particle=True,
+        ... )
         """
         # Update setting self
         self.N_inactive = N_inactive
@@ -174,6 +224,14 @@ def set_source_file(self, source_file_name):
         ----------
         source_file_name : str or path-like
             Source-particle HDF5 file.
+
+        Examples
+        --------
+        Initialize a simulation from a previously written particle source:
+
+        >>> import mcdc
+        >>> simulation = mcdc.Simulation()
+        >>> simulation.settings.set_source_file("source.h5")
         """
         self.use_source_file = True
         self.source_file_name = source_file_name
@@ -189,6 +247,20 @@ def set_transported_particles(self, transported_particles: List[str]):
         ----------
         transported_particles : list of {"neutron", "electron", "proton"}
             Particle species to enable. Species not listed are disabled.
+
+        Examples
+        --------
+        Transport neutrons only:
+
+        >>> import mcdc
+        >>> simulation = mcdc.Simulation()
+        >>> simulation.settings.set_transported_particles(["neutron"])
+
+        Enable coupled neutron and electron transport:
+
+        >>> simulation.settings.set_transported_particles(
+        ...     ["neutron", "electron"],
+        ... )
         """
         # Reset the flags
         self.neutron_transport = False
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 89495480a..051e431af 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -60,78 +60,26 @@ class Simulation(MCDCBase):
     resulting object graph, assigns IDs, and prepares it for conversion to the
     packed arrays consumed by :mod:`mcdc.transport`.
 
+    Each simulation owns its execution settings. Access them through
+    ``simulation.settings`` by assigning values such as
+    :attr:`settings.N_particle <mcdc.Simulation.settings.N_particle>` or by
+    calling configuration methods such as
+    :meth:`settings.set_eigenmode <mcdc.Simulation.settings.set_eigenmode>`.
+
+    Transport techniques are configured directly on the simulation through
+    methods such as :meth:`implicit_capture <mcdc.Simulation.implicit_capture>`
+    and :meth:`weight_windows <mcdc.Simulation.weight_windows>`.
+
     Examples
     --------
-    Assemble a minimal one-group slab simulation:
+    Configure commonly adjusted settings:
 
-    >>> import numpy as np
     >>> import mcdc
-    >>> material = mcdc.MaterialMG(capture=np.array([1.0]))
-    >>> left = mcdc.Surface.PlaneX(x=0.0, boundary_condition="vacuum")
-    >>> right = mcdc.Surface.PlaneX(x=1.0, boundary_condition="vacuum")
-    >>> cell = mcdc.Cell(region=+left & -right, fill=material)
-    >>> source = mcdc.Source(x=[0.0, 1.0], isotropic=True, energy_group=0)
-    >>> tally = mcdc.Tally(cell=cell, scores=["flux"])
     >>> simulation = mcdc.Simulation(name="Slab")
-    >>> simulation.set_model([cell])
-    >>> simulation.set_sources([source])
-    >>> simulation.set_tallies([tally])
-    >>> simulation.settings.N_particle = 1_000
-
-    Visualize an x-z slice of the model:
-
-    >>> simulation.visualize_model(
-    ...     vis_plane="xz",
-    ...     x=[0.0, 1.0],
-    ...     y=0.0,
-    ...     z=[-0.5, 0.5],
-    ...     pixels=(100, 100),
-    ...     colors=None,
-    ...     time=[0.0],
-    ...     save_as="slab",
-    ... )
-
-    Run particle transport and write the configured output:
-
-    >>> simulation.run()
-
-    Configure a time-dependent calculation with census times:
-
-    >>> transient = mcdc.Simulation(name="Transient slab")
-    >>> transient.set_model([cell])
-    >>> transient.set_sources([source])
-    >>> transient.set_tallies([tally])
-    >>> transient.settings.N_particle = 10_000
-    >>> transient.settings.set_time_census(
-    ...     time=[1.0e-6, 2.0e-6, 5.0e-6],
-    ...     tally_frequency=10,
-    ... )
-
-    Configure a k-eigenvalue calculation:
-
-    >>> fuel = mcdc.MaterialMG(
-    ...     capture=np.array([0.10]),
-    ...     fission=np.array([0.20]),
-    ...     nu_p=np.array([2.50]),
-    ... )
-    >>> fuel_cell = mcdc.Cell(region=+left & -right, fill=fuel)
-    >>> eigenvalue = mcdc.Simulation(name="Critical slab")
-    >>> eigenvalue.set_model([fuel_cell])
-    >>> eigenvalue.set_sources([source])
-    >>> eigenvalue.settings.N_particle = 10_000
-    >>> eigenvalue.settings.set_eigenmode(
-    ...     N_inactive=20,
-    ...     N_active=100,
-    ...     k_init=1.0,
-    ... )
-
-    Enable common variance-reduction techniques:
-
-    >>> simulation.implicit_capture()
-    >>> simulation.global_weight_roulette(
-    ...     weight_threshold=0.25,
-    ...     weight_target=1.0,
-    ... )
+    >>> simulation.settings.N_particle = 10_000
+    >>> simulation.settings.N_batch = 20
+    >>> simulation.settings.rng_seed = 12345
+    >>> simulation.settings.output_name = "slab"
     """
 
     # MC/DC framework metadata
@@ -352,17 +300,53 @@ def _reset_model(self) -> None:
     # ==================================================================================
 
     def set_model(self, cells: Sequence[Cell]) -> None:
-        """Set the cells in the root universe and invalidate compiled state."""
+        """Set the cells in the root universe and invalidate compiled state.
+
+        Parameters
+        ----------
+        cells : sequence of Cell
+            Cells to place in the root universe.
+
+        Examples
+        --------
+        Attach previously constructed cells:
+
+        >>> simulation.set_model([fuel_cell, moderator_cell])
+        """
         self.root_universe.cells = list(cells)
         self.compiled = False
 
     def set_sources(self, sources: Sequence[Source]) -> None:
-        """Set particle sources and invalidate compiled state."""
+        """Set particle sources and invalidate compiled state.
+
+        Parameters
+        ----------
+        sources : sequence of Source
+            Particle sources to sample during transport.
+
+        Examples
+        --------
+        Attach previously constructed sources:
+
+        >>> simulation.set_sources([volume_source, boundary_source])
+        """
         self.sources = list(sources)
         self.compiled = False
 
     def set_tallies(self, tallies: Sequence[Tally]) -> None:
-        """Set requested tallies and invalidate compiled state."""
+        """Set requested tallies and invalidate compiled state.
+
+        Parameters
+        ----------
+        tallies : sequence of Tally
+            Tallies to score during transport.
+
+        Examples
+        --------
+        Attach previously constructed tallies:
+
+        >>> simulation.set_tallies([flux_tally, current_tally])
+        """
         self.tallies = list(tallies)
         self.compiled = False
 
@@ -400,6 +384,21 @@ def visualize_model(
 
         Parameters are forwarded to :func:`mcdc.visualize.visualize_model`.
         The model is compiled first when necessary.
+
+        Examples
+        --------
+        Render an x-z slice of the model:
+
+        >>> simulation.visualize_model(
+        ...     vis_plane="xz",
+        ...     x=[0.0, 1.0],
+        ...     y=0.0,
+        ...     z=[-0.5, 0.5],
+        ...     pixels=(100, 100),
+        ...     colors=None,
+        ...     time=[0.0],
+        ...     save_as="slab",
+        ... )
         """
         if not self.compiled:
             self.compile()
@@ -409,7 +408,14 @@ def visualize_model(
         visualize_model(self, vis_plane, x, y, z, pixels, colors, time, save_as)
 
     def run(self) -> None:
-        """Compile if needed, execute particle transport, and write output."""
+        """Compile if needed, execute particle transport, and write output.
+
+        Examples
+        --------
+        Run a fully configured simulation:
+
+        >>> simulation.run()
+        """
         from mcdc.main import run_simulation
 
         if not self.compiled:
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index e7d7a77e2..219363538 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -13,7 +13,7 @@
 
 
 class ImplicitCapture(MCDCBase):
-    """Configuration for implicit capture."""
+    """Simulation-owned implicit-capture configuration."""
 
     # MC/DC framework metadata
     label = "implicit_capture"
@@ -24,7 +24,25 @@ def __init__(self):
         self.active = False
 
     def __call__(self, active: bool = True):
-        """Enable or disable implicit capture."""
+        """Configure implicit capture.
+
+        Parameters
+        ----------
+        active : bool, optional
+            Whether implicit capture is enabled.
+
+        Examples
+        --------
+        Enable implicit capture:
+
+        >>> import mcdc
+        >>> simulation = mcdc.Simulation()
+        >>> simulation.implicit_capture()
+
+        Disable implicit capture:
+
+        >>> simulation.implicit_capture(active=False)
+        """
         self.active = active
 
 
@@ -34,7 +52,7 @@ def __call__(self, active: bool = True):
 
 
 class WeightedEmission(MCDCBase):
-    """Configuration for weighted secondary-particle emission."""
+    """Simulation-owned weighted-emission configuration."""
 
     # MC/DC framework metadata
     label = "weighted_emission"
@@ -55,6 +73,22 @@ def __call__(self, active: bool = True, weight_target: float = 1.0):
             Whether the technique is active.
         weight_target : float, optional
             Target statistical weight for emitted particles.
+
+        Examples
+        --------
+        Enable weighted emission with unit target weight:
+
+        >>> import mcdc
+        >>> simulation = mcdc.Simulation()
+        >>> simulation.weighted_emission(weight_target=1.0)
+
+        Select a different target weight:
+
+        >>> simulation.weighted_emission(weight_target=0.5)
+
+        Disable weighted emission:
+
+        >>> simulation.weighted_emission(active=False)
         """
         self.active = active
         self.weight_target = weight_target
@@ -66,7 +100,7 @@ def __call__(self, active: bool = True, weight_target: float = 1.0):
 
 
 class GlobalWeightRoulette(MCDCBase):
-    """Configuration for global low-weight particle roulette."""
+    """Simulation-owned global weight-roulette configuration."""
 
     # MC/DC framework metadata
     label = "global_weight_roulette"
@@ -83,7 +117,32 @@ def __init__(self):
     def __call__(self, weight_threshold: float = 0.0, weight_target: float = 1.0):
         """Enable roulette below a global weight threshold.
 
-        ``weight_threshold`` must not exceed ``weight_target``.
+        Parameters
+        ----------
+        weight_threshold : float, optional
+            Particle weight below which roulette is applied.
+        weight_target : float, optional
+            Statistical weight assigned to particles that survive roulette.
+            Must be greater than or equal to ``weight_threshold``.
+
+        Examples
+        --------
+        Apply roulette below a particle weight of 0.25 and raise surviving
+        particles to unit weight:
+
+        >>> import mcdc
+        >>> simulation = mcdc.Simulation()
+        >>> simulation.global_weight_roulette(
+        ...     weight_threshold=0.25,
+        ...     weight_target=1.0,
+        ... )
+
+        Use a lower target weight:
+
+        >>> simulation.global_weight_roulette(
+        ...     weight_threshold=0.1,
+        ...     weight_target=0.5,
+        ... )
         """
         if weight_threshold > weight_target:
             print_error(
@@ -100,7 +159,7 @@ def __call__(self, weight_threshold: float = 0.0, weight_target: float = 1.0):
 
 
 class WeightWindows(MCDCBase):
-    """Space- and energy-dependent particle weight-window configuration."""
+    """Simulation-owned particle weight-window configuration."""
 
     # MC/DC framework metadata
     label = "weight_windows"
@@ -139,12 +198,40 @@ def __call__(self, weight_windows, mesh=None, energy=None):
         Parameters
         ----------
         weight_windows : ndarray, shape (Ne, Nx, Ny, Nz, 3)
-            Lower, target, and upper weights in the final dimension.
+            Lower, target, and upper weights in the final dimension. Every
+            lower weight must be positive, and each window must satisfy
+            ``lower <= target <= upper``.
         mesh : MeshUniform or MeshStructured, optional
             Spatial mesh. The default is one unbounded uniform bin.
         energy : ndarray, optional
             Strictly increasing energy-group boundaries. The default is one
             all-energy bin.
+
+        Examples
+        --------
+        Apply one weight window over all space and energy:
+
+        >>> import numpy as np
+        >>> import mcdc
+        >>> simulation = mcdc.Simulation()
+        >>> windows = np.array([0.5, 1.0, 2.0]).reshape(1, 1, 1, 1, 3)
+        >>> simulation.weight_windows(windows)
+
+        Configure weight windows on a uniform spatial mesh:
+
+        >>> mesh = mcdc.MeshUniform(x=(-5.0, 1.0, 10))
+        >>> windows = np.tile([0.25, 0.5, 1.0], (1, 10, 1, 1, 1))
+        >>> simulation.weight_windows(windows, mesh=mesh)
+
+        Configure both energy- and space-dependent windows:
+
+        >>> energy = np.array([0.0, 0.625e-6, 20.0])
+        >>> windows = np.tile([0.25, 0.5, 1.0], (2, 10, 1, 1, 1))
+        >>> simulation.weight_windows(
+        ...     windows,
+        ...     mesh=mesh,
+        ...     energy=energy,
+        ... )
         """
         # fill in defaults
         if mesh is None:
@@ -217,7 +304,7 @@ def __call__(self, weight_windows, mesh=None, energy=None):
 
 
 class PopulationControl(MCDCBase):
-    """Configuration for source-bank population control."""
+    """Simulation-owned source-bank population-control configuration."""
 
     # MC/DC framework metadata
     label = "population_control"
@@ -228,5 +315,23 @@ def __init__(self):
         self.active = False
 
     def __call__(self, active: bool = True):
-        """Enable or disable population control."""
+        """Configure source-bank population control.
+
+        Parameters
+        ----------
+        active : bool, optional
+            Whether source-bank population control is enabled.
+
+        Examples
+        --------
+        Enable source-bank population control:
+
+        >>> import mcdc
+        >>> simulation = mcdc.Simulation()
+        >>> simulation.population_control()
+
+        Disable source-bank population control:
+
+        >>> simulation.population_control(active=False)
+        """
         self.active = active

From 314ea5d34fd417cc106f175538ad48586bb6150a Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 30 Jul 2026 15:57:26 +0700
Subject: [PATCH 061/202] update per encapsulation

---
 docs/source/user/index.rst | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/docs/source/user/index.rst b/docs/source/user/index.rst
index a67d3fc2e..9949bf715 100644
--- a/docs/source/user/index.rst
+++ b/docs/source/user/index.rst
@@ -4,9 +4,13 @@
 User's Guide
 ============
 
-We include a simple "first simulation guide" as well as more in-depth descriptions on how to execute MC/DC in compiled modes to CPUs and GPUs with or without MPI.
+The User's Guide explains how to build a model with MC/DC's public Python
+objects, attach it to a :class:`mcdc.Simulation`, configure settings and 
+transport techniques, and run it. Additional guides describe how
+to execute the same input script on CPUs and GPUs, with or without MPI.
 
-These instructions all assume you have an operable and working version of MC/DC installed in an appropriate environment for your system.
+These instructions assume MC/DC is installed in an active Python environment
+appropriate for your system.
 
 Getting Started
 ---------------

From 6e7b36830079619f2fdad6dbaaf99d56f3cd313b Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 30 Jul 2026 16:42:15 +0700
Subject: [PATCH 062/202] update per encapsulation

---
 mcdc/visualize.py | 10 ++--------
 1 file changed, 2 insertions(+), 8 deletions(-)

diff --git a/mcdc/visualize.py b/mcdc/visualize.py
index de98502f7..27de675be 100644
--- a/mcdc/visualize.py
+++ b/mcdc/visualize.py
@@ -1,8 +1,6 @@
 from numba import njit
 import numpy as np
-from mcdc.main import preparation
-
-_visualize_cache = None
+from mcdc.main import prepare
 
 
 def visualize_model(
@@ -42,11 +40,7 @@ def visualize_model(
 
     from matplotlib import colors as mpl_colors
 
-    # Use cached preparation if available
-    global _visualize_cache
-    if _visualize_cache is None:
-        _visualize_cache = preparation(simulationPy)
-    simulation_container, data = _visualize_cache
+    simulation_container, data = prepare(simulationPy)
     simulation = simulation_container[0]
 
     # ==================================================================================

From fd315800ca51063884354a24d4f123f46acfa2f1 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 30 Jul 2026 16:42:28 +0700
Subject: [PATCH 063/202] update per encapsulation

---
 test/unit/test_visualize.py | 30 ++++++++++++++++++++++++++++++
 1 file changed, 30 insertions(+)
 create mode 100644 test/unit/test_visualize.py

diff --git a/test/unit/test_visualize.py b/test/unit/test_visualize.py
new file mode 100644
index 000000000..11a5d2da7
--- /dev/null
+++ b/test/unit/test_visualize.py
@@ -0,0 +1,30 @@
+import matplotlib
+import numpy as np
+
+import mcdc
+
+matplotlib.use("Agg")
+
+
+def test_visualize_model(tmp_path):
+    material = mcdc.MaterialMG(capture=np.array([1.0]))
+    left = mcdc.Surface.PlaneZ(z=0.0, boundary_condition="vacuum")
+    right = mcdc.Surface.PlaneZ(z=1.0, boundary_condition="vacuum")
+    cell = mcdc.Cell(region=+left & -right, fill=material)
+
+    simulation = mcdc.Simulation()
+    simulation.set_model([cell])
+
+    output = str(tmp_path / "model")
+    simulation.visualize_model(
+        vis_plane="xz",
+        x=[-0.5, 0.5],
+        y=0.0,
+        z=[0.0, 1.0],
+        pixels=(2, 2),
+        colors=None,
+        time=[0.0],
+        save_as=output,
+    )
+
+    assert (tmp_path / "model.png").is_file()

From cfbcae85524990ae3e3ed6b7c3b1bbb52df3666b Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 30 Jul 2026 16:55:56 +0700
Subject: [PATCH 064/202] update per encapsulation

---
 docs/source/examples/c5g7_k_eigenvalue.rst   |   4 +-
 docs/source/examples/c5g7_transient.rst      |   4 +-
 docs/source/examples/fuel_array_packaged.rst |   4 +-
 docs/source/examples/index.rst               |   1 +
 docs/source/examples/kobayashi_dog_leg.rst   |   4 +-
 docs/source/examples/kobayashi_td.rst        |   4 +-
 docs/source/examples/moving_pellet.rst       |   4 +-
 docs/source/examples/moving_source.rst       |   4 +-
 docs/source/examples/slab_shielding.rst      |  37 ++
 docs/source/examples/sphere_in_cube.rst      |   4 +-
 docs/source/user/faq.rst                     |   2 +-
 docs/source/user/first_mcdc.rst              | 510 +++++++------------
 docs/source/user/index.rst                   |   1 +
 docs/source/user/tallies.rst                 | 207 ++++++++
 docs/source/user/troubleshooting.rst         |   2 +-
 examples/slab_shielding/input.py             |  69 +++
 examples/slab_shielding/process-output.py    |  30 ++
 examples/slab_shielding/slab_shielding.h5    | Bin 0 -> 32016 bytes
 18 files changed, 549 insertions(+), 342 deletions(-)
 create mode 100644 docs/source/examples/slab_shielding.rst
 create mode 100644 docs/source/user/tallies.rst
 create mode 100644 examples/slab_shielding/input.py
 create mode 100644 examples/slab_shielding/process-output.py
 create mode 100644 examples/slab_shielding/slab_shielding.h5

diff --git a/docs/source/examples/c5g7_k_eigenvalue.rst b/docs/source/examples/c5g7_k_eigenvalue.rst
index 67eda2256..06f82634c 100644
--- a/docs/source/examples/c5g7_k_eigenvalue.rst
+++ b/docs/source/examples/c5g7_k_eigenvalue.rst
@@ -53,9 +53,9 @@ The complete input used for this example is embedded below:
 How to Run
 ==========
 
-From the repository root run::
+From inside ``examples/c5g7/k-eigenvalue`` run::
 
-   python examples/c5g7/k-eigenvalue/input.py
+   python input.py
 
 Expected Output
 ===============
diff --git a/docs/source/examples/c5g7_transient.rst b/docs/source/examples/c5g7_transient.rst
index 5d4a5a025..e6dd5e722 100644
--- a/docs/source/examples/c5g7_transient.rst
+++ b/docs/source/examples/c5g7_transient.rst
@@ -52,9 +52,9 @@ The complete input used for this example is embedded below:
 How to Run
 ==========
 
-From the repository root run::
+From inside ``examples/c5g7/transient`` run::
 
-   python examples/c5g7/transient/input.py
+   python input.py
 
 Expected Output
 ===============
diff --git a/docs/source/examples/fuel_array_packaged.rst b/docs/source/examples/fuel_array_packaged.rst
index 196b28f1a..7643ebb2e 100644
--- a/docs/source/examples/fuel_array_packaged.rst
+++ b/docs/source/examples/fuel_array_packaged.rst
@@ -178,9 +178,9 @@ The complete input used for this example is embedded below:
 How to Run
 ==========
 
-From the repository root run::
+From inside ``examples/fuel_array_packaged`` run::
 
-  python examples/fuel_array_packaged/input.py
+  python input.py
 
 Expected Output
 ===============
diff --git a/docs/source/examples/index.rst b/docs/source/examples/index.rst
index c5fc2feaa..9bbaaf7ac 100644
--- a/docs/source/examples/index.rst
+++ b/docs/source/examples/index.rst
@@ -24,6 +24,7 @@ Basic Examples
 .. toctree::
    :maxdepth: 1
 
+   slab_shielding
    kobayashi_dog_leg
    kobayashi_td
 
diff --git a/docs/source/examples/kobayashi_dog_leg.rst b/docs/source/examples/kobayashi_dog_leg.rst
index b7869c5f0..8d2df90ef 100644
--- a/docs/source/examples/kobayashi_dog_leg.rst
+++ b/docs/source/examples/kobayashi_dog_leg.rst
@@ -178,9 +178,9 @@ The complete input used for this example is embedded below:
 How to Run
 ==========
 
-From the repository root run::
+From inside ``examples/kobayashi`` run::
 
-  python examples/kobayashi/input.py
+  python input.py
 
 Expected Output
 ===============
diff --git a/docs/source/examples/kobayashi_td.rst b/docs/source/examples/kobayashi_td.rst
index f55f216af..be5dd59c0 100644
--- a/docs/source/examples/kobayashi_td.rst
+++ b/docs/source/examples/kobayashi_td.rst
@@ -63,9 +63,9 @@ The complete input used for this example is embedded below:
 How to Run
 ==========
 
-From the repository root run::
+From inside ``examples/kobayashi-TD`` run::
 
-   python examples/kobayashi-TD/input.py
+   python input.py
 
 Expected Output
 ===============
diff --git a/docs/source/examples/moving_pellet.rst b/docs/source/examples/moving_pellet.rst
index af70b5a34..e6daf8962 100644
--- a/docs/source/examples/moving_pellet.rst
+++ b/docs/source/examples/moving_pellet.rst
@@ -186,9 +186,9 @@ The complete input used for this example is embedded below:
 How to Run
 ==========
 
-From the repository root run::
+From inside ``examples/moving_pellet`` run::
 
-  python examples/moving_pellet/input.py
+  python input.py
 
 Expected Output
 ===============
diff --git a/docs/source/examples/moving_source.rst b/docs/source/examples/moving_source.rst
index 99263cab6..3a77e3c64 100644
--- a/docs/source/examples/moving_source.rst
+++ b/docs/source/examples/moving_source.rst
@@ -156,9 +156,9 @@ The complete input used for this example is embedded below:
 How to Run
 ==========
 
-From the repository root run::
+From inside ``examples/moving_source`` run::
 
-  python examples/moving_source/input.py
+  python input.py
 
 Expected Output
 ===============
diff --git a/docs/source/examples/slab_shielding.rst b/docs/source/examples/slab_shielding.rst
new file mode 100644
index 000000000..5f060f5b9
--- /dev/null
+++ b/docs/source/examples/slab_shielding.rst
@@ -0,0 +1,37 @@
+.. _example_slab_shielding:
+
+==============
+Slab Shielding
+==============
+
+This one-group fixed-source problem introduces the complete MC/DC workflow
+with two materials, two slab cells, an isotropic source, and a mesh flux
+tally. The :doc:`../user/first_mcdc` guide explains the input step by step.
+
+Full Input
+----------
+
+.. literalinclude:: ../../../examples/slab_shielding/input.py
+   :language: python
+   :linenos:
+
+Post-processing
+---------------
+
+.. literalinclude:: ../../../examples/slab_shielding/process-output.py
+   :language: python
+   :linenos:
+
+How to Run
+----------
+
+From inside ``examples/slab_shielding``:
+
+.. code-block:: sh
+
+   python input.py
+   python process-output.py
+
+The transport calculation writes ``slab_shielding.h5``. The
+post-processing script reads its flux tally and writes
+``slab_shielding_flux.png``.
diff --git a/docs/source/examples/sphere_in_cube.rst b/docs/source/examples/sphere_in_cube.rst
index 8c6754b00..2f65e228c 100644
--- a/docs/source/examples/sphere_in_cube.rst
+++ b/docs/source/examples/sphere_in_cube.rst
@@ -143,9 +143,9 @@ The complete input used for this example is embedded below:
 How to Run
 ==========
 
-From the repository root run::
+From inside ``examples/sphere_in_cube`` run::
 
-  python examples/sphere_in_cube/input.py
+  python input.py
 
 Expected Output
 ===============
diff --git a/docs/source/user/faq.rst b/docs/source/user/faq.rst
index 4bb2af19b..671c7375a 100644
--- a/docs/source/user/faq.rst
+++ b/docs/source/user/faq.rst
@@ -140,5 +140,5 @@ See the post-processing section in :ref:`user/first_mcdc:First MC/DC Simulation`
 **What visualization tools work with MC/DC output?**
 
 - ``matplotlib`` for quick 1-D / 2-D plots.
-- MC/DC's built-in ``mcdc.visualize()`` for geometry inspection.
+- ``simulation.visualize_model(...)`` for built-in geometry inspection.
 - `ParaView <https://www.paraview.org/>`_ or `VisIt <https://sd.llnl.gov/simulation/computer-codes/visit>`_ for 3-D data.
diff --git a/docs/source/user/first_mcdc.rst b/docs/source/user/first_mcdc.rst
index 5c1d1ad92..99d3c60ca 100644
--- a/docs/source/user/first_mcdc.rst
+++ b/docs/source/user/first_mcdc.rst
@@ -1,409 +1,271 @@
 .. _first_mcdc:
 
-
 ======================
 First MC/DC Simulation
 ======================
 
-This guide presupposes you are familiar with modeling nuclear systems using a Monte Carlo method.
-If you are completely new, we suggest checking out `OpenMC's theory guide <https://docs.openmc.org/en/stable/methods/introduction.htmll>`_ as most the basic underlying algorithms and core concepts are the same.
-Our input decks and keyword phrases are designed so that if you are familiar with tools like OpenMC or MCNP, you should be able to get up and running quickly.
+This guide constructs and runs a one-group shielding calculation. It assumes
+familiarity with the basic concepts of Monte Carlo radiation transport.
 
-While this guide is a great place to start, the  next best place to look when getting started are our ``MCDC/examples`` or ``MCDC/test`` directories.
-Run a few problems there, change a few inputs around, and keep looking around until you get the general hang of what we are doing.
-Believe it or not, there is a method to all this madness.
-If you find yourself with errors you really don't know what to do with, take look at our `GitHub issues page <https://github.com/CEMeNT-PSAAP/MCDC/issues>`_.
-If it looks like you are the first to have a given problem feel free to submit a new ticket!
+Monte Carlo transport inputs are generally assembled from the same core
+components: materials, geometry, particle sources, tallies, and simulation
+settings. In MC/DC, these components are represented by Python objects and
+assembled into a :class:`mcdc.Simulation`.
 
-A note on testing:
-Just because something seems right doesn't mean it is.
-Care must be taken to ensure that you are running the problem you think you are.
-The software only knows what you tell it.
+The example uses multigroup data defined directly in the input, so it does not
+require an external nuclear-data library. Its complete, executable source is
+available in ``examples/slab_shielding``.
 
 MC/DC Workflow
 --------------
 
-MC/DC uses an ``input`` -> ``run`` -> ``post-process`` workflow, where users
+An MC/DC calculation follows four main steps:
 
-#. build input decks using scripts that import ``mcdc`` as a package and call functions to build geometries, tally meshes, and set other simulation parameters,
-#. define a runtime sequence in the terminal to execute the ``input`` script (terminal operations are required for MPI calls),
-#. export the results from ``.h5`` files and use the MC/DC visualizer or tools like ``matplotlib`` to view results.
+#. Construct the materials, geometry, sources, and tallies.
+#. Create a simulation and attach the model objects to it.
+#. Configure settings and transport techniques.
+#. Run particle transport and analyze the output.
 
-Building an Input Script
-------------------------
+.. important::
 
-Building an input deck can be a complicated and nuanced process. Depending on the type of simulation you need to build, you could end up touching most of the functions in MC/DC, or very few.
-Again, the best way to start building input decks is to look at what we have already done in the ``MCDC/examples`` or ``MCDC/test`` directories.
-To see more on the available input functions, look through the :doc:`../pythonapi/index` section.
+   Validate the geometry, source distribution, tally definitions, and settings
+   before interpreting simulation results. A successfully executed calculation
+   is not necessarily a correctly specified physical model.
 
-As an example, we walk through building the input for the ``MCDC/test/regression/slab_absorbium`` problem, which simulates a three-region, purely absorbing, mono-energetic slab wall.
+Problem Description
+-------------------
 
-We start with our imports:
+The model contains two adjacent slab regions:
 
-.. code-block:: python3
+- A mostly scattering source region over :math:`0 < z < 2` cm.
+- A more strongly absorbing shield over :math:`2 < z < 6` cm.
 
-    import numpy as np
+Both outer boundaries are vacuum. Particles are emitted isotropically
+throughout the source region, and a mesh tally records the flux across the
+entire domain.
 
-    import mcdc
+.. list-table:: One-group material data
+   :header-rows: 1
+   :widths: 30 20 20 20
 
-You may require more packages depending on the methods you are constructing, but most of what you need will be in these two.
-Now, we define the materials for the problem:
+   * - Region
+     - Range (cm)
+     - :math:`\Sigma_c` (cm\ :sup:`-1`)
+     - :math:`\Sigma_s` (cm\ :sup:`-1`)
+   * - Source region
+     - :math:`0 < z < 2`
+     - 0.1
+     - 0.9
+   * - Shield
+     - :math:`2 < z < 6`
+     - 0.7
+     - 0.3
 
-.. code-block:: python3
+The total cross section is :math:`1.0\ \text{cm}^{-1}` in both regions.
+Changing the capture-to-scatter ratio isolates the effect of the shield on the
+flux distribution.
 
-    # Set materials
-    m1 = mcdc.MaterialMG(capture=np.array([1.0]))
-    m2 = mcdc.MaterialMG(capture=np.array([1.5]))
-    m3 = mcdc.MaterialMG(capture=np.array([2.0]))
+Building the Input
+------------------
 
-In this problem we only have mono-energetic capture, but MC/DC has support for multi-group (capture, scatter, fission) and continuous energy (capture, scatter, fission).
-Multi-group materials are created with ``mcdc.MaterialMG``; for example, a 3-group capture cross section would be ``capture=np.array([1.0, 1.1, 0.8])``.
-Continuous-energy materials are created with ``mcdc.Material``.
+Imports and Simulation
+~~~~~~~~~~~~~~~~~~~~~~
 
-If you are a member of CEMeNT, we have internal repositories containing the data required for continuous-energy simulation.
-Unfortunately due to export controls we can not publicly distribute this data.
-If you are looking for cross-section data to plug into MC/DC, we recommend you look at OpenMC or `NJOY <http://www.njoy21.io/>`_.
-
-After setting material data, we define the problem space by setting up surfaces with their boundary conditions.
-If no boundary condition is defined, the surface is assumed to be internal (``boundary_condition="none"``).
-Surfaces are created using class methods on ``mcdc.Surface`` (e.g., ``PlaneX``, ``PlaneY``, ``PlaneZ``, ``Sphere``, ``CylinderZ``).
+NumPy provides the numerical arrays used for cross sections and tally grids.
+The ``Simulation`` instance collects the model and controls its execution:
 
 .. code-block:: python3
 
-    # Set surfaces
-    s1 = mcdc.Surface.PlaneZ(z=0.0, boundary_condition="vacuum")
-    s2 = mcdc.Surface.PlaneZ(z=2.0)
-    s3 = mcdc.Surface.PlaneZ(z=4.0)
-    s4 = mcdc.Surface.PlaneZ(z=6.0, boundary_condition="vacuum")
+   import numpy as np
 
-Remember that the radiation transport equation is a 7-dimensional integro-differential equation,
-so it's possible your problem will need both initial and boundary conditions.
-While we have tried to include warnings and errors if an ill-posed problem is detected,
-we cannot forecast all the ways in which things might go haywire.
-For transient simulations, initial conditions are assumed to be 0 everywhere.
+   import mcdc
 
-We create problem geometry using cells, which are defined by the surfaces that constrain them and the material that fills them.
-The ``+/-`` convention is used to indicate whether the cell volume is outside (+) or inside (-) a given surface.
-For example, below, the first cell is filled with material m2 and is positive with respect to s1, negative with respect to s2.
-This corresponds to being bound on the left by s1 and on the right by s2.
-Cells are created with ``mcdc.Cell``, using the ``region`` and ``fill`` keyword arguments.
 
-.. code-block:: python3
+   simulation = mcdc.Simulation("One-group slab shielding")
 
-    mcdc.Cell(region=+s1 & -s2, fill=m2)
-    mcdc.Cell(region=+s2 & -s3, fill=m3)
-    mcdc.Cell(region=+s3 & -s4, fill=m1)
+Materials
+~~~~~~~~~
 
-We define a uniform isotropic source throughout the domain:
+``MaterialMG`` represents multigroup interaction data. A one-element capture
+array and a :math:`1 \times 1` scattering matrix define a one-group material:
 
 .. code-block:: python3
 
-    mcdc.Source(z=[0.0, 6.0], isotropic=True, energy_group=0)
-
-Next we set tallies and specify the specific parameters of interest. Here, we're interested in the space-averaged flux
-and collision rate. A mesh is created first, then a mesh-filtered ``Tally`` is constructed on that mesh.
-Direction bins can also be specified on the tally.
-Regardless of problem specifics, particles are simulated through all space, direction, and time;
-the tally definitions are used to indicate in which dimensions a record of particle behavior should be kept.
-Available tracklength scores include ``"flux"``, ``"density"``, ``"collision"``, ``"capture"``, and ``"fission"``.
-Current tallies can be attached to either a surface or a cell.
-Current scoring uses the surface-crossing estimator in both cases.
-For explicit surface filters, supported score is ``"current-net"``.
-For cell filters, supported scores are ``"current-net"``, ``"current-in"``, and ``"current-out"``.
-The ``"current-in"`` and ``"current-out"`` scores are positive partial currents; ``"current-net"`` keeps the sign
-of the crossing direction.
+   source_region_material = mcdc.MaterialMG(
+       capture=np.array([0.1]),
+       scatter=np.array([[0.9]]),
+   )
+   shield_material = mcdc.MaterialMG(
+       capture=np.array([0.7]),
+       scatter=np.array([[0.3]]),
+   )
 
-.. code-block:: python3
-
-    # Tally: cell-average fluxes and collisions
-    mesh = mcdc.MeshStructured(z=np.linspace(0.0, 6.0, 61))
-    mcdc.Tally(
-        mesh=mesh,
-        scores=["flux", "collision"],
-        mu=np.linspace(-1.0, 1.0, 32 + 1),
-    )
-
-    # Tally: current crossing a cell boundary
-    mcdc.Tally(
-        cell=my_cell,
-        scores=["current-net", "current-in", "current-out"],
-    )
-
-Next we set simulation settings. The only required setting is the number of particles.
-Settings are configured by assigning attributes on the ``mcdc.settings`` singleton.
-Additional settings include, for example, the cycles to use for a k-eigenvalue problem
-(via ``mcdc.settings.set_eigenmode(...)``) or the output file name.
-
-.. code-block:: python3
+Continuous-energy calculations instead use :class:`mcdc.Material` and require
+an MC/DC nuclear-data library. See :ref:`install-data-library` for
+configuration instructions.
 
-    mcdc.settings.N_particle = 1000
+Geometry
+~~~~~~~~
 
-Finally, execute the problem.
+Three z-planes define the two slab regions. The outer planes use vacuum
+boundary conditions; the plane at :math:`z=2` cm is an internal interface:
 
 .. code-block:: python3
 
-    mcdc.run()
+   left = mcdc.Surface.PlaneZ(z=0.0, boundary_condition="vacuum")
+   interface = mcdc.Surface.PlaneZ(z=2.0)
+   right = mcdc.Surface.PlaneZ(z=6.0, boundary_condition="vacuum")
 
-Put together, our example ``input.py`` file:
+A cell combines a region with the material that fills it. A positive
+half-space selects points above a ``PlaneZ``, while a negative half-space
+selects points below it:
 
 .. code-block:: python3
 
-    import numpy as np
-    import mcdc
+   source_cell = mcdc.Cell(
+       region=+left & -interface,
+       fill=source_region_material,
+   )
+   shield_cell = mcdc.Cell(
+       region=+interface & -right,
+       fill=shield_material,
+   )
+   simulation.set_model([source_cell, shield_cell])
 
-    # =============================================================================
-    # Set model
-    # =============================================================================
-    # Three slab layers with different purely-absorbing materials
+The cells are the roots of the geometry. MC/DC reaches their materials and
+surfaces when it compiles the simulation, so those objects do not require
+separate setter calls.
 
-    # Set materials
-    m1 = mcdc.MaterialMG(capture=np.array([1.0]))
-    m2 = mcdc.MaterialMG(capture=np.array([1.5]))
-    m3 = mcdc.MaterialMG(capture=np.array([2.0]))
+Source
+~~~~~~
 
-    # Set surfaces
-    s1 = mcdc.Surface.PlaneZ(z=0.0, boundary_condition="vacuum")
-    s2 = mcdc.Surface.PlaneZ(z=2.0)
-    s3 = mcdc.Surface.PlaneZ(z=4.0)
-    s4 = mcdc.Surface.PlaneZ(z=6.0, boundary_condition="vacuum")
+The source emits group-0 particles isotropically and uniformly throughout the
+first cell:
 
-    # Set cells
-    mcdc.Cell(region=+s1 & -s2, fill=m2)
-    mcdc.Cell(region=+s2 & -s3, fill=m3)
-    mcdc.Cell(region=+s3 & -s4, fill=m1)
-
-    # =============================================================================
-    # Set source
-    # =============================================================================
-    # Uniform isotropic source throughout the domain
+.. code-block:: python3
 
-    mcdc.Source(z=[0.0, 6.0], isotropic=True, energy_group=0)
+   source = mcdc.Source(
+       z=[0.0, 2.0],
+       isotropic=True,
+       energy_group=0,
+   )
+   simulation.set_sources([source])
 
-    # =============================================================================
-    # Set tally, setting, and run mcdc
-    # =============================================================================
+Tallies
+~~~~~~~
 
-    # Tally: cell-average fluxes and collisions
-    mesh = mcdc.MeshStructured(z=np.linspace(0.0, 6.0, 61))
-    mcdc.Tally(
-        mesh=mesh,
-        scores=["flux", "collision"],
-        mu=np.linspace(-1.0, 1.0, 32 + 1),
-    )
+The structured mesh divides the domain into 60 equal spatial bins. The tally
+scores the track-length estimate of flux in each bin:
 
-    # Setting
-    mcdc.settings.N_particle = 1000
+.. code-block:: python3
 
-    # Run
-    mcdc.run()
+   mesh = mcdc.MeshStructured(z=np.linspace(0.0, 6.0, 61))
+   flux_tally = mcdc.Tally(
+       name="slab_flux",
+       mesh=mesh,
+       scores=["flux"],
+   )
+   simulation.set_tallies([flux_tally])
 
-Now that we have a script to run, how do we actually run it?
+Naming the tally makes its location in the output file predictable:
+``tallies/slab_flux``.
 
-Running a Simulation
---------------------
+Settings and Execution
+~~~~~~~~~~~~~~~~~~~~~~
 
-MC/DC supports execution purely in the Python interpreter, compiled to CPUs (x86, ARM64 and Power9-64),
-and GPUs (AMD and Nvidia) and supports threading with MPI (Python or compiled modes).
-Other guides are included to execute in these modes but for the sake of this first
-MC/DC simulation we will simply execute in Python mode (slower, no acceleration) simply with
+This example runs 1,000 particle histories in each of 10 statistically
+independent batches. Multiple batches allow MC/DC to estimate the standard
+deviation of each tally bin:
 
 .. code-block:: python3
 
-    python input.py
+   simulation.settings.N_particle = 1_000
+   simulation.settings.N_batch = 10
+   simulation.settings.output_name = "slab_shielding"
 
-from a command line.
-For more performance see how to execute MC/DC on CPUs and GPUs
+   simulation.run()
 
-Postprocessing Results
-----------------------
+The calculation writes its results to ``slab_shielding.h5``.
+
+Complete Input
+--------------
 
-While the entire workflow of running and post-processing MC/DC could be done in one script,
-unless the problem is very small (or you're an expert),
-we recommend using separate simulation and post-processing/visualization scripts.
+The complete runnable input is embedded directly from
+``examples/slab_shielding/input.py``:
 
-When a problem is executed tallied results are compiled, compressed, and saved in ``.h5`` files.
-The size of these files can vary widely depending on your tally settings, 
-the geometric size of the problem (e.g. number of surfaces), and the number of particles tracked.
-Expect sizes as small as ``kB`` or as large as ``TB``.
+.. literalinclude:: ../../../examples/slab_shielding/input.py
+   :language: python
+   :linenos:
 
-These result files can be exported, manipulated, and visualized.
-Data can be pulled from an ``.h5`` file using something like,
+Visualizing the Model
+---------------------
+
+Before running transport, insert the following call immediately before
+``simulation.run()`` to render an x-z slice of the material geometry:
 
 .. code-block:: python3
 
-    import h5py
-    import numpy as np
-    # Load results
-    with h5py.File("output.h5", "r") as f:
-        # The tally name matches the auto-generated name (e.g., "mesh_tally_0")
-        tally_name = list(f["tallies"].keys())[0]
-        tally = f[f"tallies/{tally_name}"]
+   simulation.visualize_model(
+       vis_plane="xz",
+       x=[-1.0, 1.0],
+       y=0.0,
+       z=[0.0, 6.0],
+       pixels=(100, 300),
+       colors=None,
+       time=[0.0],
+       save_as="slab_shielding_geometry",
+   )
 
-        z = tally["grid/z"][:]
-        dz = z[1:] - z[:-1]
-        z_mid = 0.5 * (z[:-1] + z[1:])
+The image is saved as ``slab_shielding_geometry.png``. Visualization compiles
+the current model when necessary.
 
-        mu = tally["grid/mu"][:]
-        dmu = mu[1:] - mu[:-1]
-        mu_mid = 0.5 * (mu[:-1] + mu[1:])
+Running the Example
+-------------------
 
-        psi = tally["flux/mean"][:]
-        psi_sd = tally["flux/sdev"][:]
+Enter the problem directory, then run the input in pure Python mode:
 
-While there can be some nuance to the dimensions of these data arrays, the folder structures should be evident from your tally settings.
-You can see the structure of the file layer-by-layer using the ``keys`` attribute of an h5 group.
-For example, ``f.keys()`` will return
+.. code-block:: sh
 
-.. code-block:: bash
+   cd examples/slab_shielding
+   python input.py
 
-    <KeysViewHDF5 ['runtime', 'tallies']>
+Pure Python mode avoids compilation overhead and is suitable for checking a
+small model. For accelerated or parallel calculations, see :doc:`cpu`,
+:doc:`gpu`, and :doc:`batch_scripts`.
 
-and ``f['tallies'].keys()`` will list all tally names.
+Post-processing
+---------------
 
-If needed, you can look around a ``.h5`` file using something like `h5Viewer <https://www.hdfgroup.org/download-hdfview/>`_ (which on linux can be installed with ``sudo apt-get install hdfview``).
-Otherwise these arrays can then be manipulated and modified like any other.
-Results are stored as NumPy arrays, so any tool that works with NumPy arrays (*e.g.*, SciPy and Pandas)
-can be used to analyze the data from your simulations.
+MC/DC writes tally results and runtime information to HDF5. The companion
+script reads the spatial grid, normalizes the flux and standard deviation by
+the mesh-bin widths, and plots the result:
 
-A tool like ``matplotlib`` will work great for plotting results.
-For more complex simulations, open source professional visualization software like
-`Paraview <https://www.paraview.org/>`_  or `Visit <https://sd.llnl.gov/simulation/computer-codes/visit>`_ are available.
+.. literalinclude:: ../../../examples/slab_shielding/process-output.py
+   :language: python
+   :linenos:
 
-As the problem we ran above is pretty simple and has no scattering or fission, we have an `analytic solution we can import <https://github.com/CEMeNT-PSAAP/MCDC/blob/main/test/regression/slab_absorbium/reference.py>`_:
+After the transport calculation finishes, run the companion script from the
+same problem directory:
 
-.. code-block:: python3
+.. code-block:: sh
 
-    from reference import reference
+   python process-output.py
 
-In the script below, we plot the space-averaged flux and space-averaged current, including their statistical noise.
-We also use the space-averaged flux and current to compute a new quantity, the space-averaged angular flux, and
-plot it over space and angle in a heat map.
-Remember that when reporting results from a Monte Carlo solver, you should **always include the statistical error!**
+The script writes ``slab_shielding_flux.png``. The dashed line marks the
+material interface at :math:`z=2` cm. The flux is expected to decrease more
+rapidly in the shield because capture accounts for a larger fraction of its
+total cross section.
 
+Next Steps
+----------
 
-.. code-block:: python3
+After running the original problem, useful variations include:
+
+- Increase ``N_particle`` and compare the reported standard deviation.
+- Change the shield capture and scattering cross sections.
+- Move the material interface and observe the change in attenuation.
+- Add an energy group or another spatial region.
+- Add a surface-crossing tally at the material interface.
 
-    import matplotlib.pyplot as plt
-    import numpy as np
-
-    I = len(z) - 1
-    N = len(mu) - 1
-
-    # Scalar flux
-    phi = np.zeros(I)
-    phi_sd = np.zeros(I)
-    for i in range(I):
-        phi[i] += np.sum(psi[i, :])
-        phi_sd[i] += np.linalg.norm(psi_sd[i, :])
-
-    # Normalize
-    phi /= dz
-    phi_sd /= dz
-    J /= dz
-    J_sd /= dz
-    for n in range(N):
-        psi[:, n] = psi[:, n] / dz / dmu[n]
-        psi_sd[:, n] = psi_sd[:, n] / dz / dmu[n]
-
-    # Reference solution
-    phi_ref, J_ref, psi_ref = reference(z, mu)
-
-    # Flux - spatial average
-    plt.plot(z_mid, phi, "-b", label="MC")
-    plt.fill_between(z_mid, phi - phi_sd, phi + phi_sd, alpha=0.2, color="b")
-    plt.plot(z_mid, phi_ref, "--r", label="Ref.")
-    plt.xlabel(r"$z$, cm")
-    plt.ylabel("Flux")
-    plt.ylim([0.06, 0.16])
-    plt.grid()
-    plt.legend()
-    plt.title(r"$\bar{\phi}_i$")
-    plt.show()
-
-    # Current - spatial average
-    plt.plot(z_mid, J, "-b", label="MC")
-    plt.fill_between(z_mid, J - J_sd, J + J_sd, alpha=0.2, color="b")
-    plt.plot(z_mid, J_ref, "--r", label="Ref.")
-    plt.xlabel(r"$z$, cm")
-    plt.ylabel("Current")
-    plt.ylim([-0.03, 0.045])
-    plt.grid()
-    plt.legend()
-    plt.title(r"$\bar{J}_i$")
-    plt.show()
-
-    # Angular flux - spatial average
-    vmin = min(np.min(psi_ref), np.min(psi))
-    vmax = max(np.max(psi_ref), np.max(psi))
-    fig, ax = plt.subplots(1, 2, sharey=True)
-    Z, MU = np.meshgrid(z_mid, mu_mid)
-    im = ax[0].pcolormesh(MU.T, Z.T, psi_ref, vmin=vmin, vmax=vmax)
-    ax[0].set_xlabel(r"Polar cosine, $\mu$")
-    ax[0].set_ylabel(r"$z$")
-    ax[0].set_title(r"\psi")
-    ax[0].set_title(r"$\bar{\psi}_i(\mu)$ [Ref.]")
-    ax[1].pcolormesh(MU.T, Z.T, psi, vmin=vmin, vmax=vmax)
-    ax[1].set_xlabel(r"Polar cosine, $\mu$")
-    ax[1].set_ylabel(r"$z$")
-    ax[1].set_title(r"$\bar{\psi}_i(\mu)$ [MC]")
-    fig.subplots_adjust(right=0.8)
-    cbar_ax = fig.add_axes([0.85, 0.15, 0.05, 0.7])
-    cbar = fig.colorbar(im, cax=cbar_ax)
-    cbar.set_label("Angular flux")
-    plt.show()
-
-While this script does look rather long, most of these commands are controlling things like axis labels and whatnot.
-But at the end we have something like this.
-
-.. image:: ../images/user/sf_slab_1.png
-   :width: 266
-   :alt: Reference v computed scalar flux, 1e3 particles
-.. image:: ../images/user/j_slab_1.png
-   :width: 266
-   :alt: Reference v computed current, 1e3 particles
-.. image:: ../images/user/af_slab_1.png
-   :width: 266
-   :alt: Reference v computed angular flux, 1e3 particles
-
-Notice how noisy these solutions are? We only ran 1e3 particles.
-We need more particles to get a less statistically noisy, more converged solution.
-Here's results from the same simulation run with 1e6 particles:
-
-.. image:: ../images/user/sf_slab_2.png
-   :width: 266
-   :alt: Reference v computed scalar flux, 1e6 particles
-.. image:: ../images/user/j_slab_2.png
-   :width: 266
-   :alt: Reference v computed current, 1e6 particles
-.. image:: ../images/user/af_slab_2.png
-   :width: 266
-   :alt: Reference v computed angular flux, 1e6 particles
-
-This is much better converged around the analytic solution.
-As with everything else, the best way to see what you can do is sniff around the examples.
-We have examples with animated solutions, subplots, moving regions and more!
-
-Additional Simulation Results
------------------------------
-
-- Neutron flux distribution on a shielded dog-leg vacuum channel after a neutron pulse is completed
-
-.. image:: ../images/user/kobayashi-white.png
-   :width: 266
-   :alt: Neutron flux distribution on a shielded dog-leg vacuum channel after a neutron pulse is completed
-
-- Bottom-view of a micro reactor fission rate distribution when a control rod-driven runaway prompt supercritical occurs
-
-.. image:: ../images/user/c5g7.png
-   :width: 266
-   :alt: Bottom-view of a micro reactor fission rate distribution when a control rod-driven runaway prompt supercritical occurs
-
-- Fission and flux bursts of a neutron excursion driven by a drop of highly-enriched uranium.
-
-.. image:: ../images/user/dragon.gif
-   :width: 266
-   :alt: Fission and flux bursts of a neutron excursion driven by a drop of highly-enriched uranium
-
--------------------------------------
-MC/DC's built in model ``visualizer``
--------------------------------------
+See :doc:`../examples/index` for examples involving lattices, moving geometry,
+time-dependent transport, and reactor benchmarks.
diff --git a/docs/source/user/index.rst b/docs/source/user/index.rst
index 9949bf715..00005803c 100644
--- a/docs/source/user/index.rst
+++ b/docs/source/user/index.rst
@@ -19,6 +19,7 @@ Getting Started
    :maxdepth: 1
 
    first_mcdc
+   tallies
 
 Execution Modes
 ---------------
diff --git a/docs/source/user/tallies.rst b/docs/source/user/tallies.rst
new file mode 100644
index 000000000..791d98a15
--- /dev/null
+++ b/docs/source/user/tallies.rst
@@ -0,0 +1,207 @@
+.. _user_tallies:
+
+=============================
+Tallies and Post-processing
+=============================
+
+Tallies specify which transport quantities MC/DC records and how those
+quantities are divided into bins. This page extends the model from
+:doc:`first_mcdc`; add the examples below before ``simulation.run()``. The code
+snippets assume NumPy has been imported as ``np``.
+
+Each tally combines:
+
+- one or more scores, such as flux, collision rate, or current;
+- optional spatial, angular, energy, time, surface, or cell filters; and
+- a name used to identify the tally in the output file.
+
+Only tallies passed to ``simulation.set_tallies(...)`` are scored.
+
+Mesh Tallies
+------------
+
+The introductory example scores flux over a structured z mesh:
+
+.. code-block:: python3
+
+   mesh = mcdc.MeshStructured(z=np.linspace(0.0, 6.0, 61))
+   flux_tally = mcdc.Tally(
+       name="slab_flux",
+       mesh=mesh,
+       scores=["flux"],
+   )
+   simulation.set_tallies([flux_tally])
+
+The 61 grid points define 60 spatial bins. Track-length scores include
+``"flux"``, ``"density"``, ``"collision"``, ``"capture"``, and
+``"fission"``.
+
+Angular Filters
+---------------
+
+Add polar-cosine boundaries to retain angular information:
+
+.. code-block:: python3
+
+   angular_flux_tally = mcdc.Tally(
+       name="angular_flux",
+       mesh=mesh,
+       mu=np.linspace(-1.0, 1.0, 33),
+       scores=["flux"],
+   )
+   simulation.set_tallies([angular_flux_tally])
+
+The resulting tally contains 32 polar-angle bins in each spatial bin. A
+reference direction can be supplied with ``polar_reference``; its default is
+the positive z direction.
+
+Surface-crossing Tallies
+------------------------
+
+A surface filter scores net current across a particular surface:
+
+.. code-block:: python3
+
+   interface_current = mcdc.Tally(
+       name="interface_current",
+       surface=interface,
+       scores=["current-net"],
+   )
+
+The current sign follows the orientation of the surface normal. For the
+``PlaneZ`` at the material interface, crossings toward increasing z contribute
+positively and crossings toward decreasing z contribute negatively.
+
+A cell filter can score current across every boundary of a cell:
+
+.. code-block:: python3
+
+   shield_cell_current = mcdc.Tally(
+       name="shield_cell_current",
+       cell=shield_cell,
+       scores=["current-net", "current-in", "current-out"],
+   )
+
+``"current-in"`` and ``"current-out"`` are positive partial currents;
+``"current-net"`` retains the crossing sign.
+
+Combining cell and surface filters restricts the tally to one surface while
+using the cell to classify incoming and outgoing crossings:
+
+.. code-block:: python3
+
+   shield_interface_current = mcdc.Tally(
+       name="shield_interface_current",
+       surface=interface,
+       cell=shield_cell,
+       scores=["current-net", "current-in", "current-out"],
+   )
+
+Attach every requested tally in one call:
+
+.. code-block:: python3
+
+   simulation.set_tallies(
+       [
+           flux_tally,
+           interface_current,
+           shield_cell_current,
+           shield_interface_current,
+       ]
+   )
+
+Statistical Uncertainty
+-----------------------
+
+MC/DC estimates tally uncertainty from statistically independent batches:
+
+.. code-block:: python3
+
+   simulation.settings.N_particle = 1_000
+   simulation.settings.N_batch = 10
+
+``N_particle`` is the number of histories per batch. Increasing
+``N_particle`` reduces the noise within each batch, while ``N_batch`` controls
+how many independent batch results contribute to the reported standard
+deviation. At least two batches are required for a nonzero estimate.
+
+Reading Tally Output
+--------------------
+
+Named tallies are stored under ``tallies/<name>`` in the output HDF5 file.
+The filter grids and score results are stored below that group:
+
+.. code-block:: text
+
+   tallies/
+     slab_flux/
+       grid/
+         z
+       flux/
+         mean
+         sdev
+
+Load and normalize the mesh flux with h5py:
+
+.. code-block:: python3
+
+   import h5py
+
+   with h5py.File("slab_shielding.h5", "r") as output:
+       tally = output["tallies/slab_flux"]
+       z = tally["grid/z"][:]
+       flux = tally["flux/mean"][:]
+       flux_sdev = tally["flux/sdev"][:]
+
+   dz = z[1:] - z[:-1]
+   flux /= dz
+   flux_sdev /= dz
+
+The score arrays contain values integrated over their bins. Divide by the
+applicable spatial, angular, energy, or time widths when a differential result
+is required.
+
+Reducing an Angular Tally
+-------------------------
+
+For the angular tally above, sum the angle-bin contributions to recover scalar
+flux. Weighting by the polar-cosine midpoint gives a midpoint approximation of
+the z-directed current:
+
+.. code-block:: python3
+
+   with h5py.File("slab_shielding.h5", "r") as output:
+       tally = output["tallies/angular_flux"]
+       z = tally["grid/z"][:]
+       mu = tally["grid/mu"][:]
+       angular_flux = tally["flux/mean"][:]
+       angular_flux_sdev = tally["flux/sdev"][:]
+
+   dz = z[1:] - z[:-1]
+   dmu = mu[1:] - mu[:-1]
+   mu_mid = 0.5 * (mu[:-1] + mu[1:])
+
+   scalar_flux = np.sum(angular_flux, axis=0) / dz
+   scalar_flux_sdev = np.linalg.norm(angular_flux_sdev, axis=0) / dz
+   current = np.sum(
+       angular_flux * mu_mid[:, np.newaxis],
+       axis=0,
+   ) / dz
+
+The exact array-axis order follows the active filters and is recorded by the
+corresponding grids in the tally group. Inspect the output shapes before
+performing reductions.
+
+Verification
+------------
+
+Before drawing conclusions from a tally:
+
+- Confirm that its filters cover the intended phase-space region.
+- Check that the result changes consistently when the mesh is refined.
+- Increase the particle population and verify that uncertainty decreases.
+- Use current tallies to check particle balance where appropriate.
+- Compare against an analytic or benchmark solution when one is available.
+
+The :class:`mcdc.Tally` API reference documents all supported scores and filter
+combinations.
diff --git a/docs/source/user/troubleshooting.rst b/docs/source/user/troubleshooting.rst
index 1e3595fbe..dff51b47a 100644
--- a/docs/source/user/troubleshooting.rst
+++ b/docs/source/user/troubleshooting.rst
@@ -202,7 +202,7 @@ Also ensure that the number of MPI ranks does not exceed available cores:
 
    srun -n <ncores> python input.py --mode=numba
 
-**"AttributeError: 'list' object has no attribute 'ID'" in** ``mcdc.cell()``
+**"AttributeError: 'list' object has no attribute 'ID'" in** ``mcdc.Cell()``
 
 This error occurs when passing a Python list instead of using the ``&`` (intersection)
 and ``|`` (union) region operators.
diff --git a/examples/slab_shielding/input.py b/examples/slab_shielding/input.py
new file mode 100644
index 000000000..3d5fec72c
--- /dev/null
+++ b/examples/slab_shielding/input.py
@@ -0,0 +1,69 @@
+import numpy as np
+
+import mcdc
+
+simulation = mcdc.Simulation("One-group slab shielding")
+
+# Materials
+source_region_material = mcdc.MaterialMG(
+    capture=np.array([0.1]),
+    scatter=np.array([[0.9]]),
+)
+shield_material = mcdc.MaterialMG(
+    capture=np.array([0.7]),
+    scatter=np.array([[0.3]]),
+)
+
+# Geometry
+left = mcdc.Surface.PlaneZ(z=0.0, boundary_condition="vacuum")
+interface = mcdc.Surface.PlaneZ(z=2.0)
+right = mcdc.Surface.PlaneZ(z=6.0, boundary_condition="vacuum")
+
+source_cell = mcdc.Cell(
+    region=+left & -interface,
+    fill=source_region_material,
+)
+shield_cell = mcdc.Cell(
+    region=+interface & -right,
+    fill=shield_material,
+)
+simulation.set_model([source_cell, shield_cell])
+
+# Source
+source = mcdc.Source(
+    z=[0.0, 2.0],
+    isotropic=True,
+    energy_group=0,
+)
+simulation.set_sources([source])
+
+# Tally
+mesh = mcdc.MeshStructured(z=np.linspace(0.0, 6.0, 61))
+flux_tally = mcdc.Tally(
+    name="slab_flux",
+    mesh=mesh,
+    scores=["flux"],
+)
+simulation.set_tallies([flux_tally])
+
+# Settings
+simulation.settings.N_particle = 1_000
+simulation.settings.N_batch = 10
+simulation.settings.output_name = "slab_shielding"
+
+# Visualize model
+"""
+simulation.visualize_model(
+    vis_plane="xz",
+    x=[-1.0, 1.0],
+    y=0.0,
+    z=[0.0, 6.0],
+    pixels=(100, 300),
+    colors=None,
+    time=[0.0],
+    save_as="slab_shielding_geometry",
+)
+"""
+
+# Run simulation
+simulation.run()
diff --git a/examples/slab_shielding/process-output.py b/examples/slab_shielding/process-output.py
new file mode 100644
index 000000000..dca8214ed
--- /dev/null
+++ b/examples/slab_shielding/process-output.py
@@ -0,0 +1,30 @@
+import h5py
+import matplotlib.pyplot as plt
+
+with h5py.File("slab_shielding.h5", "r") as output:
+    tally = output["tallies/slab_flux"]
+    z = tally["grid/z"][:]
+    flux = tally["flux/mean"][:]
+    flux_sdev = tally["flux/sdev"][:]
+
+dz = z[1:] - z[:-1]
+z_mid = 0.5 * (z[:-1] + z[1:])
+flux /= dz
+flux_sdev /= dz
+
+figure, axis = plt.subplots()
+axis.plot(z_mid, flux, label="Flux")
+axis.fill_between(
+    z_mid,
+    flux - flux_sdev,
+    flux + flux_sdev,
+    alpha=0.25,
+    label="Standard deviation",
+)
+axis.axvline(2.0, color="black", linestyle="--", label="Material interface")
+axis.set_xlabel("z [cm]")
+axis.set_ylabel("Flux")
+axis.grid()
+axis.legend()
+figure.tight_layout()
+figure.savefig("slab_shielding_flux.png", dpi=150)
diff --git a/examples/slab_shielding/slab_shielding.h5 b/examples/slab_shielding/slab_shielding.h5
new file mode 100644
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From 7dee244b8ae758793ddbb2bda010e9f6fb97ad5c Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 30 Jul 2026 19:50:04 +0700
Subject: [PATCH 065/202] update examples per encapsulation

---
 docs/source/examples/fuel_array_packaged.rst |  8 +++---
 docs/source/examples/kobayashi_dog_leg.rst   |  2 +-
 docs/source/examples/moving_pellet.rst       |  2 +-
 docs/source/theory/geometry.rst              | 25 ++++++++++++-----
 docs/source/theory/k_eigenvalue.rst          |  2 +-
 docs/source/theory/variance_reduction.rst    | 28 ++++++++++++--------
 6 files changed, 43 insertions(+), 24 deletions(-)

diff --git a/docs/source/examples/fuel_array_packaged.rst b/docs/source/examples/fuel_array_packaged.rst
index 7643ebb2e..eca9d00e4 100644
--- a/docs/source/examples/fuel_array_packaged.rst
+++ b/docs/source/examples/fuel_array_packaged.rst
@@ -91,7 +91,7 @@ Reference Solution
 ==================
 
 No analytical reference.  The geometry can be verified using MC/DC's
-built-in ``mcdc.visualize()`` function to render the CSG model.
+built-in ``simulation.visualize_model()`` method to render the CSG model.
 
 Step-by-Step Walkthrough
 ========================
@@ -133,7 +133,7 @@ The assembly universe is placed twice using ``mcdc.Cell(..., fill=assembly)``:
 - **Left** — translated to :math:`(-5, 0, 0)`.
 - **Right** — translated to :math:`(+5, 0, 0)` and rotated 10° about :math:`y`.
 
-``set_root_universe()`` tells MC/DC these are the top-level cells.
+``simulation.set_model()`` tells MC/DC these are the top-level cells.
 
 **4. Source, Tallies, Settings, and Run (lines 82–105)**
 
@@ -156,7 +156,7 @@ The ``active_bank_buffer`` accommodates fission-born particles.
    :lineno-match:
 
 Set ``visualize = True`` to render the CSG geometry with
-``mcdc.visualize()`` instead of running the transport.
+``simulation.visualize_model()`` instead of running the transport.
 
 **What to try:**
 
@@ -186,4 +186,4 @@ Expected Output
 ===============
 
 An HDF5 mesh tally and optional visualization images produced by the
-``mcdc.visualize()`` helper when run with visualization enabled.
+``simulation.visualize_model()`` method when run with visualization enabled.
diff --git a/docs/source/examples/kobayashi_dog_leg.rst b/docs/source/examples/kobayashi_dog_leg.rst
index 8d2df90ef..d9914ce2d 100644
--- a/docs/source/examples/kobayashi_dog_leg.rst
+++ b/docs/source/examples/kobayashi_dog_leg.rst
@@ -156,7 +156,7 @@ An isotropic, uniformly distributed source fills the
 - A uniform :math:`60 \times 100 \times 60` mesh tally records scalar flux.
 - 1 000 source particles in 2 batches (increase for production).
 - Implicit capture prevents particles from being absorbed prematurely.
-- ``mcdc.run()`` launches the simulation.
+- ``simulation.run()`` launches the simulation.
 
 **What to try:**
 
diff --git a/docs/source/examples/moving_pellet.rst b/docs/source/examples/moving_pellet.rst
index e6daf8962..74d996283 100644
--- a/docs/source/examples/moving_pellet.rst
+++ b/docs/source/examples/moving_pellet.rst
@@ -169,7 +169,7 @@ captures the fission rate as the pellet moves.
 
 - Change the pellet velocities to create different trajectories.
 - Set ``visualize = True`` to watch the geometry evolve with
-  ``mcdc.visualize(..., time=...)``.
+  ``simulation.visualize_model(..., time=...)``.
 - Compare with ``moving_source`` to see source motion vs. geometry motion.
 
 Full Input
diff --git a/docs/source/theory/geometry.rst b/docs/source/theory/geometry.rst
index 062523ef8..872430870 100644
--- a/docs/source/theory/geometry.rst
+++ b/docs/source/theory/geometry.rst
@@ -151,12 +151,14 @@ for a full-core lattice example.
 Root Universe
 ^^^^^^^^^^^^^
 
-When using universes or lattices, the top-level cell collection is
-registered as the **root universe**:
+When using universes or lattices, attach the top-level cell collection
+to a simulation. MC/DC registers these cells in the simulation's
+**root universe**:
 
 .. code-block:: python3
 
-   mcdc.simulation.set_root_universe(cells=[cell_left, cell_right])
+   simulation = mcdc.Simulation()
+   simulation.set_model([cell_left, cell_right])
 
 
 Geometry Visualization
@@ -167,13 +169,15 @@ geometries before running a full transport simulation:
 
 .. code-block:: python3
 
-   mcdc.visualize(
-       "xz",                         # projection plane
+   simulation.visualize_model(
+       vis_plane="xz",               # projection plane
        y=0.0,                        # slice position
        x=[-10.0, 10.0],              # plot range
        z=[-5.0, 5.0],
        pixels=(400, 400),
        colors={fuel: "red", water: "blue"},
+       time=[0.0],
+       save_as=None,
    )
 
 This produces a pixel map showing which material fills each pixel.
@@ -182,7 +186,16 @@ argument:
 
 .. code-block:: python3
 
-   mcdc.visualize(..., time=np.linspace(0, 9, 19), save_as="geo_animation")
+   simulation.visualize_model(
+       vis_plane="xz",
+       y=0.0,
+       x=[-10.0, 10.0],
+       z=[-5.0, 5.0],
+       pixels=(400, 400),
+       colors={fuel: "red", water: "blue"},
+       time=np.linspace(0, 9, 19),
+       save_as="geo_animation",
+   )
 
 For details on moving surfaces and sources, see :ref:`cont_movement`.
 
diff --git a/docs/source/theory/k_eigenvalue.rst b/docs/source/theory/k_eigenvalue.rst
index 521261d26..cad27a655 100644
--- a/docs/source/theory/k_eigenvalue.rst
+++ b/docs/source/theory/k_eigenvalue.rst
@@ -53,7 +53,7 @@ Users configure eigenmode via:
 
 .. code-block:: python3
 
-   mcdc.settings.set_eigenmode(N_inactive=50, N_active=200, k_init=1.0)
+   simulation.settings.set_eigenmode(N_inactive=50, N_active=200, k_init=1.0)
 
 - ``N_inactive`` — Cycles discarded for fission source convergence.
 - ``N_active`` — Cycles used for tally accumulation.
diff --git a/docs/source/theory/variance_reduction.rst b/docs/source/theory/variance_reduction.rst
index 84a33183c..b424af08d 100644
--- a/docs/source/theory/variance_reduction.rst
+++ b/docs/source/theory/variance_reduction.rst
@@ -10,8 +10,8 @@ MC/DC provides several **variance reduction** (VR) techniques that
 reduce the statistical uncertainty per particle history without
 introducing bias.
 
-All techniques below are activated through the ``mcdc.simulation``
-interface.
+All techniques below are configured on an explicit
+:class:`mcdc.Simulation` instance.
 
 Implicit Capture
 -----------------
@@ -33,7 +33,7 @@ effective in highly absorbing media.
 
 .. code-block:: python3
 
-   mcdc.simulation.implicit_capture()
+   simulation.implicit_capture()
 
 .. note::
 
@@ -59,7 +59,10 @@ preserving the expected weight (unbiased).
 
 .. code-block:: python3
 
-   mcdc.simulation.global_weight_roulette(weight_threshold=0.25, weight_target=1.0)
+   simulation.global_weight_roulette(
+       weight_threshold=0.25,
+       weight_target=1.0,
+   )
 
 ``weight_threshold`` and ``weight_target`` should be chosen so that
 :math:`w_{\text{thresh}} < w_{\text{target}}`; a common ratio is
@@ -85,7 +88,7 @@ This reduces the variance of the fission source weight distribution.
 
 .. code-block:: python3
 
-   mcdc.simulation.weighted_emission(active=True, weight_target=1.0)
+   simulation.weighted_emission(active=True, weight_target=1.0)
 
 
 Population Control
@@ -102,7 +105,7 @@ rouletting low-weight ones, targeting a uniform weight close to
 
 .. code-block:: python3
 
-   mcdc.simulation.population_control()
+   simulation.population_control()
 
 Population control is typically combined with a time census
 (``set_time_census``) that checkpoints the particle population at
@@ -130,16 +133,19 @@ setup might use:
 
 .. code-block:: python3
 
-   mcdc.simulation.implicit_capture()
-   mcdc.simulation.global_weight_roulette(weight_threshold=0.25, weight_target=1.0)
+   simulation.implicit_capture()
+   simulation.global_weight_roulette(
+       weight_threshold=0.25,
+       weight_target=1.0,
+   )
 
 For time-dependent fission problems:
 
 .. code-block:: python3
 
-   mcdc.simulation.implicit_capture()
-   mcdc.simulation.weighted_emission(active=True, weight_target=1.0)
-   mcdc.simulation.population_control()
+   simulation.implicit_capture()
+   simulation.weighted_emission(active=True, weight_target=1.0)
+   simulation.population_control()
 
 The order of activation does not matter — MC/DC applies them in the
 correct transport-physics order internally.

From b6351d0b1dc7f88fcad1356dfa480452cd810d5a Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 31 Jul 2026 05:45:27 +0700
Subject: [PATCH 066/202] migrate to PyData Sphinx Theme

---
 .dockerignore                                 |   4 +-
 .github/pull_request_template.md              |   4 +-
 .gitignore                                    |   2 +-
 README.md                                     |  13 +-
 containers/Dockerfile                         |   2 +-
 containers/Dockerfile.cuda                    |   4 +-
 containers/Dockerfile.rocm                    |   4 +-
 docs/README.md                                |  14 +-
 docs/requirements-rtd.txt                     |   6 +-
 docs/source/_static/custom.css                |  16 --
 docs/source/_static/switcher.json             |  18 ++
 docs/source/_static/theme-toggle.js           |  40 +++++
 docs/source/_templates/copyright.html         |  10 ++
 docs/source/_templates/theme-toggle.html      |  10 ++
 docs/source/conf.py                           |  75 +++++++--
 .../container_development.rst}                |   0
 .../continuous_integration.rst}               |   8 +-
 .../index.rst                                 |  53 +++---
 .../architecture/acceleration.rst}            |   4 +-
 .../architecture}/gpu.rst                     |  10 +-
 .../developer_guide/architecture/index.rst    |  21 +++
 .../documentation/index.rst                   |   4 +
 .../documentation/philosophy.rst              |   6 +-
 .../documentation/sphinx.rst                  |  37 +++--
 docs/source/developer_guide/index.rst         |  22 +++
 docs/source/examples/c5g7_k_eigenvalue.rst    |   2 +-
 docs/source/examples/c5g7_transient.rst       |   2 +-
 docs/source/examples/fuel_array_packaged.rst  |   2 +-
 docs/source/examples/index.rst                |   4 +
 docs/source/examples/kobayashi_dog_leg.rst    |   2 +-
 docs/source/examples/kobayashi_td.rst         |   2 +-
 docs/source/examples/moving_pellet.rst        |   2 +-
 docs/source/examples/moving_source.rst        |   2 +-
 docs/source/examples/slab_shielding.rst       |   3 +-
 docs/source/examples/sphere_in_cube.rst       |   2 +-
 docs/source/images/home/DOE_logo.png          | Bin 120843 -> 0 bytes
 docs/source/images/home/NNSA_Logo.png         | Bin 302481 -> 0 bytes
 docs/source/images/home/SU.png                | Bin 167165 -> 0 bytes
 docs/source/images/home/berkeley-logo.png     | Bin 22419 -> 0 bytes
 docs/source/images/home/carre.png             | Bin 430266 -> 0 bytes
 docs/source/images/home/carre2.png            | Bin 611083 -> 0 bytes
 docs/source/images/home/cement-logo-1.png     | Bin 232890 -> 0 bytes
 docs/source/images/home/kobayashi.gif         | Bin 533351 -> 0 bytes
 docs/source/images/home/kobayishi-red.png     | Bin 67141 -> 0 bytes
 docs/source/images/home/ncsu-logo.png         | Bin 10588 -> 0 bytes
 docs/source/images/home/nd-logo.png           | Bin 89757 -> 0 bytes
 docs/source/images/home/osu-logo.png          | Bin 24458 -> 0 bytes
 docs/source/images/home/psaapiii.png          | Bin 22446 -> 0 bytes
 docs/source/images/home/psaapiv.png           | Bin 19388 -> 0 bytes
 docs/source/images/home/smr-mcdc.png          | Bin 150834 -> 0 bytes
 docs/source/images/home/ucsd-logo.png         | Bin 33734 -> 0 bytes
 docs/source/images/home/vanderbilt-logo.png   | Bin 47364 -> 0 bytes
 docs/source/images/user/af_slab_1.png         | Bin 30935 -> 0 bytes
 docs/source/images/user/af_slab_2.png         | Bin 32062 -> 0 bytes
 docs/source/images/user/c5g7.png              | Bin 4967636 -> 0 bytes
 docs/source/images/user/dragon.gif            | Bin 3498116 -> 0 bytes
 docs/source/images/user/j_slab_1.png          | Bin 50399 -> 0 bytes
 docs/source/images/user/j_slab_2.png          | Bin 28412 -> 0 bytes
 docs/source/images/user/kobayashi-white.png   | Bin 1045464 -> 0 bytes
 docs/source/images/user/sf_slab_1.png         | Bin 61936 -> 0 bytes
 docs/source/images/user/sf_slab_2.png         | Bin 28948 -> 0 bytes
 docs/source/index.rst                         | 154 +++++++++---------
 docs/source/project/index.rst                 |  16 ++
 docs/source/{ => project}/publications.rst    |   3 +-
 docs/source/reference/index.rst               |  20 +++
 .../python_api}/index.rst                     |   8 +-
 ...{cont_energy.rst => continuous_energy.rst} |   4 +-
 ...t_movement.rst => continuous_movement.rst} |   2 +-
 ...in_decomp.rst => domain_decomposition.rst} |   2 +-
 docs/source/theory/geometry.rst               |   4 +-
 docs/source/theory/index.rst                  |  32 ++--
 .../theory/{mc_basics.rst => monte_carlo.rst} |   4 +-
 ...{uq.rst => uncertainty_quantification.rst} |   2 +-
 docs/source/theory/variance_reduction.rst     |   2 +-
 .../theory/{ww.rst => weight_windows.rst}     |   2 +-
 docs/source/user/index.rst                    |  41 -----
 .../source/{user => user_guide}/container.rst |   0
 .../execution/batch_systems.rst}              |   2 +-
 .../{user => user_guide/execution}/cpu.rst    |  10 +-
 .../{user => user_guide/execution}/gpu.rst    |   2 +-
 docs/source/user_guide/execution/index.rst    |  20 +++
 docs/source/{user => user_guide}/faq.rst      |  19 ++-
 .../getting_started/first_simulation.rst}     |  15 +-
 .../user_guide/getting_started/index.rst      |  25 +++
 .../getting_started/installation.rst}         |  22 +--
 .../getting_started/what_is_mcdc.rst          |  57 +++++++
 docs/source/user_guide/index.rst              |  59 +++++++
 docs/source/{user => user_guide}/tallies.rst  |   3 +-
 .../{user => user_guide}/troubleshooting.rst  |   8 +-
 pyproject.toml                                |   6 +-
 .../data_library_generator/electron/README.md |   4 +-
 .../data_library_generator/neutron/README.md  |   4 +-
 92 files changed, 649 insertions(+), 313 deletions(-)
 create mode 100644 docs/source/_static/switcher.json
 create mode 100644 docs/source/_static/theme-toggle.js
 create mode 100644 docs/source/_templates/copyright.html
 create mode 100644 docs/source/_templates/theme-toggle.html
 rename docs/source/{contribution_guide/container-dev.rst => contributing/container_development.rst} (100%)
 rename docs/source/{contribution_guide/ci.rst => contributing/continuous_integration.rst} (87%)
 rename docs/source/{contribution_guide => contributing}/index.rst (87%)
 rename docs/source/{theory/ana.rst => developer_guide/architecture/acceleration.rst} (97%)
 rename docs/source/{theory => developer_guide/architecture}/gpu.rst (97%)
 create mode 100644 docs/source/developer_guide/architecture/index.rst
 rename docs/source/{contribution_guide => developer_guide}/documentation/index.rst (68%)
 rename docs/source/{contribution_guide => developer_guide}/documentation/philosophy.rst (95%)
 rename docs/source/{contribution_guide => developer_guide}/documentation/sphinx.rst (81%)
 create mode 100644 docs/source/developer_guide/index.rst
 delete mode 100644 docs/source/images/home/DOE_logo.png
 delete mode 100644 docs/source/images/home/NNSA_Logo.png
 delete mode 100644 docs/source/images/home/SU.png
 delete mode 100644 docs/source/images/home/berkeley-logo.png
 delete mode 100644 docs/source/images/home/carre.png
 delete mode 100644 docs/source/images/home/carre2.png
 delete mode 100644 docs/source/images/home/cement-logo-1.png
 delete mode 100644 docs/source/images/home/kobayashi.gif
 delete mode 100644 docs/source/images/home/kobayishi-red.png
 delete mode 100644 docs/source/images/home/ncsu-logo.png
 delete mode 100644 docs/source/images/home/nd-logo.png
 delete mode 100644 docs/source/images/home/osu-logo.png
 delete mode 100644 docs/source/images/home/psaapiii.png
 delete mode 100644 docs/source/images/home/psaapiv.png
 delete mode 100644 docs/source/images/home/smr-mcdc.png
 delete mode 100644 docs/source/images/home/ucsd-logo.png
 delete mode 100644 docs/source/images/home/vanderbilt-logo.png
 delete mode 100644 docs/source/images/user/af_slab_1.png
 delete mode 100644 docs/source/images/user/af_slab_2.png
 delete mode 100644 docs/source/images/user/c5g7.png
 delete mode 100644 docs/source/images/user/dragon.gif
 delete mode 100644 docs/source/images/user/j_slab_1.png
 delete mode 100644 docs/source/images/user/j_slab_2.png
 delete mode 100644 docs/source/images/user/kobayashi-white.png
 delete mode 100644 docs/source/images/user/sf_slab_1.png
 delete mode 100644 docs/source/images/user/sf_slab_2.png
 create mode 100644 docs/source/project/index.rst
 rename docs/source/{ => project}/publications.rst (99%)
 create mode 100644 docs/source/reference/index.rst
 rename docs/source/{pythonapi => reference/python_api}/index.rst (97%)
 rename docs/source/theory/{cont_energy.rst => continuous_energy.rst} (98%)
 rename docs/source/theory/{cont_movement.rst => continuous_movement.rst} (99%)
 rename docs/source/theory/{domain_decomp.rst => domain_decomposition.rst} (98%)
 rename docs/source/theory/{mc_basics.rst => monte_carlo.rst} (98%)
 rename docs/source/theory/{uq.rst => uncertainty_quantification.rst} (98%)
 rename docs/source/theory/{ww.rst => weight_windows.rst} (98%)
 delete mode 100644 docs/source/user/index.rst
 rename docs/source/{user => user_guide}/container.rst (100%)
 rename docs/source/{user/batch_scripts.rst => user_guide/execution/batch_systems.rst} (99%)
 rename docs/source/{user => user_guide/execution}/cpu.rst (81%)
 rename docs/source/{user => user_guide/execution}/gpu.rst (99%)
 create mode 100644 docs/source/user_guide/execution/index.rst
 rename docs/source/{user => user_guide}/faq.rst (87%)
 rename docs/source/{user/first_mcdc.rst => user_guide/getting_started/first_simulation.rst} (93%)
 create mode 100644 docs/source/user_guide/getting_started/index.rst
 rename docs/source/{install.rst => user_guide/getting_started/installation.rst} (95%)
 create mode 100644 docs/source/user_guide/getting_started/what_is_mcdc.rst
 create mode 100644 docs/source/user_guide/index.rst
 rename docs/source/{user => user_guide}/tallies.rst (98%)
 rename docs/source/{user => user_guide}/troubleshooting.rst (95%)

diff --git a/.dockerignore b/.dockerignore
index c64cfd509..6b088eb85 100644
--- a/.dockerignore
+++ b/.dockerignore
@@ -58,7 +58,6 @@ htmlcov
 
 # Documentation builds
 docs/build
-docs/source/pythonapi/generated/
 docs
 
 # Container artifacts
@@ -135,7 +134,6 @@ htmlcov
 
 # Documentation builds
 docs/build
-docs/source/pythonapi/generated/
 docs
 
 # Container artifacts
@@ -161,4 +159,4 @@ source_particles.h5
 
 # Regression test data
 dummy_nuclide.h5
-source_particles.h5
\ No newline at end of file
+source_particles.h5
diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md
index cf55e92fc..abf14f19f 100644
--- a/.github/pull_request_template.md
+++ b/.github/pull_request_template.md
@@ -19,8 +19,8 @@
     Put an `x` in all boxes once completed.
 -->
 
-- [ ] I have read the [contributing guide](https://mcdc.readthedocs.io/en/latest/contribution/index.html).
-- [ ] My code follows the [code style](https://mcdc.readthedocs.io/en/latest/contribution/index.html#code-styling) of this project.
+- [ ] I have read the [contributing guide](https://mcdc.readthedocs.io/en/latest/contributing/index.html).
+- [ ] My code follows the [code style](https://mcdc.readthedocs.io/en/latest/contributing/index.html#code-styling) of this project.
 - [ ] I have updated the documentation as needed. <!-- Delete if not applicable -->
 - [ ] I have updated `CHANGELOG.md` as needed. <!-- Delete if not applicable -->
 - [ ] I have added or updated tests to cover my changes. <!-- Delete if not applicable -->
diff --git a/.gitignore b/.gitignore
index 72f26787f..c92291229 100644
--- a/.gitignore
+++ b/.gitignore
@@ -58,7 +58,7 @@ pytestdebug.log
 
 # Documentation builds
 docs/build
-docs/source/pythonapi/generated/
+docs/source/reference/python_api/generated/
 dist/
 mcdc/_version.py
 
diff --git a/README.md b/README.md
index c4d4000ff..045efa334 100644
--- a/README.md
+++ b/README.md
@@ -36,17 +36,18 @@ pip install mcdc
 ```
 
 For development installation and additional options, see the
-[Installation Guide](https://mcdc.readthedocs.io/en/latest/install.html).
+[Installation Guide](https://mcdc.readthedocs.io/en/latest/user_guide/getting_started/installation.html).
 
 ## Documentation
 
 Complete documentation is available on
 [Read the Docs](https://mcdc.readthedocs.io/), including:
 
-- [Installation](https://mcdc.readthedocs.io/en/latest/install.html)
-- [User Guide](https://mcdc.readthedocs.io/en/latest/user/index.html)
-- [Python API Reference](https://mcdc.readthedocs.io/en/latest/pythonapi/index.html)
-- [Contribution Guide](https://mcdc.readthedocs.io/en/latest/contribution/index.html)
+- [User Guide](https://mcdc.readthedocs.io/en/latest/user_guide/index.html)
+- [Getting Started](https://mcdc.readthedocs.io/en/latest/user_guide/getting_started/index.html)
+- [API Reference](https://mcdc.readthedocs.io/en/latest/reference/python_api/index.html)
+- [Developer Guide](https://mcdc.readthedocs.io/en/latest/developer_guide/index.html)
+- [Contributing](https://mcdc.readthedocs.io/en/latest/contributing/index.html)
 
 ## Citing
 
@@ -56,7 +57,7 @@ references as appropriate:
 - **MC/DC Origins**
   I. Variansyah, et al. (2023). *Development of MC/DC: a performant,
   scalable, and portable Python-based Monte Carlo neutron transport code.*
-  Proceedings of the ANS Mathematics & Computation Conference 2025,
+  Proceedings of the ANS Mathematics & Computation Conference 2023,
   Niagara Falls, Canada.
   https://doi.org/10.48550/arXiv.2305.07636
 
diff --git a/containers/Dockerfile b/containers/Dockerfile
index da7cf4ac3..57a103cb1 100644
--- a/containers/Dockerfile
+++ b/containers/Dockerfile
@@ -1,6 +1,6 @@
 FROM python:3.11-slim
 
-LABEL org.opencontainers.image.source="https://github.com/CEMeNT-PSAAP/MCDC"
+LABEL org.opencontainers.image.source="https://github.com/mcdc-project/mcdc"
 LABEL org.opencontainers.image.description="MC/DC: Monte Carlo Dynamic Code"
 LABEL org.opencontainers.image.licenses="BSD-3-Clause"
 
diff --git a/containers/Dockerfile.cuda b/containers/Dockerfile.cuda
index d8f4943c5..00d74a541 100644
--- a/containers/Dockerfile.cuda
+++ b/containers/Dockerfile.cuda
@@ -1,6 +1,6 @@
 FROM nvidia/cuda:11.8.0-devel-ubuntu22.04
 
-LABEL org.opencontainers.image.source="https://github.com/CEMeNT-PSAAP/MCDC"
+LABEL org.opencontainers.image.source="https://github.com/mcdc-project/mcdc"
 LABEL org.opencontainers.image.description="MC/DC: Monte Carlo Dynamic Code (CUDA/GPU)"
 LABEL org.opencontainers.image.licenses="BSD-3-Clause"
 
@@ -49,4 +49,4 @@ COPY pyproject.toml .
 COPY . .
 RUN pip install --no-cache-dir -e ".[dev]"
 
-CMD ["bash"]
\ No newline at end of file
+CMD ["bash"]
diff --git a/containers/Dockerfile.rocm b/containers/Dockerfile.rocm
index 952ae40c5..05505cd62 100644
--- a/containers/Dockerfile.rocm
+++ b/containers/Dockerfile.rocm
@@ -1,6 +1,6 @@
 FROM rocm/dev-ubuntu-22.04:6.0
 
-LABEL org.opencontainers.image.source="https://github.com/CEMeNT-PSAAP/MCDC"
+LABEL org.opencontainers.image.source="https://github.com/mcdc-project/mcdc"
 LABEL org.opencontainers.image.description="MC/DC: Monte Carlo Dynamic Code (ROCm/GPU)"
 LABEL org.opencontainers.image.licenses="BSD-3-Clause"
 
@@ -50,4 +50,4 @@ COPY pyproject.toml .
 COPY . .
 RUN pip install --no-cache-dir -e ".[dev]"
 
-CMD ["bash"]
\ No newline at end of file
+CMD ["bash"]
diff --git a/docs/README.md b/docs/README.md
index 21284cd27..988f5ac11 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -1,10 +1,12 @@
-# MC/DC Documentation!
+# MC/DC Documentation
 
-To build these docs locally run the following:
-```bash 
-conda install sphinx==7.2.6
-pip install furo sphinx_toolbox
+To build the documentation locally, install MC/DC with its documentation
+dependencies from the repository root:
+
+```bash
+pip install -e ".[docs]"
+cd docs
 make html
 ```
 
-Then launch ``build/html/index.html`` with your browser of choice
\ No newline at end of file
+Then open `build/html/index.html` in your browser.
diff --git a/docs/requirements-rtd.txt b/docs/requirements-rtd.txt
index 59629f309..13675110a 100644
--- a/docs/requirements-rtd.txt
+++ b/docs/requirements-rtd.txt
@@ -1,8 +1,8 @@
-sphinx==7.2.6
-furo
+sphinx>=8,<10
+pydata-sphinx-theme>=0.20,<0.21
+sphinx-design>=0.6
 numpy
 numba
 matplotlib
 scipy
 h5py
-sphinx_toolbox
diff --git a/docs/source/_static/custom.css b/docs/source/_static/custom.css
index 025e49129..67d32c29e 100644
--- a/docs/source/_static/custom.css
+++ b/docs/source/_static/custom.css
@@ -9,19 +9,3 @@ dt.sig.sig-object.py > em.property {
 .simulation-members {
     margin-left: 30px;
 }
-
-/* Container styling */
-.admonition.tip {
-    border-left: 5px solid #ffde57; /* Python Yellow border */
-}
-
-/* Adding the Green Circle to the title */
-.admonition.tip > .admonition-title::before {
-    background-color: #ffde57;
-}
-
-/* Optional: Change title background to a light Python Yellow */
-.admonition.tip > .admonition-title {
-    background-color: #3776ab;
-    color: #ffffff;
-}
diff --git a/docs/source/_static/switcher.json b/docs/source/_static/switcher.json
new file mode 100644
index 000000000..3460b9166
--- /dev/null
+++ b/docs/source/_static/switcher.json
@@ -0,0 +1,18 @@
+[
+  {
+    "name": "dev",
+    "version": "dev",
+    "url": "https://mcdc.readthedocs.io/en/dev/"
+  },
+  {
+    "name": "latest",
+    "version": "latest",
+    "url": "https://mcdc.readthedocs.io/en/latest/"
+  },
+  {
+    "name": "stable",
+    "version": "stable",
+    "url": "https://mcdc.readthedocs.io/en/stable/",
+    "preferred": true
+  }
+]
diff --git a/docs/source/_static/theme-toggle.js b/docs/source/_static/theme-toggle.js
new file mode 100644
index 000000000..fe7f4bc8b
--- /dev/null
+++ b/docs/source/_static/theme-toggle.js
@@ -0,0 +1,40 @@
+document.addEventListener("DOMContentLoaded", () => {
+  const buttons = document.querySelectorAll(".mcdc-theme-toggle");
+  if (!buttons.length) {
+    return;
+  }
+
+  const root = document.documentElement;
+
+  const updateButtons = () => {
+    const darkMode = root.dataset.theme === "dark";
+    const nextMode = darkMode ? "light" : "dark";
+
+    buttons.forEach((button) => {
+      button.setAttribute("aria-label", `Switch to ${nextMode} mode`);
+      button.setAttribute("title", `Switch to ${nextMode} mode`);
+    });
+  };
+
+  buttons.forEach((button) => {
+    button.addEventListener("click", () => {
+      const nextMode = root.dataset.theme === "dark" ? "light" : "dark";
+
+      root.dataset.mode = nextMode;
+      root.dataset.theme = nextMode;
+      document.querySelectorAll(".dropdown-menu").forEach((menu) => {
+        menu.classList.toggle("dropdown-menu-dark", nextMode === "dark");
+      });
+
+      localStorage.setItem("mode", nextMode);
+      localStorage.setItem("theme", nextMode);
+      updateButtons();
+    });
+  });
+
+  new MutationObserver(updateButtons).observe(root, {
+    attributes: true,
+    attributeFilter: ["data-theme"],
+  });
+  updateButtons();
+});
diff --git a/docs/source/_templates/copyright.html b/docs/source/_templates/copyright.html
new file mode 100644
index 000000000..aad76875c
--- /dev/null
+++ b/docs/source/_templates/copyright.html
@@ -0,0 +1,10 @@
+{# Link the two institutions named in the MC/DC copyright notice. #}
+{% if show_copyright %}
+  <p class="copyright">
+    © Copyright 2023-2026,
+    Center for Exascale Monte Carlo Neutron Transport <a href="https://cement-psaap.github.io/">(CEMeNT)</a>,
+    Center for Advancing the Radiation Resilience of Electronics <a href="https://carre-psaapiv.org/">(CARRE)</a>,
+    and MC/DC contributors.
+    <br/>
+  </p>
+{% endif %}
diff --git a/docs/source/_templates/theme-toggle.html b/docs/source/_templates/theme-toggle.html
new file mode 100644
index 000000000..c8680325b
--- /dev/null
+++ b/docs/source/_templates/theme-toggle.html
@@ -0,0 +1,10 @@
+{# A two-state light/dark toggle that replaces the theme's dropdown. #}
+<button
+  class="mcdc-theme-toggle btn btn-sm nav-link pst-navbar-icon pst-js-only"
+  type="button"
+  aria-label="{{ _('Switch color mode') }}"
+  title="{{ _('Switch color mode') }}"
+>
+  <i class="fa-solid fa-sun fa-lg fa-fw only-light" aria-hidden="true"></i>
+  <i class="fa-solid fa-moon fa-lg fa-fw only-dark" aria-hidden="true"></i>
+</button>
diff --git a/docs/source/conf.py b/docs/source/conf.py
index 7cbd2f32f..dc9b6fdf7 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -40,18 +40,13 @@
     "sphinx.ext.autodoc",
     "sphinx.ext.napoleon",
     "sphinx.ext.autosummary",
-    "sphinx_toolbox.github",
-    "sphinx_toolbox.sidebar_links",
     "sphinx.ext.autosectionlabel",
+    "sphinx_design",
     "simulation_members",
 ]
 autosummary_generate = True
 autosectionlabel_prefix_document = True
 
-github_username = "CEMeNT-PSAAP"
-github_repository = "MCDC"
-github_url = "https://github.com/{github_username}/{github_repository}"
-
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ["_templates"]
 
@@ -61,16 +56,72 @@
 exclude_patterns = []
 
 # -- Options for HTML output -------------------------------------------------
-# The theme to use for HTML and HTML Help pages.  See the documentation for
-# a list of builtin themes.
-#
-html_theme = "furo"
+# The PyData Sphinx Theme provides the site-wide header, section navigation,
+# in-page table of contents, search, and light/dark mode.
+html_theme = "pydata_sphinx_theme"
+html_title = "MC/DC Documentation"
 html_logo = "images/home/mcdc.svg"
+html_favicon = "images/home/mcdc.svg"
+
+# Read the Docs provides the active version slug during hosted builds. Use the
+# development docs as the local-build default.
+docs_version = os.environ.get("READTHEDOCS_VERSION", "dev")
+switcher_json_url = (
+    "https://mcdc.readthedocs.io/en/latest/_static/switcher.json"
+    if os.environ.get("READTHEDOCS") == "True"
+    else "/_static/switcher.json"
+)
+
+html_theme_options = {
+    "navbar_align": "left",
+    "navbar_end": ["theme-toggle", "version-switcher", "navbar-icon-links"],
+    "navbar_persistent": ["search-button"],
+    "header_links_before_dropdown": 5,
+    "navigation_depth": 4,
+    "show_nav_level": 2,
+    "use_edit_page_button": True,
+    "switcher": {
+        "json_url": switcher_json_url,
+        "version_match": docs_version,
+    },
+    # Hosted builds share one version list from the latest documentation. Local
+    # builds use the copied static file when served from the HTML output root.
+    "check_switcher": False,
+    "logo": {
+        "alt_text": "MC/DC Documentation - Home",
+    },
+    "icon_links": [
+        {
+            "name": "GitHub",
+            "url": "https://github.com/mcdc-project/mcdc",
+            "icon": "fa-brands fa-square-github",
+            "type": "fontawesome",
+        },
+        {
+            "name": "PyPI",
+            "url": "https://pypi.org/project/mcdc/",
+            "icon": "fa-solid fa-box",
+            "type": "fontawesome",
+        },
+    ],
+}
+
+html_context = {
+    "github_user": "mcdc-project",
+    "github_repo": "mcdc",
+    "github_version": "dev",
+    "doc_path": "docs/source",
+}
 
-# html_permalinks = ['https://cement-psaap.github.io/', 'https://github.com/CEMeNT-PSAAP/MCDC']
+# The home page already provides purpose-based routing. Section pages use the
+# theme's default collapsible primary sidebar.
+html_sidebars = {
+    "index": [],
+}
 
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ["_static", "images/home"]
+html_static_path = ["_static"]
 html_css_files = ["custom.css"]
+html_js_files = ["theme-toggle.js"]
diff --git a/docs/source/contribution_guide/container-dev.rst b/docs/source/contributing/container_development.rst
similarity index 100%
rename from docs/source/contribution_guide/container-dev.rst
rename to docs/source/contributing/container_development.rst
diff --git a/docs/source/contribution_guide/ci.rst b/docs/source/contributing/continuous_integration.rst
similarity index 87%
rename from docs/source/contribution_guide/ci.rst
rename to docs/source/contributing/continuous_integration.rst
index 0fb31d7c0..c2943f376 100644
--- a/docs/source/contribution_guide/ci.rst
+++ b/docs/source/contributing/continuous_integration.rst
@@ -1,11 +1,11 @@
-.. _ci:
+.. _continuous_integration:
 
 .. highlight:: none
 
 Continuous Integration
 ======================
 
-We use `github actions <https://github.com/CEMeNT-PSAAP/MCDC/actions>`_ to host and run most of our CI tests and version release information.
+We use `GitHub Actions <https://github.com/mcdc-project/mcdc/actions>`_ to host and run most of our CI tests and version release information.
 We run pure python unit tests and regression testing in pure Python, pure Python + MPI, numba, numba + MPI, and numba+GPU+harmonize.
 When running regression tests we compare small particle count outputs to saved files in the testing directory.
 If the RNG seed has not changed the results should be deterministic.
@@ -14,7 +14,7 @@ If the RNG seed has not changed the results should be deterministic.
 GPU COE Machine
 ---------------
 
-CEMeNT currently has a `CI machine <https://github.com/CEMeNT-PSAAP/MCDC/settings/actions/runners>`_ on OSU's campus administered by the college of engineering HPC folks to do export controlled and GPU continuous integration.
+CEMeNT currently has a `CI machine <https://github.com/mcdc-project/mcdc/settings/actions/runners>`_ on OSU's campus administered by the college of engineering HPC folks to do export controlled and GPU continuous integration.
 It has a single Nvidia A2 (16GB VRAM) and an AMD EPYC 7313P 16-Core Processor with 64 GBs of RAM.
 This is a dedicated machine with no additional users other then CEMeNT staff.
 
@@ -38,4 +38,4 @@ The standard dev env for MC/DC install on this machine can be ascertained with
 
 Then MC/DC and harmonize can be installed there in the normal manner for GPU capabilities.
 The runner runs all the time in background of Joanna's account.
-Contact her with any issues or on instructions to set up your own runner!
\ No newline at end of file
+Contact her with any issues or on instructions to set up your own runner!
diff --git a/docs/source/contribution_guide/index.rst b/docs/source/contributing/index.rst
similarity index 87%
rename from docs/source/contribution_guide/index.rst
rename to docs/source/contributing/index.rst
index 7597598c4..0d33b4ebc 100644
--- a/docs/source/contribution_guide/index.rst
+++ b/docs/source/contributing/index.rst
@@ -1,39 +1,38 @@
-.. _contribution_guide:
+.. _contributing:
 
-==================
-Contribution Guide
-==================
+============
+Contributing
+============
 
-Thank you for looking to contribute to MC/DC! 
-We are really excited to see what you bring to this exciting open source project!
-Whether you are here to make a single PR and never return, or want to become a maintainer we are pumped to work with you.
-We have regular developers meetings for any and all who are interested to discuss contributions to this code base.
+This guide describes the repository workflow and quality checks for
+contributing to MC/DC. It is intended for both occasional contributors and
+project maintainers.
 
-This describes the processes of contributing to MC/DC for both internal (CEMeNT) and external developers.
-We make contributions to the ``dev`` branch of MC/DC.
-To get started making alterations in a cloned repo
+Start with the setup steps below. Use :doc:`continuous_integration` to
+understand automated checks and :doc:`container_development` when developing in
+the project container. For software architecture and documentation practices,
+see the :doc:`../developer_guide/index`.
 
-#. fork ``CEMeNT-PSAAP/MCDC`` to your github account
-#. ``git clone git@github.com:<YOUR_GITHUB>/MCDC.git``
-#. ``git switch dev``
-#. run install script which will install MC/DC as an editable package from this directory
+Contributions target the ``dev`` branch. To prepare a development checkout:
 
-Push some particles around!!!!
+#. Fork ``mcdc-project/mcdc`` to your GitHub account.
+#. ``git clone git@github.com:<YOUR_GITHUB>/mcdc.git``
+#. ``git switch dev``
+#. Run the installation script to install MC/DC as an editable package.
 
-Development Guides
-------------------
+Development Workflow
+--------------------
 
 .. toctree::
    :maxdepth: 1
 
-   documentation/index
-   ci
-   container-dev
+   continuous_integration
+   container_development
 
 MC/DC documentation is an important part of the project and evolves alongside
-the codebase. The :doc:`documentation/index` guide describes the documentation
-philosophy, writing guidelines, and the tools used to build and maintain the
-documentation.
+the codebase. The :doc:`../developer_guide/documentation/index` guide describes
+the documentation philosophy, writing guidelines, and the tools used to build
+and maintain the documentation.
 
 Please note our `code of conduct <https://github.com/mcdc-project/mcdc/blob/dev/CODE_OF_CONDUCT.md>`_, which we take seriously.
 
@@ -126,7 +125,8 @@ The input objects are defined as dataclasses in the ``mcdc/object_/`` directory:
 Testing
 -------
 
-Check out the :doc:`ci` for more info on how we run these tests automatically 
+See :doc:`continuous_integration` for more information on how we run these
+tests automatically.
 
 MC/DC has a robust testing suite that your changes must be able to pass before a PR is accepted.
 Unit tests for functions that have them are ran in a pure python from.
@@ -192,7 +192,8 @@ Documentation is a core part of MC/DC. Contributions that introduce new
 features, modify existing behavior, or change developer workflows should update
 the relevant documentation accordingly.
 
-See the :doc:`documentation/index` guide for documentation philosophy, writing
+See the :doc:`../developer_guide/documentation/index` guide for documentation
+philosophy, writing
 guidelines, and instructions for contributing to the documentation.
 
 
diff --git a/docs/source/theory/ana.rst b/docs/source/developer_guide/architecture/acceleration.rst
similarity index 97%
rename from docs/source/theory/ana.rst
rename to docs/source/developer_guide/architecture/acceleration.rst
index 7ed8fcc65..0ebe4738a 100644
--- a/docs/source/theory/ana.rst
+++ b/docs/source/developer_guide/architecture/acceleration.rst
@@ -1,4 +1,4 @@
-.. _ana:
+.. _acceleration:
 
 ============================
 Acceleration and Abstraction
@@ -45,7 +45,7 @@ The compilation pipeline differs by vendor:
 - **Nvidia**: Python → PTX (via ``numba.cuda``) → relocatable device code (via ``nvcc``) → linked shared library.
 - **AMD**: Python → LLVM-IR (via a `Numba-HIP patch <https://github.com/ROCm/numba-hip>`_) → relocatable device code (via ``hipcc`` / ``clang``) → linked shared library.
 
-For a detailed walkthrough of the compilation flow, see the :ref:`theory_gpu` section.
+For details about accelerator execution, see :ref:`architecture_gpu`.
 
 For more details, see:
 
diff --git a/docs/source/theory/gpu.rst b/docs/source/developer_guide/architecture/gpu.rst
similarity index 97%
rename from docs/source/theory/gpu.rst
rename to docs/source/developer_guide/architecture/gpu.rst
index d3c8db863..6b3e51130 100644
--- a/docs/source/theory/gpu.rst
+++ b/docs/source/developer_guide/architecture/gpu.rst
@@ -1,4 +1,4 @@
-.. _theory_gpu:
+.. _architecture_gpu:
 
 =================
 GPU Functionality
@@ -27,7 +27,7 @@ Nvidia Targets
 To compile to Nvidia GPU hardware-targets at runtime, we rely entirely on the Nvidia C-Compiler (`nvcc`).
 Current versions of Numba come with CUDA operability natively, but this is set to be deprecated in future releases in favor of a more modular approach where the Numba-CUDA package will be an optional separate feature.
 
-.. image:: ../images/theory/gpu_comp/nvcc_flow.png
+.. image:: ../../images/theory/gpu_comp/nvcc_flow.png
    :width: 800
    :alt: Simple proxy example describing how to compile device functions in Numba-Python with external C++ code for targeting Nvidia GPUs. In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize.
 
@@ -50,7 +50,7 @@ This compilation strategy also allows for the extension of functions defined in
 AMD Targets
 -----------
 
-Just in time compilation and execution to AMD devices are enabled as of `MC/DC v0.11.0 <https://github.com/CEMeNT-PSAAP/MCDC/tree/v0.11.0>`_.
+Just in time compilation and execution to AMD devices are enabled as of `MC/DC v0.11.0 <https://github.com/mcdc-project/mcdc/tree/v0.11.0>`_.
 Significant adaptations from the process of Nvidia compilation are required to target AMD GPUs.
 PTX is a proprietary Nvidia standard, so when targeting AMD GPUs, we rely on intermediate compiler representation (IR) from LLVM for an AMD GPU hardware-target (also called an LLVM target triple).
 AMD's compiler toolchain is based in the LLVM-Clang ecosystem, so we will be calling LLVM-Clang-based tools (e.g., ``hipcc`` is a wrapper function for ``clang``).
@@ -70,7 +70,7 @@ Every GPU program is technically a bound set of two complementary applications:
 To link external device code together for AMD hardware-targets, we have to unbundle these two programs, link the extra device functions (coming from Python) to the device side, then re-bundle the device and host functions back together.
 This process is done in LLVM-IR.
 
-.. image:: ../images/theory/gpu_comp/amd_flow.png
+.. image:: ../../images/theory/gpu_comp/amd_flow.png
    :width: 800
    :alt: Simple proxy example describing how to compile device functions in Numba-HIP with external C++ code to AMD GPU targets. In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize.
 
@@ -93,4 +93,4 @@ We begin compilation by
 As in the Nvidia compilation, non-implemented functions can be brought into the final program via the C++ source.
 This was required for MC/DC on AMD GPUs as vector operable atomics are not currently implemented in the Numba HIP port and thus must come from the C++ side.
 We hope that these more generic adaptations (relying on LLVM-Clang infrastructure instead of CUDA) will allow for greater extensibility as we move to target future accelerator platforms---namely, Intel GPUs.
-For compilation to Nvidia hardware-targets, we will still keep the PTX-based compilation structure.
\ No newline at end of file
+For compilation to Nvidia hardware-targets, we will still keep the PTX-based compilation structure.
diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
new file mode 100644
index 000000000..55e697c81
--- /dev/null
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -0,0 +1,21 @@
+.. _architecture:
+
+============
+Architecture
+============
+
+Architecture documentation explains how MC/DC translates flexible Python model
+definitions into high-performance particle-transport execution.
+
+Start with :doc:`acceleration` for an overview of the acceleration and code
+generation layers. Read :doc:`gpu` when working on accelerator execution or
+the Harmonize integration.
+
+Documentation of the explicit ``Simulation`` compilation pipeline, runtime data
+layout, and Numba design belongs in this section as those pages are developed.
+
+.. toctree::
+   :maxdepth: 1
+
+   acceleration
+   gpu
diff --git a/docs/source/contribution_guide/documentation/index.rst b/docs/source/developer_guide/documentation/index.rst
similarity index 68%
rename from docs/source/contribution_guide/documentation/index.rst
rename to docs/source/developer_guide/documentation/index.rst
index 4fa72dc1c..9dfd789e0 100644
--- a/docs/source/contribution_guide/documentation/index.rst
+++ b/docs/source/developer_guide/documentation/index.rst
@@ -11,6 +11,10 @@ and evolving the software.
 This section explains both the philosophy behind MC/DC's documentation and the
 tools used to build it.
 
+Read :doc:`philosophy` when deciding what information belongs in a page and how
+to layer it for different audiences. Read :doc:`sphinx` for source layout,
+reStructuredText, API generation, and local build instructions.
+
 .. toctree::
    :maxdepth: 1
 
diff --git a/docs/source/contribution_guide/documentation/philosophy.rst b/docs/source/developer_guide/documentation/philosophy.rst
similarity index 95%
rename from docs/source/contribution_guide/documentation/philosophy.rst
rename to docs/source/developer_guide/documentation/philosophy.rst
index 93f28c7cf..52ebecdd1 100644
--- a/docs/source/contribution_guide/documentation/philosophy.rst
+++ b/docs/source/developer_guide/documentation/philosophy.rst
@@ -14,9 +14,9 @@ scalable and maintainable as its software architecture.
 MC/DC adopts a layered documentation philosophy that balances usability,
 technical depth, and long-term maintainability across the entire project.
 
-This philosophy applies to all forms of MC/DC documentation, including the
-README, User Guide, Theory Guide, Python API documentation, examples,
-tutorials, and API docstrings.
+This philosophy applies to all forms of MC/DC documentation, including Getting
+Started, the User Guide, Examples, Theory and Methods, Reference, the Developer
+Guide, Contributing, the README, and API docstrings.
 
 The Layered Documentation Philosophy
 ------------------------------------
diff --git a/docs/source/contribution_guide/documentation/sphinx.rst b/docs/source/developer_guide/documentation/sphinx.rst
similarity index 81%
rename from docs/source/contribution_guide/documentation/sphinx.rst
rename to docs/source/developer_guide/documentation/sphinx.rst
index dbe8914dc..2750a8a3d 100644
--- a/docs/source/contribution_guide/documentation/sphinx.rst
+++ b/docs/source/developer_guide/documentation/sphinx.rst
@@ -21,7 +21,8 @@ We write files for Sphinx using a plaintext markup language called reStructuredT
 `Click here for a rst Primer <https://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html>`_.
 Sphinx builds an html file for every rst file in the documentation root directory and its subdirectories our documentation root directory is ``mcdc/docs/source/``. 
 The root document, ``index.rst``, serves as the welcome page. 
-The root directory also contains several subdirectories, each of which has its own ``index.rst`` file and several other rst files. 
+The root directory also contains task-oriented sections, each with an
+``index.rst`` landing page and related topic pages.
 It's useful to compare our rst files to their associated webpages to get a feel for how they translate.
 
 
@@ -58,13 +59,14 @@ The toctree
 
 Sphinx's main directive is the `toctree` directive, which generates a table of contents tree (toctree) with links to other webpages in the build.
 The listed documents should be named relative to the current document and excluding the .rst extension.
-For example, the MC/DC docs root directory contains ``index.rst``, ``install.rst``, and a subdirectory ``user/`` that also contains its own ``index.rst``. 
-The following on ``index.rst`` creates a table of contents on the main page with links to the install and user pages: 
+For example, the following on ``index.rst`` creates a table of contents on the
+main page with links to the main user-facing sections:
 ::
 
   .. toctree::
-     install
-     user/index
+     user_guide/index
+     theory/index
+     examples/index
 
 Sphinx will build an html file for all rst files in the source directory and its subdirectories.
 Sphinx will issue a warning if an html file isn't referenced in any toctree because that means that the generated webpage is not reachable through standard navigation.
@@ -78,7 +80,8 @@ Within MC/DC's source code, we document functions and classes using docstrings.
 For ``autodoc`` and ``autosummary`` to work, the docstrings within MC/DC's source code must be written in correct rst.
 
 The ``autodoc`` extension includes a set of directives to document different chunks of code (e.g., modules, functions, classes). 
-For example, below is the entire rst file that generates the :doc:`../../pythonapi/generated/mcdc.MaterialMG` page:
+For example, below is the entire rst file that generates the
+:doc:`../../reference/python_api/generated/mcdc.MaterialMG` page:
 
 .. code-block::
    
@@ -89,12 +92,16 @@ For example, below is the entire rst file that generates the :doc:`../../pythona
    
    .. autoclass:: MaterialMG
 
-(That in-line reference was created using :code:`:doc:\`../../pythonapi/generated/mcdc.MaterialMG\``, by the way).
+(That in-line reference was created using
+:code:`:doc:\`../../reference/python_api/generated/mcdc.MaterialMG\``, by the
+way).
 
 A rst file with an ``autodoc`` directive is required for each module or function that we would like to document.
 Rather than create all of these rst files by hand, we use the ``autosummary`` extension to do it for us.
 
-For example, let's look at the first ``autosummary`` directive in ``source/pythonapi/index.rst``, the file that governs the :doc:`../../pythonapi/index` page: 
+For example, consider the first ``autosummary`` directive in
+``source/reference/python_api/index.rst``, the file that governs the
+:doc:`../../reference/python_api/index` page:
 
 .. code-block::
 
@@ -104,9 +111,12 @@ For example, let's look at the first ``autosummary`` directive in ``source/pytho
       mcdc.MaterialMG
 
 This directive:
-  #. Generates two files in ``pythonapi/generated/``: ``mcdc.Material.rst`` and ``mcdc.MaterialMG.rst``.
+  #. Generates two files in ``reference/python_api/generated/``:
+     ``mcdc.Material.rst`` and ``mcdc.MaterialMG.rst``.
   #. Populates each file with the proper autoclass directive.
-  #. Creates a table on :doc:`../../pythonapi/index` with entries mcdc.Material and mcdc.MaterialMG that link to the respective generated pages. 
+  #. Creates a table on :doc:`../../reference/python_api/index` with entries
+     mcdc.Material and mcdc.MaterialMG that link to the respective generated
+     pages.
 
 
 Building Locally
@@ -115,9 +125,10 @@ Building Locally
 We can check our work with a local build. 
 Make sure you're in ``mcdc/docs/``:
 
-#. Both Sphinx and furo (the package we use for website theming) should have been installed with MC/DC.
+#. Both Sphinx and the PyData Sphinx Theme should have been installed with MC/DC.
    To check, type ``sphinx-build --version`` on the commandline.
-   If not installed, ``pip install sphinx furo``.
+   If they are not installed, run ``pip install -e ".[docs]"`` from the
+   repository root.
 #. With Sphinx installed, run ``make html``.
    This builds local html files in ``mcdc/docs/build/``.
 #. To launch your local html from the commandline, ``open build/html/index.html``.
@@ -139,5 +150,3 @@ Make sure you're in ``mcdc/docs/``:
 
 
 Once you're satisfied with your changes and have added any new modules to ``conf.py``, submit a PR!
-
-
diff --git a/docs/source/developer_guide/index.rst b/docs/source/developer_guide/index.rst
new file mode 100644
index 000000000..0a94de59a
--- /dev/null
+++ b/docs/source/developer_guide/index.rst
@@ -0,0 +1,22 @@
+.. _developer_guide:
+
+===============
+Developer Guide
+===============
+
+The Developer Guide explains how MC/DC works internally and how to extend or
+maintain its implementation.
+
+- Read :doc:`architecture/index` to understand the execution framework and
+  major internal layers.
+- Read :doc:`documentation/index` when writing or reviewing project
+  documentation.
+- Use the :doc:`../contributing/index` for repository setup, development
+  workflow, testing, and pull-request requirements.
+
+.. toctree::
+   :maxdepth: 2
+
+   architecture/index
+   documentation/index
+   Contributing <../contributing/index>
diff --git a/docs/source/examples/c5g7_k_eigenvalue.rst b/docs/source/examples/c5g7_k_eigenvalue.rst
index 06f82634c..9aeb74da1 100644
--- a/docs/source/examples/c5g7_k_eigenvalue.rst
+++ b/docs/source/examples/c5g7_k_eigenvalue.rst
@@ -42,7 +42,7 @@ section (materials, pins, assemblies, core, source, tallies, settings).
 Full Input
 ==========
 
-Click here to view the input file: `examples/c5g7/k-eigenvalue/input.py <https://github.com/CEMeNT-PSAAP/MCDC/blob/dev/examples/c5g7/k-eigenvalue/input.py>`_.
+Click here to view the input file: `examples/c5g7/k-eigenvalue/input.py <https://github.com/mcdc-project/mcdc/blob/dev/examples/c5g7/k-eigenvalue/input.py>`_.
 
 The complete input used for this example is embedded below:
 
diff --git a/docs/source/examples/c5g7_transient.rst b/docs/source/examples/c5g7_transient.rst
index e6dd5e722..d1f2a22c3 100644
--- a/docs/source/examples/c5g7_transient.rst
+++ b/docs/source/examples/c5g7_transient.rst
@@ -41,7 +41,7 @@ Refer to the embedded code below for the full implementation.
 Full Input
 ==========
 
-Click here to view the input file: `examples/c5g7/transient/input.py <https://github.com/CEMeNT-PSAAP/MCDC/blob/dev/examples/c5g7/transient/input.py>`_.
+Click here to view the input file: `examples/c5g7/transient/input.py <https://github.com/mcdc-project/mcdc/blob/dev/examples/c5g7/transient/input.py>`_.
 
 The complete input used for this example is embedded below:
 
diff --git a/docs/source/examples/fuel_array_packaged.rst b/docs/source/examples/fuel_array_packaged.rst
index eca9d00e4..c211ffa2f 100644
--- a/docs/source/examples/fuel_array_packaged.rst
+++ b/docs/source/examples/fuel_array_packaged.rst
@@ -167,7 +167,7 @@ Set ``visualize = True`` to render the CSG geometry with
 Full Input
 ==========
 
-Click here to view the input file: `examples/fuel_array_packaged/input.py <https://github.com/CEMeNT-PSAAP/MCDC/blob/dev/examples/fuel_array_packaged/input.py>`_.
+Click here to view the input file: `examples/fuel_array_packaged/input.py <https://github.com/mcdc-project/mcdc/blob/dev/examples/fuel_array_packaged/input.py>`_.
 
 The complete input used for this example is embedded below:
 
diff --git a/docs/source/examples/index.rst b/docs/source/examples/index.rst
index 9bbaaf7ac..ce8ea6417 100644
--- a/docs/source/examples/index.rst
+++ b/docs/source/examples/index.rst
@@ -18,6 +18,10 @@ the code shipped in-tree.  A **Step-by-Step Walkthrough** section breaks
 the input into annotated blocks, and a **What to try** box suggests
 parameter changes for further exploration.
 
+If you are learning MC/DC for the first time, complete the
+:doc:`../user_guide/getting_started/first_simulation` before using these examples as
+templates. For individual API details, consult the :doc:`../reference/index`.
+
 Basic Examples
 --------------
 
diff --git a/docs/source/examples/kobayashi_dog_leg.rst b/docs/source/examples/kobayashi_dog_leg.rst
index d9914ce2d..861107790 100644
--- a/docs/source/examples/kobayashi_dog_leg.rst
+++ b/docs/source/examples/kobayashi_dog_leg.rst
@@ -167,7 +167,7 @@ An isotropic, uniformly distributed source fills the
 Full Input
 ==========
 
-Click here to view the input file: `examples/kobayashi/input.py <https://github.com/CEMeNT-PSAAP/MCDC/blob/dev/examples/kobayashi/input.py>`_.
+Click here to view the input file: `examples/kobayashi/input.py <https://github.com/mcdc-project/mcdc/blob/dev/examples/kobayashi/input.py>`_.
 
 The complete input used for this example is embedded below:
 
diff --git a/docs/source/examples/kobayashi_td.rst b/docs/source/examples/kobayashi_td.rst
index be5dd59c0..9f1cd0781 100644
--- a/docs/source/examples/kobayashi_td.rst
+++ b/docs/source/examples/kobayashi_td.rst
@@ -52,7 +52,7 @@ population over time.
 Full Input
 ==========
 
-Click here to view the input file: `examples/kobayashi-TD/input.py <https://github.com/CEMeNT-PSAAP/MCDC/blob/dev/examples/kobayashi-TD/input.py>`_.
+Click here to view the input file: `examples/kobayashi-TD/input.py <https://github.com/mcdc-project/mcdc/blob/dev/examples/kobayashi-TD/input.py>`_.
 
 The complete input used for this example is embedded below:
 
diff --git a/docs/source/examples/moving_pellet.rst b/docs/source/examples/moving_pellet.rst
index 74d996283..56c8cab18 100644
--- a/docs/source/examples/moving_pellet.rst
+++ b/docs/source/examples/moving_pellet.rst
@@ -175,7 +175,7 @@ captures the fission rate as the pellet moves.
 Full Input
 ==========
 
-Click here to view the input file: `examples/moving_pellet/input.py <https://github.com/CEMeNT-PSAAP/MCDC/blob/dev/examples/moving_pellet/input.py>`_.
+Click here to view the input file: `examples/moving_pellet/input.py <https://github.com/mcdc-project/mcdc/blob/dev/examples/moving_pellet/input.py>`_.
 
 The complete input used for this example is embedded below:
 
diff --git a/docs/source/examples/moving_source.rst b/docs/source/examples/moving_source.rst
index 3a77e3c64..b1f43dcd2 100644
--- a/docs/source/examples/moving_source.rst
+++ b/docs/source/examples/moving_source.rst
@@ -145,7 +145,7 @@ generates an animated GIF.
 Full Input
 ==========
 
-Click here to view the input file: `examples/moving_source/input.py <https://github.com/CEMeNT-PSAAP/MCDC/blob/dev/examples/moving_source/input.py>`_.
+Click here to view the input file: `examples/moving_source/input.py <https://github.com/mcdc-project/mcdc/blob/dev/examples/moving_source/input.py>`_.
 
 The complete input used for this example is embedded below:
 
diff --git a/docs/source/examples/slab_shielding.rst b/docs/source/examples/slab_shielding.rst
index 5f060f5b9..0973be407 100644
--- a/docs/source/examples/slab_shielding.rst
+++ b/docs/source/examples/slab_shielding.rst
@@ -6,7 +6,8 @@ Slab Shielding
 
 This one-group fixed-source problem introduces the complete MC/DC workflow
 with two materials, two slab cells, an isotropic source, and a mesh flux
-tally. The :doc:`../user/first_mcdc` guide explains the input step by step.
+tally. The :doc:`../user_guide/getting_started/first_simulation` guide explains the input
+step by step.
 
 Full Input
 ----------
diff --git a/docs/source/examples/sphere_in_cube.rst b/docs/source/examples/sphere_in_cube.rst
index 2f65e228c..f1da9876b 100644
--- a/docs/source/examples/sphere_in_cube.rst
+++ b/docs/source/examples/sphere_in_cube.rst
@@ -132,7 +132,7 @@ Implicit capture is enabled to keep particles alive longer.
 Full Input
 ==========
 
-Click here to view the input file: `examples/sphere_in_cube/input.py <https://github.com/CEMeNT-PSAAP/MCDC/blob/dev/examples/sphere_in_cube/input.py>`_.
+Click here to view the input file: `examples/sphere_in_cube/input.py <https://github.com/mcdc-project/mcdc/blob/dev/examples/sphere_in_cube/input.py>`_.
 
 The complete input used for this example is embedded below:
 
diff --git a/docs/source/images/home/DOE_logo.png b/docs/source/images/home/DOE_logo.png
deleted file mode 100644
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diff --git a/docs/source/index.rst b/docs/source/index.rst
index 337bf0d30..e9d2d3a75 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -1,96 +1,96 @@
-.. MC/DC documentation master file
+:html_theme.sidebar_secondary.remove: true
 
 ======================================
 MC/DC: Monte Carlo Dynamic Code
 ======================================
 
 MC/DC is an open-source, Python-based Monte Carlo radiation transport software
-package that combines rapid methods development with scalable execution on modern
-high-performance computing systems. It supports execution across CPUs and GPUs
-while providing a flexible environment for developing and testing new transport
-algorithms.
-
-MC/DC is intended for researchers developing new Monte Carlo transport methods,
-including variance reduction techniques, sensitivity and uncertainty quantification
-methods, as well as high-performance computing algorithms. It also provides
-an accessible platform for students learning Monte Carlo radiation transport methods
-and modern code development.
-
-MC/DC supports continuous-energy and multi-group neutron transport calculations,
-including fixed-source and eigenvalue simulations on constructive solid geometry
-(CSG) models. For continuous-energy transport, MC/DC converts
-`ACE <https://nucleardata.lanl.gov/ace/>`_-format nuclear data libraries into its native
-`HDF5 <https://www.hdfgroup.org/solutions/hdf5/>`_ format. Photon, electron, proton,
-and other charged-particle transport capabilities are currently under development as
-part of the ongoing expansion of MC/DC into a comprehensive multi-particle radiation
-transport software package.
-
-MC/DC's Python interface enables rapid prototyping and iterative development,
-while its `Numba <https://numba.pydata.org>`_-based compilation framework delivers high
-performance without sacrificing portability.
-`Harmonize <https://github.com/CEMeNT-PSAAP/harmonize>`_ provides a GPU execution
-framework, and `MPI4Py <https://mpi4py.readthedocs.io/en/stable/>`_ enables
-distributed-memory parallelism across large HPC systems.
-In addition to desktop and workstation systems, MC/DC has been demonstrated on
-large heterogeneous supercomputers, including
-`Lassen <https://asc.llnl.gov/computers/historicdecommissioned-machines/lassen>`_
-(IBM POWER9 and NVIDIA Volta V100) and 
-`Tuolumne <https://warpx.readthedocs.io/en/latest/install/hpc/tuolumne.html>`_ (AMD
-MI300A APU).
-
-MC/DC was initiated by the Center for Exascale Monte Carlo Neutron Transport
-(`CEMeNT <https://cement-psaap.github.io>`_), a Focused Investigatory Center of
-the Predictive Science Academic Alliance Program–III
-(`PSAAP-III <https://psaap.llnl.gov>`_). Development is now led by the Center for
-Advancing the Radiation Resilience of Electronics
-(`CARRE <https://carre-psaapiv.org>`_), a Predictive Simulation Center of
-`PSAAP-IV <https://psaap.llnl.gov>`_.
-
-MC/DC is released under the
-`BSD 3-Clause <https://github.com/CEMeNT-PSAAP/MCDC/blob/main/LICENSE>`_
-license and welcomes community contributions through
-`GitHub <https://github.com/CEMeNT-PSAAP/MCDC>`_.
+package for rapid methods development and scalable execution on CPUs, GPUs,
+and modern high-performance computing systems. New to the project? Begin with
+:doc:`What is MC/DC? <user_guide/getting_started/what_is_mcdc>`.
 
+-------------
+Documentation
+-------------
 
+Choose the path that best matches what you want to accomplish.
 
-.. admonition:: Recommended citation
-   :class: tip
+.. grid:: 1 1 2 2
+   :gutter: 3
 
-   Morgan, Joanna Piper, et al. "Monte Carlo/Dynamic Code (MC/DC): An accelerated 
-   Python package for fully transient neutron transport and rapid methods development." 
-   Journal of Open Source Software 9.96 (2024): 6415. 
-   https://joss.theoj.org/papers/10.21105/joss.06415
+   .. grid-item-card:: :octicon:`book;2em` User Guide
+      :link: user_guide/index
+      :link-type: doc
+      :link-alt: Get started and learn how to use MC/DC
+      :class-card: sd-card-hover
+      :text-align: center
 
-------------------------------
-Contents
-------------------------------
+      Learn what MC/DC is, install it, run your first simulation, and follow
+      task-oriented guidance for everyday use.
 
-.. toctree::
-   :maxdepth: 1
-   :caption: User Documentation
+      +++
+      Start here :octicon:`arrow-right`
 
-   install
-   user/index
-   Python API Reference <pythonapi/index>
-   examples/index
+   .. grid-item-card:: :octicon:`beaker;2em` Theory and Methods
+      :link: theory/index
+      :link-type: doc
+      :link-alt: Study the transport theory and numerical methods in MC/DC
+      :class-card: sd-card-hover
+      :text-align: center
 
-.. toctree::
-   :maxdepth: 1
-   :caption: Developer Documentation
+      Study the transport theory, numerical algorithms, and acceleration
+      methods implemented in MC/DC.
 
-   contribution_guide/index
-   theory/index
+      +++
+      Explore the theory :octicon:`arrow-right`
 
-.. toctree::
-   :maxdepth: 1
-   :caption: References
+   .. grid-item-card:: :octicon:`code-square;2em` API Reference
+      :link: reference/python_api/index
+      :link-type: doc
+      :link-alt: Look up MC/DC Python classes and methods
+      :class-card: sd-card-hover
+      :text-align: center
+
+      Look up the classes, methods, arguments, and attributes available through
+      MC/DC's Python interface.
+
+      +++
+      Browse the API :octicon:`arrow-right`
+
+   .. grid-item-card:: :octicon:`tools;2em` Developer Guide
+      :link: developer_guide/index
+      :link-type: doc
+      :link-alt: Understand and contribute to MC/DC development
+      :class-card: sd-card-hover
+      :text-align: center
 
-   publications
+      Understand MC/DC's architecture, extend its implementation, and prepare
+      contributions to the project.
 
-.. sidebar-links::
-   :caption: External Links
-   :pypi: mcdc
-   :github:
+      +++
+      Develop MC/DC :octicon:`arrow-right`
 
-   CARRE <https://carre-psaapiv.org/>
-   CEMeNT <https://cement-psaap.github.io>
+More resources
+--------------
+
+- Learn from complete input decks in :doc:`examples/index`.
+- Follow the contribution workflow in :doc:`contributing/index`.
+- Find citation and publication information in :doc:`project/index`.
+
+.. admonition:: Recommended citation
+   :class: tip
+
+   Morgan, Joanna Piper, et al. "Monte Carlo/Dynamic Code (MC/DC): An accelerated
+   Python package for fully transient neutron transport and rapid methods development."
+   *Journal of Open Source Software* 9.96 (2024): 6415.
+   https://doi.org/10.21105/joss.06415
+
+.. toctree::
+   :hidden:
+   :maxdepth: 2
+
+   user_guide/index
+   theory/index
+   reference/index
+   developer_guide/index
+   project/index
diff --git a/docs/source/project/index.rst b/docs/source/project/index.rst
new file mode 100644
index 000000000..6659011bf
--- /dev/null
+++ b/docs/source/project/index.rst
@@ -0,0 +1,16 @@
+.. _project:
+
+=======
+Project
+=======
+
+Project information collects material about MC/DC as a research software
+project rather than instructions for using or developing the code.
+
+Use :doc:`publications` to find overview and method-specific references for
+published work.
+
+.. toctree::
+   :maxdepth: 1
+
+   publications
diff --git a/docs/source/publications.rst b/docs/source/project/publications.rst
similarity index 99%
rename from docs/source/publications.rst
rename to docs/source/project/publications.rst
index eaf986a88..c504117b0 100644
--- a/docs/source/publications.rst
+++ b/docs/source/project/publications.rst
@@ -1,4 +1,4 @@
-.. _pubs:
+.. _publications:
 
 =============
 Publications
@@ -80,4 +80,3 @@ Miscellany
 - Variansyah, Ilham, and Ryan G. McClarren. “High-fidelity treatment for object movement in time-dependent Monte Carlo transport simulations.” In International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering. Niagara Falls, Ontario, Canada (2023). Preprint: https://doi.org/10.48550/arXiv.2305.07641
 
 - Variansyah, Ilham, and Ryan G. McClarren. “An effective initial particle sampling technique for Monte Carlo reactor transient simulations.” In International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering. Niagara Falls, Ontario, Canada (2023). Preprint: https://doi.org/10.48550/arXiv.2305.07646
-
diff --git a/docs/source/reference/index.rst b/docs/source/reference/index.rst
new file mode 100644
index 000000000..023846db3
--- /dev/null
+++ b/docs/source/reference/index.rst
@@ -0,0 +1,20 @@
+.. _reference:
+
+=============
+API Reference
+=============
+
+Reference documentation provides precise descriptions of MC/DC's public
+interfaces. Use it when you know what object or operation you need and want its
+accepted arguments, attributes, or behavior.
+
+The :doc:`python_api/index` documents the classes used to construct, configure,
+compile, visualize, and run a simulation.
+
+.. toctree::
+   :maxdepth: 1
+
+   Python API <python_api/index>
+
+For guided model construction, begin with the
+:doc:`../user_guide/getting_started/first_simulation` instead.
diff --git a/docs/source/pythonapi/index.rst b/docs/source/reference/python_api/index.rst
similarity index 97%
rename from docs/source/pythonapi/index.rst
rename to docs/source/reference/python_api/index.rst
index c59fd01b8..1dd2dc234 100644
--- a/docs/source/pythonapi/index.rst
+++ b/docs/source/reference/python_api/index.rst
@@ -1,8 +1,8 @@
-.. _pythonapi:
+.. _python_api:
 
-====================
-Python API Reference
-====================
+==========
+Python API
+==========
 
 The MC/DC public API is centered on :class:`mcdc.Simulation`. A simulation owns
 the model geometry and material, sources, tallies, settings, transport
diff --git a/docs/source/theory/cont_energy.rst b/docs/source/theory/continuous_energy.rst
similarity index 98%
rename from docs/source/theory/cont_energy.rst
rename to docs/source/theory/continuous_energy.rst
index 7fe8aa35f..8004100ca 100644
--- a/docs/source/theory/cont_energy.rst
+++ b/docs/source/theory/continuous_energy.rst
@@ -1,4 +1,4 @@
-.. _cont_energy:
+.. _continuous_energy:
 
 =================
 Continuous Energy
@@ -177,4 +177,4 @@ The key HDF5 structure expected by MC/DC is:
 
 A converter from OpenMC's ``IncidentNeutron`` HDF5 format to this schema is
 a planned future addition.  Contributions are welcome — see
-`Issue #333 <https://github.com/CEMeNT-PSAAP/MCDC/issues/333>`_.
+`Issue #333 <https://github.com/mcdc-project/mcdc/issues/333>`_.
diff --git a/docs/source/theory/cont_movement.rst b/docs/source/theory/continuous_movement.rst
similarity index 99%
rename from docs/source/theory/cont_movement.rst
rename to docs/source/theory/continuous_movement.rst
index 0b484115d..c943c7113 100644
--- a/docs/source/theory/cont_movement.rst
+++ b/docs/source/theory/continuous_movement.rst
@@ -1,4 +1,4 @@
-.. _cont_movement:
+.. _continuous_movement:
 
 ===================
 Continuous Movement
diff --git a/docs/source/theory/domain_decomp.rst b/docs/source/theory/domain_decomposition.rst
similarity index 98%
rename from docs/source/theory/domain_decomp.rst
rename to docs/source/theory/domain_decomposition.rst
index b0b0edb7d..be19d0f25 100644
--- a/docs/source/theory/domain_decomp.rst
+++ b/docs/source/theory/domain_decomposition.rst
@@ -1,4 +1,4 @@
-.. _dd:
+.. _domain_decomposition:
 
 ====================
 Domain Decomposition
diff --git a/docs/source/theory/geometry.rst b/docs/source/theory/geometry.rst
index 872430870..e3e1435af 100644
--- a/docs/source/theory/geometry.rst
+++ b/docs/source/theory/geometry.rst
@@ -197,7 +197,7 @@ argument:
        save_as="geo_animation",
    )
 
-For details on moving surfaces and sources, see :ref:`cont_movement`.
+For details on moving surfaces and sources, see :ref:`continuous_movement`.
 
 
 Moving Surfaces
@@ -212,4 +212,4 @@ Any surface can be given a piecewise-constant velocity using the
 
 MC/DC solves for the exact intersection of a particle trajectory with
 the moving surface — no time-step discretization error is introduced.
-For the mathematical formulation, see :ref:`cont_movement`.
+For the mathematical formulation, see :ref:`continuous_movement`.
diff --git a/docs/source/theory/index.rst b/docs/source/theory/index.rst
index dd40c302f..15803d817 100644
--- a/docs/source/theory/index.rst
+++ b/docs/source/theory/index.rst
@@ -1,13 +1,15 @@
 .. _theory:
 
-============
-Theory Guide
-============
+==================
+Theory and Methods
+==================
 
-We provided a brief theory guide into the methods, algorithms, and compilation
-schemes in MC/DC.
+Theory and Methods explains the physical models, mathematical formulations, and
+numerical algorithms implemented in MC/DC. Use these pages to understand why a
+method works; use the :doc:`../user_guide/index` to learn how to configure it
+and the :doc:`../developer_guide/index` for software implementation details.
 
-New to Monte Carlo transport?  Start with :ref:`mc_basics` for the
+New to Monte Carlo transport? Start with :ref:`monte_carlo` for the
 fundamentals and :ref:`geometry` for how MC/DC represents problem domains.
 Then explore the advanced topics below.
 
@@ -20,7 +22,7 @@ Fundamentals
 .. toctree::
    :maxdepth: 1
 
-   mc_basics
+   monte_carlo
    geometry
    k_eigenvalue
 
@@ -31,19 +33,17 @@ Advanced Methods
    :maxdepth: 1
 
    variance_reduction
-   ana
    iqmc
-   ww
-   uq
+   weight_windows
+   uncertainty_quantification
    compressed_sensing
 
-Implementation
---------------
+Transport Models
+----------------
 
 .. toctree::
    :maxdepth: 1
 
-   gpu
-   cont_energy
-   domain_decomp
-   cont_movement
+   continuous_energy
+   domain_decomposition
+   continuous_movement
diff --git a/docs/source/theory/mc_basics.rst b/docs/source/theory/monte_carlo.rst
similarity index 98%
rename from docs/source/theory/mc_basics.rst
rename to docs/source/theory/monte_carlo.rst
index 1b76a680a..911cb3af0 100644
--- a/docs/source/theory/mc_basics.rst
+++ b/docs/source/theory/monte_carlo.rst
@@ -1,4 +1,4 @@
-.. _mc_basics:
+.. _monte_carlo:
 
 ============================
 Monte Carlo Transport Basics
@@ -118,7 +118,7 @@ The relative standard deviation
 
 - :ref:`variance_reduction` — implicit capture, weight roulette,
   population control.
-- :ref:`ww` — weight windows.
+- :ref:`weight_windows` — weight windows.
 - :ref:`iqmc` — quasi-Monte Carlo methods for  :math:`O((\log N)^d / N)`
   convergence.
 
diff --git a/docs/source/theory/uq.rst b/docs/source/theory/uncertainty_quantification.rst
similarity index 98%
rename from docs/source/theory/uq.rst
rename to docs/source/theory/uncertainty_quantification.rst
index 96e07f39d..52d7a64de 100644
--- a/docs/source/theory/uq.rst
+++ b/docs/source/theory/uncertainty_quantification.rst
@@ -1,4 +1,4 @@
-.. _uq:
+.. _uncertainty_quantification:
 
 ==========================
 Uncertainty Quantification
diff --git a/docs/source/theory/variance_reduction.rst b/docs/source/theory/variance_reduction.rst
index b424af08d..7802e1b47 100644
--- a/docs/source/theory/variance_reduction.rst
+++ b/docs/source/theory/variance_reduction.rst
@@ -120,7 +120,7 @@ time-dependent) target weights and bounds.  They combine splitting and
 roulette to focus computational effort in regions of high importance.
 
 MC/DC supports both user-defined and automatically generated weight
-windows.  See :ref:`ww` for a full description of the available
+windows. See :ref:`weight_windows` for a full description of the available
 strategies (``WW_USER`` and ``WW_PREVIOUS``) and modification schemes
 (``WW_MIN`` and ``WW_WOLLABER``).
 
diff --git a/docs/source/theory/ww.rst b/docs/source/theory/weight_windows.rst
similarity index 98%
rename from docs/source/theory/ww.rst
rename to docs/source/theory/weight_windows.rst
index 33701163e..d61f40d12 100644
--- a/docs/source/theory/ww.rst
+++ b/docs/source/theory/weight_windows.rst
@@ -1,4 +1,4 @@
-.. _ww:
+.. _weight_windows:
 
 ===============
 Weight Windows
diff --git a/docs/source/user/index.rst b/docs/source/user/index.rst
deleted file mode 100644
index 00005803c..000000000
--- a/docs/source/user/index.rst
+++ /dev/null
@@ -1,41 +0,0 @@
-.. _users:
-
-============
-User's Guide
-============
-
-The User's Guide explains how to build a model with MC/DC's public Python
-objects, attach it to a :class:`mcdc.Simulation`, configure settings and 
-transport techniques, and run it. Additional guides describe how
-to execute the same input script on CPUs and GPUs, with or without MPI.
-
-These instructions assume MC/DC is installed in an active Python environment
-appropriate for your system.
-
-Getting Started
----------------
-
-.. toctree::
-   :maxdepth: 1
-
-   first_mcdc
-   tallies
-
-Execution Modes
----------------
-
-.. toctree::
-   :maxdepth: 1
-
-   cpu
-   gpu
-   batch_scripts
-
-Help & Support
---------------
-
-.. toctree::
-   :maxdepth: 1
-
-   faq
-   troubleshooting
diff --git a/docs/source/user/container.rst b/docs/source/user_guide/container.rst
similarity index 100%
rename from docs/source/user/container.rst
rename to docs/source/user_guide/container.rst
diff --git a/docs/source/user/batch_scripts.rst b/docs/source/user_guide/execution/batch_systems.rst
similarity index 99%
rename from docs/source/user/batch_scripts.rst
rename to docs/source/user_guide/execution/batch_systems.rst
index 53b18538b..bfc3cf458 100644
--- a/docs/source/user/batch_scripts.rst
+++ b/docs/source/user_guide/execution/batch_systems.rst
@@ -1,4 +1,4 @@
-.. _batch_scripts:
+.. _batch_systems:
 
 =================
 Batch Job Scripts
diff --git a/docs/source/user/cpu.rst b/docs/source/user_guide/execution/cpu.rst
similarity index 81%
rename from docs/source/user/cpu.rst
rename to docs/source/user_guide/execution/cpu.rst
index 41a3f4436..76c9f9436 100644
--- a/docs/source/user/cpu.rst
+++ b/docs/source/user_guide/execution/cpu.rst
@@ -1,5 +1,5 @@
 
-.. _cpu:
+.. _cpu_execution:
 
 =====================
 Running MC/DC on CPUs
@@ -9,7 +9,7 @@ Executing MC/DC in something like a jupyter notebook is possible but not recomme
 especially when using MPI and/or Numba.
 The instructions below assume you have an existing MC/DC installation.
 MPI can be quite tricky to configure if on an HPC; if you're having trouble,
-consult our :ref:`install`, your HPC admin, or our `GitHub issues page <https://github.com/CEMeNT-PSAAP/MCDC/issues>`_.
+consult our :ref:`installation`, your HPC admin, or our `GitHub issues page <https://github.com/mcdc-project/mcdc/issues>`_.
 
 Pure Python Mode
 ----------------
@@ -31,7 +31,8 @@ When running in Numba mode a significant amount of time is taken compiling Pytho
 Only the functions used in a specific simulation will be compiled.
 These binaries will be cached, meaning that in subsequent runs of the same simulation the compilation step can be avoided.
 The cache can be used as an effective ahead-of-time compilation scheme where binaries can be compiled once and shared between machines.
-For more information on caching see :ref:`contribution_guide/index:Caching <contribution_guide/index:Caching>` and `Numba Caching <https://numba.readthedocs.io/en/stable/developer/caching.html>`_.
+For more information on caching, see :ref:`contributing/index:Caching` and
+`Numba Caching <https://numba.readthedocs.io/en/stable/developer/caching.html>`_.
 
 MC/DC also has the ability to run Numba in a debugging mode.
 This will result in less performant code and longer compile times but will allow for better error messages from Numba and other packages.
@@ -41,7 +42,8 @@ This will result in less performant code and longer compile times but will allow
     python input.py --mode=numba_debug
 
 
-For more information on the exact behavior of this option see :ref:`contribution_guide/index:Debugging <contribution_guide/index:Debugging>`
+For more information on the exact behavior of this option, see
+:ref:`contributing/index:Debugging`.
 
 Using MPI
 ---------
diff --git a/docs/source/user/gpu.rst b/docs/source/user_guide/execution/gpu.rst
similarity index 99%
rename from docs/source/user/gpu.rst
rename to docs/source/user_guide/execution/gpu.rst
index ab0d1234c..704a19d8d 100644
--- a/docs/source/user/gpu.rst
+++ b/docs/source/user_guide/execution/gpu.rst
@@ -1,5 +1,5 @@
 
-.. _gpu:
+.. _gpu_execution:
 
 =====================
 Running MC/DC on GPUs
diff --git a/docs/source/user_guide/execution/index.rst b/docs/source/user_guide/execution/index.rst
new file mode 100644
index 000000000..b5958ad74
--- /dev/null
+++ b/docs/source/user_guide/execution/index.rst
@@ -0,0 +1,20 @@
+.. _execution:
+
+=========
+Execution
+=========
+
+These guides explain how to run the same MC/DC input on different hardware and
+computing environments.
+
+- Start with :doc:`cpu` for local execution, Numba modes, and MPI.
+- Use :doc:`gpu` when targeting supported NVIDIA or AMD accelerators.
+- Use :doc:`batch_systems` when submitting calculations through a scheduler on
+  an HPC system.
+
+.. toctree::
+   :maxdepth: 1
+
+   cpu
+   gpu
+   batch_systems
diff --git a/docs/source/user/faq.rst b/docs/source/user_guide/faq.rst
similarity index 87%
rename from docs/source/user/faq.rst
rename to docs/source/user_guide/faq.rst
index 671c7375a..e1dba8b3f 100644
--- a/docs/source/user/faq.rst
+++ b/docs/source/user_guide/faq.rst
@@ -20,10 +20,10 @@ linux-ppc64 (IBM POWER9), linux-nvidia-cuda, and linux-amd-rocm.
 **Should I use pip or conda to install MC/DC?**
 
 For **personal machines and simple setups**, ``pip`` inside a ``venv`` is the easiest route
-(see :ref:`install:Installing with pip`).
+(see :ref:`user_guide/getting_started/installation:Installing with pip`).
 For **HPCs or non-standard hardware** (e.g., POWER9 on Lassen, or when mpi4py is
 troublesome), a **conda environment** with the ``install.sh`` script is more robust
-(see :ref:`install:Installing MC/DC via conda`).
+(see :ref:`user_guide/getting_started/installation:Installing MC/DC via conda`).
 
 .. list-table:: pip vs. conda at a glance
    :widths: 30 35 35
@@ -81,7 +81,8 @@ Load the correct MPI module first, then install from source:
    CC=mpicc pip install --no-binary mpi4py mpi4py
 
 Or use the conda path with ``bash install.sh --hpc``, which handles this automatically.
-See :ref:`user/troubleshooting:Building mpi4py from Source` for more details.
+See :ref:`user_guide/troubleshooting:Building mpi4py from Source` for more
+details.
 
 **I get Numba version errors or** ``TypingError`` **on older Numba versions.**
 
@@ -93,7 +94,8 @@ If you are on an older version, upgrade:
    pip install 'numba>=0.60.0'
 
 If your system constrains the Numba version (e.g., due to CUDA toolkit compatibility),
-see :ref:`user/troubleshooting:Numba Version Compatibility` for patching guidance.
+see :ref:`user_guide/troubleshooting:Numba Version Compatibility` for patching
+guidance.
 
 Running Simulations
 -------------------
@@ -105,7 +107,8 @@ Running Simulations
    mpiexec -n <nprocs> python input.py --mode=numba
 
 On HPCs, use the appropriate launcher (``srun``, ``jsrun``, ``flux run``).
-See :ref:`user/batch_scripts:Batch Job Scripts` for ready-to-use templates.
+See :ref:`user_guide/execution/batch_systems:Batch Job Scripts` for ready-to-use
+templates.
 
 **My simulation is very slow — what should I check?**
 
@@ -116,7 +119,7 @@ See :ref:`user/batch_scripts:Batch Job Scripts` for ready-to-use templates.
 
 **I see** ``SyntaxWarning: invalid escape sequence`` **on import.**
 
-This is a known cosmetic warning in some older releases (see `#211 <https://github.com/CEMeNT-PSAAP/MCDC/issues/211>`_).
+This is a known cosmetic warning in some older releases (see `#211 <https://github.com/mcdc-project/mcdc/issues/211>`_).
 It does not affect simulation results.
 Updating to the latest MC/DC version resolves it.
 
@@ -135,7 +138,9 @@ Use ``h5py`` to read them:
        print(list(f.keys()))                    # ['runtime', 'tallies']
        print(list(f["tallies"].keys()))          # list of tally names
 
-See the post-processing section in :ref:`user/first_mcdc:First MC/DC Simulation` for a complete example.
+See the post-processing section in
+:ref:`user_guide/getting_started/first_simulation:First MC/DC Simulation` for a complete
+example.
 
 **What visualization tools work with MC/DC output?**
 
diff --git a/docs/source/user/first_mcdc.rst b/docs/source/user_guide/getting_started/first_simulation.rst
similarity index 93%
rename from docs/source/user/first_mcdc.rst
rename to docs/source/user_guide/getting_started/first_simulation.rst
index 99d3c60ca..e13506a12 100644
--- a/docs/source/user/first_mcdc.rst
+++ b/docs/source/user_guide/getting_started/first_simulation.rst
@@ -1,10 +1,10 @@
-.. _first_mcdc:
+.. _first_simulation:
 
 ======================
 First MC/DC Simulation
 ======================
 
-This guide constructs and runs a one-group shielding calculation. It assumes
+This tutorial constructs and runs a one-group shielding calculation. It assumes
 familiarity with the basic concepts of Monte Carlo radiation transport.
 
 Monte Carlo transport inputs are generally assembled from the same core
@@ -193,7 +193,7 @@ Complete Input
 The complete runnable input is embedded directly from
 ``examples/slab_shielding/input.py``:
 
-.. literalinclude:: ../../../examples/slab_shielding/input.py
+.. literalinclude:: ../../../../examples/slab_shielding/input.py
    :language: python
    :linenos:
 
@@ -230,8 +230,9 @@ Enter the problem directory, then run the input in pure Python mode:
    python input.py
 
 Pure Python mode avoids compilation overhead and is suitable for checking a
-small model. For accelerated or parallel calculations, see :doc:`cpu`,
-:doc:`gpu`, and :doc:`batch_scripts`.
+small model. For accelerated or parallel calculations, see
+:doc:`../execution/cpu`, :doc:`../execution/gpu`, and
+:doc:`../execution/batch_systems`.
 
 Post-processing
 ---------------
@@ -240,7 +241,7 @@ MC/DC writes tally results and runtime information to HDF5. The companion
 script reads the spatial grid, normalizes the flux and standard deviation by
 the mesh-bin widths, and plots the result:
 
-.. literalinclude:: ../../../examples/slab_shielding/process-output.py
+.. literalinclude:: ../../../../examples/slab_shielding/process-output.py
    :language: python
    :linenos:
 
@@ -267,5 +268,5 @@ After running the original problem, useful variations include:
 - Add an energy group or another spatial region.
 - Add a surface-crossing tally at the material interface.
 
-See :doc:`../examples/index` for examples involving lattices, moving geometry,
+See :doc:`../../examples/index` for examples involving lattices, moving geometry,
 time-dependent transport, and reactor benchmarks.
diff --git a/docs/source/user_guide/getting_started/index.rst b/docs/source/user_guide/getting_started/index.rst
new file mode 100644
index 000000000..97e5e7bb3
--- /dev/null
+++ b/docs/source/user_guide/getting_started/index.rst
@@ -0,0 +1,25 @@
+.. _getting_started:
+
+===============
+Getting Started
+===============
+
+Getting Started is the shortest path from learning what MC/DC is to completing
+a working transport calculation.
+
+Begin with :doc:`what_is_mcdc` for an overview of the project and its intended
+uses. Then install MC/DC and follow the first-simulation tutorial to build,
+visualize, run, and post-process a complete transport problem.
+
+.. toctree::
+   :maxdepth: 1
+
+   what_is_mcdc
+   installation
+   first_simulation
+
+After completing these pages:
+
+- Continue through the :doc:`../index` for task-oriented guidance.
+- Browse :doc:`../../examples/index` for complete models.
+- Consult the :doc:`../../reference/index` for exact API behavior.
diff --git a/docs/source/install.rst b/docs/source/user_guide/getting_started/installation.rst
similarity index 95%
rename from docs/source/install.rst
rename to docs/source/user_guide/getting_started/installation.rst
index 9750d3733..e671c73a7 100644
--- a/docs/source/install.rst
+++ b/docs/source/user_guide/getting_started/installation.rst
@@ -1,8 +1,8 @@
-.. _install:
+.. _installation:
 
-===================
-Installation Guide
-===================
+============
+Installation
+============
 
 Whether installing MC/DC as a user or from source as a developer, 
 we recommend doing so using an environment manager like venv or conda.
@@ -67,7 +67,7 @@ Installing from Source
 If you would like to execute a version of MC/DC from a specific branch or 
 *do* plan to develop in MC/DC, you'll need to install from source: 
 
-#. Clone the MC/DC repo: ``git clone https://github.com/CEMeNT-PSAAP/MCDC.git`` 
+#. Clone the MC/DC repository: ``git clone https://github.com/mcdc-project/mcdc.git``
 #. Go to your new MC/DC directory: ``cd MCDC``
 #. Install the package from your MC/DC files: ``pip install -e .``
 
@@ -121,7 +121,7 @@ Then, MC/DC can be installed from source by first cloning the MC/DC repository:
 
 .. code-block:: sh
 
-    git clone https://github.com/CEMeNT-PSAAP/MCDC.git
+    git clone https://github.com/mcdc-project/mcdc.git
     cd MCDC
 
 then using the the ``install.sh`` within it. The install script will
@@ -155,12 +155,8 @@ To confirm that everything is properly installed, execute ``pytest`` from the MC
 Installing via Containers
 --------------------------
 
-For container-based installation and execution, see :doc:`user/container`.
-
-.. toctree::
-   :maxdepth: 1
-
-   user/container
+For container-based installation and execution, see
+:doc:`../container`.
 
 .. _install-data-library:
 
@@ -238,7 +234,7 @@ How Harmonize works gets a little involved, but in short,
 Harmonize acts as MC/DC's GPU runtime by using two major scheduling schemes: an event schedular similar to those implemented in OpenMC and Shift, plus a novel scheduler.
 For more information on Harmonize and how we compile MC/DC with it, see this `TOMACs article describing the async scheduler <https://doi.org/10.1145/3626957>`_ or our publications in American Nuclear Society: Math and Comp Meeting in 2025.
 
-If you encounter problems with configuration, please file `Github issues promptly <https://github.com/CEMeNT-PSAAP/MCDC/issues>`_ ,
+If you encounter problems with configuration, please file `GitHub issues promptly <https://github.com/mcdc-project/mcdc/issues>`_ ,
 especially when on supported super computers (LLNL's `Tioga <https://hpc.llnl.gov/hardware/compute-platforms/tioga>`_, `El Capitan <https://hpc.llnl.gov/documentation/user-guides/using-el-capitan-systems>`_, and `Lassen <https://hpc.llnl.gov/hardware/compute-platforms/lassen>`_).
 
 .. rubric:: Nvidia GPUs
diff --git a/docs/source/user_guide/getting_started/what_is_mcdc.rst b/docs/source/user_guide/getting_started/what_is_mcdc.rst
new file mode 100644
index 000000000..beb3ea7d3
--- /dev/null
+++ b/docs/source/user_guide/getting_started/what_is_mcdc.rst
@@ -0,0 +1,57 @@
+.. _what_is_mcdc:
+
+================
+What is MC/DC?
+================
+
+MC/DC is an open-source, Python-based Monte Carlo radiation transport software
+package that combines rapid methods development with scalable execution on
+modern high-performance computing systems. It supports execution across CPUs
+and GPUs while providing a flexible environment for developing and testing new
+transport algorithms.
+
+**Audience** — MC/DC is intended for researchers developing new Monte Carlo
+transport methods, including variance reduction techniques, sensitivity and
+uncertainty quantification methods, and high-performance computing algorithms.
+It also provides an accessible platform for students learning Monte Carlo
+radiation transport methods and modern code development.
+
+**Capabilities** — MC/DC supports continuous-energy and multi-group neutron
+transport calculations, including fixed-source and eigenvalue simulations on
+constructive solid geometry (CSG) models. For continuous-energy transport,
+MC/DC converts `ACE <https://nucleardata.lanl.gov/ace/>`_-format nuclear data
+libraries into its native `HDF5 <https://www.hdfgroup.org/solutions/hdf5/>`_
+format. Photon, electron, proton, and other charged-particle transport
+capabilities are currently under development as part of the ongoing expansion
+of MC/DC into a comprehensive multi-particle radiation transport software
+package.
+
+**Performance and portability** — MC/DC's Python interface enables rapid
+prototyping and iterative development, while its
+`Numba <https://numba.pydata.org>`_-based compilation framework delivers high
+performance without sacrificing portability.
+`Harmonize <https://github.com/CEMeNT-PSAAP/harmonize>`_ provides a GPU
+execution framework, and `MPI4Py <https://mpi4py.readthedocs.io/en/stable/>`_
+enables distributed-memory parallelism across large HPC systems. In addition
+to desktop and workstation systems, MC/DC has been demonstrated on large
+heterogeneous supercomputers, including
+`Lassen <https://asc.llnl.gov/computers/historicdecommissioned-machines/lassen>`_
+(IBM POWER9 and NVIDIA Volta V100) and
+`Tuolumne <https://warpx.readthedocs.io/en/latest/install/hpc/tuolumne.html>`_
+(AMD MI300A APU).
+
+**Origins** — MC/DC was initiated by the Center for Exascale Monte Carlo
+Neutron Transport (`CEMeNT <https://cement-psaap.github.io>`_), a Focused
+Investigatory Center of the Predictive Science Academic Alliance Program–III
+(`PSAAP-III <https://psaap.llnl.gov>`_). Development is now led by the Center
+for Advancing the Radiation Resilience of Electronics
+(`CARRE <https://carre-psaapiv.org>`_), a Predictive Simulation Center of
+`PSAAP-IV <https://psaap.llnl.gov>`_.
+
+**Open source** — MC/DC is released under the
+`BSD 3-Clause <https://github.com/mcdc-project/mcdc/blob/main/LICENSE>`_
+license and welcomes community contributions through
+`GitHub <https://github.com/mcdc-project/mcdc>`_.
+
+Next, :doc:`install MC/DC <installation>` or proceed to the
+:doc:`first simulation <first_simulation>` if it is already installed.
diff --git a/docs/source/user_guide/index.rst b/docs/source/user_guide/index.rst
new file mode 100644
index 000000000..99cc9c63d
--- /dev/null
+++ b/docs/source/user_guide/index.rst
@@ -0,0 +1,59 @@
+.. _user_guide:
+
+==========
+User Guide
+==========
+
+The User Guide provides task-oriented instructions for building, running, and
+analyzing MC/DC simulations. It begins with an introduction for new users and
+then covers modeling, execution, examples, and troubleshooting.
+
+For exact class and method signatures, use the :doc:`../reference/index`.
+
+Getting Started
+---------------
+
+New to MC/DC? Begin here to understand the project, install the package, and
+complete your first transport calculation.
+
+.. toctree::
+   :maxdepth: 2
+
+   getting_started/index
+
+Modeling and Results
+--------------------
+
+.. toctree::
+   :maxdepth: 1
+
+   tallies
+
+Execution
+---------
+
+.. toctree::
+   :maxdepth: 1
+
+   execution/index
+
+Learning by Example
+-------------------
+
+Use the :doc:`../examples/index` to learn from complete, runnable input decks
+that progress from basic models to advanced benchmarks.
+
+.. toctree::
+   :maxdepth: 2
+
+   Example Problems <../examples/index>
+
+Help & Support
+--------------
+
+.. toctree::
+   :maxdepth: 1
+
+   container
+   faq
+   troubleshooting
diff --git a/docs/source/user/tallies.rst b/docs/source/user_guide/tallies.rst
similarity index 98%
rename from docs/source/user/tallies.rst
rename to docs/source/user_guide/tallies.rst
index 791d98a15..d8dd20bcc 100644
--- a/docs/source/user/tallies.rst
+++ b/docs/source/user_guide/tallies.rst
@@ -6,7 +6,8 @@ Tallies and Post-processing
 
 Tallies specify which transport quantities MC/DC records and how those
 quantities are divided into bins. This page extends the model from
-:doc:`first_mcdc`; add the examples below before ``simulation.run()``. The code
+:doc:`getting_started/first_simulation`; add the examples below before
+``simulation.run()``. The code
 snippets assume NumPy has been imported as ``np``.
 
 Each tally combines:
diff --git a/docs/source/user/troubleshooting.rst b/docs/source/user_guide/troubleshooting.rst
similarity index 95%
rename from docs/source/user/troubleshooting.rst
rename to docs/source/user_guide/troubleshooting.rst
index dff51b47a..a604b8300 100644
--- a/docs/source/user/troubleshooting.rst
+++ b/docs/source/user_guide/troubleshooting.rst
@@ -6,7 +6,7 @@ Troubleshooting
 
 This page collects solutions to common installation and runtime problems.
 If your issue is not listed here, please check our
-`GitHub issues <https://github.com/CEMeNT-PSAAP/MCDC/issues>`_
+`GitHub issues <https://github.com/mcdc-project/mcdc/issues>`_
 or open a new one.
 
 Numba Version Compatibility
@@ -216,7 +216,7 @@ Use the operator syntax:
    # Wrong — do NOT use a list
    mcdc.Cell(region=[+s1, -s2], fill=material)
 
-See `#348 <https://github.com/CEMeNT-PSAAP/MCDC/issues/348>`_.
+See `#348 <https://github.com/mcdc-project/mcdc/issues/348>`_.
 
 
 Bugs and Issues
@@ -224,14 +224,14 @@ Bugs and Issues
 
 Our documentation is in the early stages of development, so thank you for bearing with us 
 while we bring it up to snuff. If you find a novel bug or anything else you feel we should 
-be aware of, feel free to `open an issue <https://github.com/CEMeNT-PSAAP/MCDC/issues>`_.
+be aware of, feel free to `open an issue <https://github.com/mcdc-project/mcdc/issues>`_.
 
 Getting More Help
 ~~~~~~~~~~~~~~~~~
 
 If you are still stuck after reviewing this troubleshooting guide:
 
-#. Search the `GitHub issues <https://github.com/CEMeNT-PSAAP/MCDC/issues>`_ for similar problems.
+#. Search the `GitHub issues <https://github.com/mcdc-project/mcdc/issues>`_ for similar problems.
 #. Run in debug mode for more informative error messages:
 
    .. code-block:: sh
diff --git a/pyproject.toml b/pyproject.toml
index 6fe3b703a..4a7ca903a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -76,9 +76,9 @@ dependencies = [
 
 [project.optional-dependencies]
 docs = [
-  "sphinx==7.2.6",
-  "furo",
-  "sphinx_toolbox",
+  "sphinx>=8,<10",
+  "pydata-sphinx-theme>=0.20,<0.21",
+  "sphinx-design>=0.6",
 ]
 
 dev = [
diff --git a/tools/data_library_generator/electron/README.md b/tools/data_library_generator/electron/README.md
index 6a28bf7e2..96b14caf2 100644
--- a/tools/data_library_generator/electron/README.md
+++ b/tools/data_library_generator/electron/README.md
@@ -100,5 +100,5 @@ only CDFs for EPRDATA14; sampling from the CDF is handled on the MC/DC side.
 ```
 
 ## See Also
-- [Continuous Energy Theory Guide](../../docs/source/theory/cont_energy.rst)
-- [Installation Guide — CE Library Configuration](../../docs/source/install.rst)
+- [Continuous Energy Theory Guide](../../docs/source/theory/continuous_energy.rst)
+- [Installation — CE Library Configuration](../../../docs/source/user_guide/getting_started/installation.rst)
diff --git a/tools/data_library_generator/neutron/README.md b/tools/data_library_generator/neutron/README.md
index 6f133dd94..41d7c50ce 100644
--- a/tools/data_library_generator/neutron/README.md
+++ b/tools/data_library_generator/neutron/README.md
@@ -76,5 +76,5 @@ For each ACE file in `$MCDC_ACELIB`, the generator:
 
 ## See Also
 
-- [Continuous Energy Theory Guide](../../docs/source/theory/cont_energy.rst)
-- [Installation Guide — CE Library Configuration](../../docs/source/install.rst)
+- [Continuous Energy Theory Guide](../../docs/source/theory/continuous_energy.rst)
+- [Installation — CE Library Configuration](../../../docs/source/user_guide/getting_started/installation.rst)

From 4eda9371091ac4b4edaa94c7f374364b7d677739 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 31 Jul 2026 14:43:37 +0700
Subject: [PATCH 067/202] draft for Dev Doc

---
 .../contributing/example_validation.rst       |  66 ++++
 docs/source/contributing/index.rst            |  42 +--
 docs/source/contributing/pull_requests.rst    |  39 ++
 .../architecture/acceleration.rst             |  53 ---
 .../developer_guide/architecture/index.rst    |  76 +++-
 .../{gpu.rst => numba_gpu_execution.rst}      |  32 +-
 .../python_first_numba_accelerated_design.rst | 228 ++++++++++++
 .../python_numba_cpu_execution.rst            | 135 +++++++
 .../architecture/runtime_data_layout.rst      | 147 ++++++++
 .../architecture/simulation_compilation.rst   | 335 ++++++++++++++++++
 .../extending/extending_the_object_model.rst  | 335 ++++++++++++++++++
 .../developer_guide/extending/index.rst       |  26 ++
 ...riting_numba_compatible_transport_code.rst | 236 ++++++++++++
 docs/source/developer_guide/index.rst         |  10 +-
 docs/source/examples/index.rst                |   5 +-
 .../examples/iterative_source_reweighting.rst |  48 +++
 .../architecture/architecture_flow.svg        |   1 +
 .../architecture/execution_modes.svg          |  43 +++
 .../architecture/numba_gpu_amd_flow.png}      | Bin
 .../architecture/numba_gpu_nvidia_flow.png}   | Bin
 .../architecture/object_graph_compilation.svg |  86 +++++
 .../architecture/runtime_data_layout.svg      |  79 +++++
 docs/source/project/index.rst                 |   4 +-
 docs/source/project/release_policy.rst        |  30 ++
 docs/source/reference/python_api/index.rst    |   8 +-
 docs/source/user_guide/execution/cpu.rst      |   6 +-
 docs/source/user_guide/execution/gpu.rst      |   3 +
 .../getting_started/first_simulation.rst      |  10 +-
 docs/source/user_guide/index.rst              |   4 +
 .../user_guide/simulation_lifecycle.rst       | 189 ++++++++++
 .../iterative_source_reweighting/input.py     |  60 ++++
 .../process-output.py                         |  84 +++++
 ...generator.py => numba_layers_generator.py} |  13 +-
 mcdc/main.py                                  |   6 +-
 mcdc/numba_types.py                           |   4 +-
 mcdc/object_/simulation.py                    |   5 +
 test/unit/test_example_inputs.py              |  41 +++
 37 files changed, 2372 insertions(+), 117 deletions(-)
 create mode 100644 docs/source/contributing/example_validation.rst
 create mode 100644 docs/source/contributing/pull_requests.rst
 delete mode 100644 docs/source/developer_guide/architecture/acceleration.rst
 rename docs/source/developer_guide/architecture/{gpu.rst => numba_gpu_execution.rst} (91%)
 create mode 100644 docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
 create mode 100644 docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
 create mode 100644 docs/source/developer_guide/architecture/runtime_data_layout.rst
 create mode 100644 docs/source/developer_guide/architecture/simulation_compilation.rst
 create mode 100644 docs/source/developer_guide/extending/extending_the_object_model.rst
 create mode 100644 docs/source/developer_guide/extending/index.rst
 create mode 100644 docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
 create mode 100644 docs/source/examples/iterative_source_reweighting.rst
 create mode 100644 docs/source/images/developer_guide/architecture/architecture_flow.svg
 create mode 100644 docs/source/images/developer_guide/architecture/execution_modes.svg
 rename docs/source/images/{theory/gpu_comp/amd_flow.png => developer_guide/architecture/numba_gpu_amd_flow.png} (100%)
 rename docs/source/images/{theory/gpu_comp/nvcc_flow.png => developer_guide/architecture/numba_gpu_nvidia_flow.png} (100%)
 create mode 100644 docs/source/images/developer_guide/architecture/object_graph_compilation.svg
 create mode 100644 docs/source/images/developer_guide/architecture/runtime_data_layout.svg
 create mode 100644 docs/source/project/release_policy.rst
 create mode 100644 docs/source/user_guide/simulation_lifecycle.rst
 create mode 100644 examples/iterative_source_reweighting/input.py
 create mode 100644 examples/iterative_source_reweighting/process-output.py
 rename mcdc/code_factory/{numba_objects_generator.py => numba_layers_generator.py} (99%)
 create mode 100644 test/unit/test_example_inputs.py

diff --git a/docs/source/contributing/example_validation.rst b/docs/source/contributing/example_validation.rst
new file mode 100644
index 000000000..4e4084cb6
--- /dev/null
+++ b/docs/source/contributing/example_validation.rst
@@ -0,0 +1,66 @@
+.. _example_validation:
+
+==================
+Example Validation
+==================
+
+The inputs under ``examples/`` are executable documentation. Changes to the
+public API, object-compilation behavior, or example models should validate them
+at three levels.
+
+Compile Every Example
+---------------------
+
+The automated example test executes every ``examples/**/input.py`` while
+replacing transport and visualization with model compilation:
+
+.. code-block:: sh
+
+   python -m pytest test/unit/test_example_inputs.py --mode=python
+
+This check:
+
+- Discovers new example inputs automatically.
+- Executes their model-construction code from the correct working directory.
+- Requires an explicit :class:`mcdc.Simulation`.
+- Allows iterative examples to compile the same simulation more than once.
+- Compiles the complete reachable object graph.
+- Requires at least one cell, source, and tally.
+- Avoids long particle-transport runs and output files.
+
+The test catches removed public interfaces, missing object attachments,
+invalid model references, compilation failures, and example files that no
+longer reach ``simulation.run()`` or ``simulation.visualize_model()``.
+
+Run Representative Transport
+----------------------------
+
+The compile-only test does not validate transport results. Before merging a
+change that affects execution, run the small slab-shielding problem in the
+affected CPU modes:
+
+.. code-block:: sh
+
+   cd examples/slab_shielding
+   python input.py --mode=python --N_particle=100 --N_batch=2
+   python input.py --mode=numba --N_particle=100 --N_batch=2
+
+Check that both commands finish, write ``slab_shielding.h5``, and produce the
+expected ``slab_flux`` tally. Use the normal example settings when evaluating
+statistical agreement rather than only execution.
+
+Validate Specialized Paths
+--------------------------
+
+Run examples that represent the changed capability:
+
+- ``examples/c5g7/k-eigenvalue`` for k-eigenvalue behavior.
+- ``examples/moving_source`` or ``examples/c5g7/transient`` for transient
+  behavior.
+- ``examples/slab_shielding`` or ``examples/fuel_array_packaged`` for
+  visualization.
+- A supported accelerator environment for Numba-GPU changes.
+
+Regression tests remain the authoritative check for numerical results.
+Example validation complements them by ensuring the documented, user-facing
+inputs continue to construct models through the current public API.
diff --git a/docs/source/contributing/index.rst b/docs/source/contributing/index.rst
index 0d33b4ebc..203491a7b 100644
--- a/docs/source/contributing/index.rst
+++ b/docs/source/contributing/index.rst
@@ -10,8 +10,13 @@ project maintainers.
 
 Start with the setup steps below. Use :doc:`continuous_integration` to
 understand automated checks and :doc:`container_development` when developing in
-the project container. For software architecture and documentation practices,
-see the :doc:`../developer_guide/index`.
+the project container. Use :doc:`example_validation` when changing the public
+API or example problems. Read :doc:`pull_requests` before preparing a
+contribution. For software architecture and documentation practices, see the
+:doc:`../developer_guide/index`.
+
+For implementation guidance specific to compiled transport functions, see
+:doc:`../developer_guide/extending/writing_numba_compatible_transport_code`.
 
 Contributions target the ``dev`` branch. To prepare a development checkout:
 
@@ -28,6 +33,8 @@ Development Workflow
 
    continuous_integration
    container_development
+   example_validation
+   pull_requests
 
 MC/DC documentation is an important part of the project and evolves alongside
 the codebase. The :doc:`../developer_guide/documentation/index` guide describes
@@ -108,9 +115,11 @@ However if absolutely required by users numba does allow for some `cache sharing
 Adding a New Input
 ------------------
 
-To add a new keyword argument such that a user can interface with it in an input deck 
-there are a few different places a dev will need to make alterations.
-The input objects are defined as dataclasses in the ``mcdc/object_/`` directory:
+For architectural guidance on adding a model field, embedded configuration,
+registered object category, or polymorphic subtype, see
+:doc:`../developer_guide/extending/extending_the_object_model`. Public model
+classes and configuration are primarily defined in ``mcdc/object_/``. Common
+input-related locations include:
 
 #. ``mcdc/object_/settings.py`` — simulation settings and k-eigenvalue parameters
 #. ``mcdc/object_/material.py`` — material definitions (``Material``, ``MaterialMG``)
@@ -195,26 +204,3 @@ the relevant documentation accordingly.
 See the :doc:`../developer_guide/documentation/index` guide for documentation
 philosophy, writing
 guidelines, and instructions for contributing to the documentation.
-
-
--------------
-Pull Requests
--------------
-
-
-MC/DC works off of a fork workflow in which contributors fork our repo, make alterations, and submit a pull requests.
-You should only submit a pull request once your code passes all tests, is properly linted, you have edited documentation (if necessary), and added any new tests (if needed).
-Open a PR to the ``dev`` branch in Github.
-MC/DC's main branch is only updated for version releases at which time a PR from dev to main is opened, tagged, archived, and published automatically.
-
-Within your pull request documentation please list:
-
-#. Type of PR (e.g. enhancement, bugfix, etc);
-#. Link to any theory to understand what you are doing;
-#. Link to any open/closed issues if applicable;
-#. New functionalities implemented
-#. Depreciated functionalities
-#. New dependencies needed (we don't add these lightly)
-#. Anything else we need to give you the thorough code review you deserve!
-
-If these things aren't listed we will ask for clarifying questions!
diff --git a/docs/source/contributing/pull_requests.rst b/docs/source/contributing/pull_requests.rst
new file mode 100644
index 000000000..9c9c55c2f
--- /dev/null
+++ b/docs/source/contributing/pull_requests.rst
@@ -0,0 +1,39 @@
+.. _pull_requests:
+
+=============
+Pull Requests
+=============
+
+MC/DC uses a fork-based contribution workflow. Open pull requests from your
+fork against the ``dev`` branch of ``mcdc-project/mcdc``.
+
+Before opening a pull request, make sure:
+
+- The applicable tests pass.
+- The code follows the project style.
+- Tests and documentation have been added or updated as needed.
+- ``CHANGELOG.md`` has been updated when the change is notable.
+
+Changelog Updates
+-----------------
+
+Add a concise entry under ``[Unreleased]`` in
+`CHANGELOG.md <https://github.com/mcdc-project/mcdc/blob/dev/CHANGELOG.md>`_
+when a pull request introduces a notable user- or developer-visible change.
+Follow the format described in that file. Release headings, versions, and dates
+are assigned during release preparation.
+
+Pull Request Description
+------------------------
+
+Use the pull request template to summarize:
+
+- The type and purpose of the change.
+- Associated issues or pull requests.
+- Relevant theory or design context.
+- New, changed, deprecated, or removed functionality.
+- Any new dependency.
+- The developers who should be notified.
+
+The description should give reviewers enough context to understand the change,
+verify its scope, and identify any follow-up work.
diff --git a/docs/source/developer_guide/architecture/acceleration.rst b/docs/source/developer_guide/architecture/acceleration.rst
deleted file mode 100644
index 0ebe4738a..000000000
--- a/docs/source/developer_guide/architecture/acceleration.rst
+++ /dev/null
@@ -1,53 +0,0 @@
-.. _acceleration:
-
-============================
-Acceleration and Abstraction
-============================
-
-MC/DC employs a layered compilation and abstraction strategy that allows the same Python source code to target CPUs (pure Python or Numba JIT) and GPUs (via Harmonize) without modification to the transport algorithms.
-
-Execution Modes
----------------
-
-MC/DC supports three execution modes, selected at runtime with the ``--mode`` flag:
-
-- **Python mode** (``--mode=python``): Transport kernels run as interpreted Python. Useful for debugging and rapid prototyping.
-- **Numba mode** (``--mode=numba``): Transport kernels are just-in-time compiled to native machine code using `Numba <https://numba.readthedocs.io/>`_. This provides significant speedup (often 100x or more) at the cost of an initial compilation overhead of 15–80 seconds.
-- **Numba debug mode** (``--mode=numba_debug``): JIT compilation with extra debug instrumentation (bounds checking, full tracebacks, type inference logging). Slower, but produces actionable error messages.
-
-The ``--target`` flag selects the hardware target: ``cpu`` (default) or ``gpu``.
-
-Numba Object Generation
------------------------
-
-MC/DC's simulation state (materials, surfaces, cells, tallies, settings, particle banks, etc.) is defined as annotated Python classes in ``mcdc/object_/``.
-At startup, the **Numba object generator** (``mcdc/code_factory/numba_objects_generator.py``) converts these class hierarchies into NumPy structured array dtypes:
-
-#. Class annotations (type hints) are read and mapped to NumPy dtypes.
-#. Polymorphic objects (e.g., different surface types) are represented using ``parent_ID``/``child_ID`` fields that index into typed sub-arrays.
-#. All simulation data is flattened into a single contiguous NumPy buffer (``data``), enabling efficient access from JIT-compiled code.
-#. Getter and setter access functions (in ``mcdc/mcdc_get/`` and ``mcdc/mcdc_set/``) are auto-generated so that JIT-compiled transport kernels can read and write simulation state without Python object overhead.
-
-This approach allows the transport code to be written in natural, object-oriented Python while still achieving the performance of flat array access in compiled mode.
-
-GPU Portability
----------------
-
-When targeting GPUs, MC/DC uses the `Harmonize <https://github.com/CEMeNT-PSAAP/harmonize>`_ library as its GPU runtime.
-The GPU program builder (``mcdc/code_factory/gpu/program_builder.py``) constructs a Harmonize ``RuntimeSpec`` that includes:
-
-- **Global state**: the simulation structured array and the flat data buffer.
-- **Device functions**: the MC/DC transport kernels, compiled from Python to device code via Numba.
-- **Scheduling strategy**: either event-based (``--gpu_strategy=event``) or asynchronous (``--gpu_strategy=async``, Nvidia only).
-
-The compilation pipeline differs by vendor:
-
-- **Nvidia**: Python → PTX (via ``numba.cuda``) → relocatable device code (via ``nvcc``) → linked shared library.
-- **AMD**: Python → LLVM-IR (via a `Numba-HIP patch <https://github.com/ROCm/numba-hip>`_) → relocatable device code (via ``hipcc`` / ``clang``) → linked shared library.
-
-For details about accelerator execution, see :ref:`architecture_gpu`.
-
-For more details, see:
-
-- J. P. Morgan, I. Variansyah, B. Cuneo, T. S. Palmer, and K. E. Niemeyer. "Performance Portable Monte Carlo Neutron Transport in MCDC via Numba." Preprint DOI 10.48550/arXiv.2306.07847.
-- B. Cuneo and M. Bailey. "Divergence Reduction in Monte Carlo Neutron Transport with On-GPU Asynchronous Scheduling." *ACM TOMACS* (2023). DOI 10.1145/3626957.
diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index 55e697c81..003fbc798 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -5,17 +5,77 @@ Architecture
 ============
 
 Architecture documentation explains how MC/DC translates flexible Python model
-definitions into high-performance particle-transport execution.
+definitions into particle-transport execution. The main path follows the model
+through compilation, runtime preparation, Python execution, Numba-CPU acceleration,
+and finally the Numba-GPU and Harmonize layers. MC/DC's architecture flow and
+component responsibilities are presented below.
 
-Start with :doc:`acceleration` for an overview of the acceleration and code
-generation layers. Read :doc:`gpu` when working on accelerator execution or
-the Harmonize integration.
+Architecture Flow
+-----------------
 
-Documentation of the explicit ``Simulation`` compilation pipeline, runtime data
-layout, and Numba design belongs in this section as those pages are developed.
+MC/DC has three distinct preparation and execution stages:
+
+#. **Model compilation** discovers the Python objects owned by a
+   :class:`mcdc.Simulation`, deduplicates them, and assigns simulation-local
+   identifiers.
+#. **Runtime preparation** converts the compiled model into the structured
+   ``simulation`` state and flat ``data`` array consumed by transport.
+#. **Backend execution** runs the shared transport implementation through
+   Python, Numba-CPU, or Numba-GPU.
+
+.. image:: ../../images/developer_guide/architecture/architecture_flow.svg
+   :width: 100%
+   :alt: MC/DC architecture from Python model objects through compilation, runtime preparation, and execution backends.
+
+Component Responsibility
+------------------------
+
+.. list-table::
+   :header-rows: 1
+   :widths: 30 70
+
+   * - Component
+     - Responsibility
+   * - ``mcdc/object_``
+     - Defines the Python-side model, configuration, and runtime-state classes.
+   * - :class:`mcdc.Simulation` in ``mcdc/object_/simulation.py``
+     - Owns model roots and configuration and controls compilation,
+       visualization, and execution.
+   * - ``mcdc/code_factory/python_objects_compiler.py``
+     - Discovers and registers the connected Python object graph.
+   * - ``mcdc/code_factory/numba_layers_generator.py``
+     - Derives structured dtypes, packs runtime state, generates accessors, and
+       initiates GPU-specific preparation when requested.
+   * - Runtime ``simulation`` and ``data``
+     - Generated by ``numba_layers_generator.py``; store fixed-layout state and
+       variable-length numerical data,
+       respectively.
+   * - ``mcdc/mcdc_get`` and ``mcdc/mcdc_set``
+     - Provide generated, structured access to fields stored in ``data``.
+   * - ``mcdc/transport``
+     - Implements the particle-transport algorithms consumed by every
+       execution backend.
+
+What's Next
+-----------
+
+Begin with :doc:`python_first_numba_accelerated_design` for a high-level view of the
+rationale, boundaries, and tradeoffs that shape the architecture.
+
+Then read :doc:`simulation_compilation` to understand ownership of Python model objects,
+recursive object discovery, and simulation-local ID assignment. Continue with
+:doc:`runtime_data_layout` for the packed runtime representation and generated access
+helpers.
+
+Next, read :doc:`python_numba_cpu_execution` to follow execution first in Python and
+then with Numba-CPU. Finish with :doc:`numba_gpu_execution` for GPU code generation,
+memory placement, and Harmonize scheduling.
 
 .. toctree::
    :maxdepth: 1
 
-   acceleration
-   gpu
+   python_first_numba_accelerated_design
+   simulation_compilation
+   runtime_data_layout
+   python_numba_cpu_execution
+   numba_gpu_execution
diff --git a/docs/source/developer_guide/architecture/gpu.rst b/docs/source/developer_guide/architecture/numba_gpu_execution.rst
similarity index 91%
rename from docs/source/developer_guide/architecture/gpu.rst
rename to docs/source/developer_guide/architecture/numba_gpu_execution.rst
index 6b3e51130..1ea36eb12 100644
--- a/docs/source/developer_guide/architecture/gpu.rst
+++ b/docs/source/developer_guide/architecture/numba_gpu_execution.rst
@@ -1,14 +1,30 @@
-.. _architecture_gpu:
+.. _numba_gpu_execution:
 
-=================
-GPU Functionality
-=================
+===================
+Numba-GPU Execution
+===================
+
+GPU execution is the final layer in MC/DC's execution model. MC/DC first
+compiles the Python model and creates the same logical runtime representation
+used on the CPU. It then adapts the transport functions for device execution,
+allocates or transfers runtime state, and uses Harmonize to schedule particle
+work.
+
+Read :doc:`simulation_compilation`, :doc:`runtime_data_layout`, and
+:doc:`python_numba_cpu_execution` first. This page focuses on the additional
+GPU-specific compilation and runtime machinery.
 
 GPU Compilation
 ---------------
 
-When targeting GPUs, MC/DC functions are just-in-time (JIT) compiled with Harmonize.
-To JIT compile and execute on AMD or Nvidia GPUs, MC/DC users need only to append their terminal launches with a ``--target=gpu`` option.
+When targeting GPUs, MC/DC functions are just-in-time (JIT) compiled with
+Numba and integrated with Harmonize. A GPU run selects Numba mode and the GPU
+target:
+
+.. code-block:: sh
+
+   python input.py --mode=numba --target=gpu
+
 When considered in totality the MC/DC+Numba+Harmonize JIT compilation structure is akin to "portability framework", in that it allows dynamic targeting and developer abstraction of hardware architectures, like OpenMP target-offloading used by OpenMC.
 This JIT compilation process allows MC/DC to pair the idea of a portability framework with a high-level language in an effort to enable more rapid methods development on Exascale systems.
 
@@ -27,7 +43,7 @@ Nvidia Targets
 To compile to Nvidia GPU hardware-targets at runtime, we rely entirely on the Nvidia C-Compiler (`nvcc`).
 Current versions of Numba come with CUDA operability natively, but this is set to be deprecated in future releases in favor of a more modular approach where the Numba-CUDA package will be an optional separate feature.
 
-.. image:: ../../images/theory/gpu_comp/nvcc_flow.png
+.. image:: ../../images/developer_guide/architecture/numba_gpu_nvidia_flow.png
    :width: 800
    :alt: Simple proxy example describing how to compile device functions in Numba-Python with external C++ code for targeting Nvidia GPUs. In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize.
 
@@ -70,7 +86,7 @@ Every GPU program is technically a bound set of two complementary applications:
 To link external device code together for AMD hardware-targets, we have to unbundle these two programs, link the extra device functions (coming from Python) to the device side, then re-bundle the device and host functions back together.
 This process is done in LLVM-IR.
 
-.. image:: ../../images/theory/gpu_comp/amd_flow.png
+.. image:: ../../images/developer_guide/architecture/numba_gpu_amd_flow.png
    :width: 800
    :alt: Simple proxy example describing how to compile device functions in Numba-HIP with external C++ code to AMD GPU targets. In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize.
 
diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
new file mode 100644
index 000000000..5df62e992
--- /dev/null
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -0,0 +1,228 @@
+.. _python_first_numba_accelerated_design:
+
+======================================
+Python-First, Numba-Accelerated Design
+======================================
+
+MC/DC is designed for Monte Carlo methods development in Python while retaining
+an execution path suitable for large transport calculations. Python is the
+language in which users construct models and developers express transport
+algorithms. Numba is the acceleration layer that specializes those algorithms
+for CPUs and helps make them available to GPU execution.
+
+*Python-first* describes the order in which MC/DC is understood and developed:
+establish correct behavior in Python, accelerate the same typed transport path
+with Numba-CPU, and then satisfy the additional constraints of Numba-GPU and
+Harmonize. It does not mean that transport operates directly on the rich
+Python object graph.
+
+Where Each Layer Runs
+---------------------
+
+MC/DC deliberately separates flexible model construction from constrained
+transport execution:
+
+.. list-table::
+   :header-rows: 1
+   :widths: 24 38 38
+
+   * - Stage
+     - Representation
+     - Execution environment
+   * - Model definition
+     - User-facing Python objects and references
+     - Python
+   * - Model compilation
+     - Simulation-owned, ordered object graph
+     - Python
+   * - Runtime preparation
+     - Structured ``simulation`` state and flat ``data``
+     - Python and NumPy
+   * - Transport
+     - Typed functions operating on packed state
+     - Python, Numba-CPU, or Numba-GPU
+   * - Output and postprocessing
+     - HDF5 output and analysis objects
+     - Python
+
+The Python stages may use object-oriented interfaces, variable-length
+collections, validation, and other features that make model construction
+clear. The transport stage uses stable numerical types, arrays, integer IDs,
+and explicit function calls that compilation targets can understand.
+
+Why MC/DC Uses Numba
+--------------------
+
+Numba lets MC/DC preserve a Python implementation of its numerical algorithms
+while compiling type-stable functions for a hardware target at run time. This
+supports several project goals:
+
+- Researchers can implement and inspect transport methods in Python.
+- Python mode provides a direct path for debugging algorithm and data-flow
+  errors.
+- Numba-CPU can specialize the same transport functions without maintaining a
+  separate implementation in another language.
+- The typed runtime representation and transport interfaces provide a
+  foundation for GPU code generation and Harmonize scheduling.
+
+The result is one conceptual transport implementation, with backend-specific
+adaptation where the hardware requires it. GPU support is not automatic for
+arbitrary Python or arbitrary Numba-CPU code; transport intended for all three
+modes must stay within their supported common subset.
+
+Staged Methods Development
+--------------------------
+
+Python-first also describes how new methods are typically developed. A method
+usually begins as a pure-Python prototype, either independently or in MC/DC's
+Python execution mode. At this stage, the priority is to establish the
+method's correctness, understand its behavior, and test it on problems small
+enough that compiled performance is unnecessary.
+
+Once the method is verified and larger calculations require more performance,
+the implementation can advance to Numba-CPU. This step is more than enabling
+JIT compilation: Python constructs that Numba cannot type or compile may need
+to be replaced with explicit numerical types, stable control flow, packed
+runtime data, and supported operations.
+
+Numba-GPU is a further stage. Device execution typically imposes additional
+constraints involving memory placement, allocation, host interaction, atomics,
+and Harmonize scheduling. Some code that works with Numba-CPU therefore
+requires further adaptation before it can execute on a GPU.
+
+Each stage is a useful endpoint:
+
+- **Python** is sufficient for prototyping methods, diagnosing behavior, and
+  running small problems.
+- **Numba-CPU** is sufficient when compiled CPU performance meets the
+  calculation's needs.
+- **Numba-GPU** provides the final portability stage when accelerator
+  performance is required.
+
+This staged workflow allows researchers to stop when their immediate objective
+has been achieved. A general feature intended to be merged and maintained as
+part of MC/DC, however, must work in Python, Numba-CPU, and Numba-GPU unless
+the maintainers explicitly accept and document a backend-specific limitation.
+
+An independent pure-Python prototype may use data structures chosen only for
+exploration. Once integrated into MC/DC, however, Python mode still performs
+model compilation and runtime preparation. It is the reference execution mode
+for the same packed transport path that later stages accelerate.
+
+Architectural Consequences
+--------------------------
+
+Using Numba shapes the boundary between MC/DC's model and execution layers.
+The following are architectural requirements rather than incidental
+implementation details.
+
+Model Objects Are Not Runtime Objects
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Materials, cells, sources, tallies, and related objects are convenient
+descriptions of a model. Before transport, MC/DC discovers the complete object
+graph and converts Python references into simulation-local IDs. Transport
+receives packed records and arrays, not instances of ``MCDCObject``.
+
+See :doc:`simulation_compilation` for the owning ``Simulation`` context,
+recursive discovery, and the ``MCDCBase``--``MCDCObject``--
+``MCDCPolymorphic`` hierarchy.
+
+Execution Data Has a Stable Layout
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The types and collection sizes needed by a run are finalized before transport.
+Fixed-layout values are stored in the structured ``simulation`` record.
+Variable-length and ragged numerical values are flattened into ``data`` and
+described by offsets, lengths, and shapes.
+
+This representation avoids dynamic Python containers in transport and gives
+all backends the same logical state. Generated ``mcdc_get`` and ``mcdc_set``
+helpers centralize the corresponding indexing rules. See
+:doc:`runtime_data_layout` for the complete representation.
+
+Dispatch Is Explicit
+^^^^^^^^^^^^^^^^^^^^
+
+Python dynamic dispatch is replaced by integer type codes and explicit
+branches in transport interfaces. A polymorphic base record stores
+``sub_type`` and ``sub_ID``; transport uses them to select the concrete packed
+record and implementation.
+
+This makes the possible execution paths visible to Numba and keeps runtime
+behavior independent of Python object identity.
+
+Mutation Is Bounded
+^^^^^^^^^^^^^^^^^^^
+
+Transport updates particle state, banks, tallies, and counters in storage
+allocated during preparation. It does not add model objects or resize the
+model's runtime layout. A model change therefore produces a new compilation
+snapshot and a newly prepared runtime representation.
+
+CPU and GPU Share a Deliberate Subset
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Numba-CPU supports some operations that are unavailable or unsuitable inside a
+GPU device function. Code shared by the two targets must use explicit numeric
+types, supported NumPy operations, predictable control flow, and preallocated
+state. Host callbacks, Python objects, and object-mode escapes must remain
+outside GPU transport paths.
+
+MC/DC may use target-specific modules when execution, memory, atomics, or
+scheduling genuinely differs. The common transport path should remain the
+default so that backend implementations do not drift apart.
+
+Design Tradeoffs
+----------------
+
+The architecture makes methods development and compiled execution share a
+language and much of an implementation, but the boundary has costs:
+
+- Runtime-visible state must be declared and packed before execution.
+- Dynamic Python conveniences cannot be used inside compiled transport paths.
+- New model concepts often require coordinated object, layout, accessor,
+  transport, and test changes.
+- Just-in-time compilation adds startup work and can produce typing errors that
+  do not appear in Python mode.
+- GPU support may require additional code generation, memory management, and
+  backend-specific implementations.
+
+These constraints are accepted at the execution boundary so that the
+user-facing model and host-side development workflow can remain expressive.
+
+Related Design Choices
+----------------------
+
+Other designs emphasize different tradeoffs. A pure-Python solver would
+maximize dynamism but would not provide MC/DC's compiled execution path.
+Handwritten C, C++, or Fortran kernels could provide direct low-level control
+but would split methods development across languages and require a binding
+boundary. Passing the object graph directly to execution would retain its
+structure but make types, ownership, and accelerator data movement harder to
+control. Padding every ragged field into a rectangular array would simplify
+some indexing while increasing storage and obscuring the field's natural
+shape.
+
+MC/DC instead uses rich Python model objects on the host and a generated,
+typed, flat representation for execution. This section describes the current
+design space; it should not be read as a claim that every alternative was
+implemented and benchmarked by the project.
+
+Future Evolution
+----------------
+
+The Python-first principle does not require the present implementation to
+remain fixed. Future work may revise compilation-state ownership, generated
+layer lifecycles, typed-container support, or the boundary between common and
+backend-specific transport. Such changes should preserve three properties:
+
+- A clear Python path for developing and diagnosing transport behavior.
+- An explicit conversion from user model to execution state.
+- Equivalent physical behavior across supported execution backends.
+
+For the mechanisms behind this boundary, see :doc:`simulation_compilation` and
+:doc:`runtime_data_layout`. If following the main Architecture path, return to
+the Numba-CPU section of :doc:`python_numba_cpu_execution`, then continue with
+:doc:`numba_gpu_execution`. When implementing a transport change, use
+:doc:`../extending/writing_numba_compatible_transport_code`.
diff --git a/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst b/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
new file mode 100644
index 000000000..46f3d5bf3
--- /dev/null
+++ b/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
@@ -0,0 +1,135 @@
+.. _python_numba_cpu_execution:
+
+==============================
+Python and Numba-CPU Execution
+==============================
+
+MC/DC uses one transport implementation for both Python and Numba-CPU
+execution. The Python path is the conceptual baseline: it is the easiest mode
+to inspect and debug, and it establishes the behavior that the accelerated
+path preserves.
+
+Both modes operate on the same packed :doc:`runtime_data_layout` and call the
+same functions under ``mcdc/transport``. The difference is whether Numba
+executes functions decorated with ``@njit`` as ordinary Python functions or
+compiles them for the CPU.
+
+Shared Preparation
+------------------
+
+Before transport begins, both modes follow the same preparation path:
+
+#. :class:`mcdc.Simulation` compiles the reachable Python object graph.
+#. ``mcdc.main.prepare`` derives run-dependent values such as particle-bank
+   sizes and physics-mode selections.
+#. ``mcdc.code_factory`` builds the structured ``simulation`` state and flat
+   ``data`` array.
+#. Generated ``mcdc_get`` and ``mcdc_set`` helpers provide transport-safe
+   access to variable-length fields.
+#. The fixed-source or k-eigenvalue driver calls the transport kernels.
+
+This shared preparation is why Python mode can expose the same data-layout and
+transport behavior as Numba mode without maintaining a separate reference
+implementation.
+
+.. image:: ../../images/developer_guide/architecture/execution_modes.svg
+   :width: 100%
+   :alt: Shared MC/DC preparation feeding Python, Numba-CPU, and Numba-GPU execution.
+
+Python Mode
+-----------
+
+Python mode is the default:
+
+.. code-block:: sh
+
+   python input.py --mode=python
+
+In this mode, MC/DC sets ``numba.config.DISABLE_JIT``. Functions decorated with
+``@njit`` therefore execute through Python while retaining the same signatures
+and packed runtime inputs used by accelerated execution.
+
+Python mode is best for:
+
+- Developing and inspecting transport logic.
+- Checking model construction and object compilation.
+- Obtaining ordinary Python tracebacks.
+- Running small smoke tests before enabling acceleration.
+
+Python mode does not bypass simulation compilation or runtime packing. It
+bypasses machine-code generation for the CPU transport functions.
+
+Before Numba Acceleration
+-------------------------
+
+At this transition, :doc:`python_first_numba_accelerated_design` becomes the
+main conceptual guide. It explains why MC/DC converts its flexible Python
+model into typed runtime data, which parts remain shared across execution
+backends, and which constraints follow from supporting Numba-CPU and
+Numba-GPU.
+
+If you have not already read that design page as an overview, read it before
+continuing when developing MC/DC or studying its acceleration architecture.
+Readers who only need the mechanics of the Python and Numba-CPU modes may
+continue directly below.
+
+Numba-CPU Mode
+--------------
+
+Numba-CPU mode enables just-in-time compilation:
+
+.. code-block:: sh
+
+   python input.py --mode=numba
+
+The target defaults to ``cpu``. Numba specializes the shared transport
+functions for the structured simulation dtype, flat data array, particle
+records, and other argument types encountered during execution. The initial
+run therefore includes compilation work; subsequent transport work uses the
+compiled functions.
+
+The runtime representation is unchanged:
+
+.. list-table::
+   :header-rows: 1
+   :widths: 24 38 38
+
+   * - Concern
+     - Python mode
+     - Numba-CPU mode
+   * - Model ownership
+     - Explicit ``Simulation``
+     - Explicit ``Simulation``
+   * - Object-graph compilation
+     - Required
+     - Required
+   * - Packed ``simulation`` and ``data``
+     - Required
+     - Required
+   * - Transport implementation
+     - ``mcdc/transport``
+     - ``mcdc/transport``
+   * - ``@njit`` behavior
+     - JIT disabled
+     - Compiled for CPU
+
+Numba debug mode keeps JIT compilation enabled while adding bounds checking,
+fuller tracebacks, and compiler diagnostics:
+
+.. code-block:: sh
+
+   python input.py --mode=numba_debug
+
+Use the ordinary Python mode first to separate model or algorithm errors from
+Numba typing and compilation errors. For operational commands, MPI execution,
+and caching options, see :doc:`../../user_guide/execution/cpu`. For coding
+rules and a staged verification workflow, see
+:doc:`../extending/writing_numba_compatible_transport_code`.
+
+From CPU to GPU
+---------------
+
+Numba-GPU execution retains the same Python model-compilation and runtime-layout
+concepts, then replaces the CPU execution backend with device compilation and
+Harmonize scheduling. Continue with :doc:`numba_gpu_execution` after the
+Python and Numba-CPU paths are clear.
diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
new file mode 100644
index 000000000..a9bd8802e
--- /dev/null
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -0,0 +1,147 @@
+.. _runtime_data_layout:
+
+===================
+Runtime Data Layout
+===================
+
+After model compilation has discovered and ordered the Python object graph,
+``mcdc.main.prepare`` creates the runtime representation used by transport.
+The representation has two complementary parts:
+
+``simulation``
+   A fixed-layout NumPy structured record containing scalar state, embedded
+   records, typed object collections, fixed-size arrays, and metadata.
+
+``data``
+   A contiguous one-dimensional NumPy array containing variable-length
+   numerical payloads and lists of object IDs.
+
+The same logical representation is used by Python, Numba-CPU, and Numba-GPU
+execution. It should therefore be understood as MC/DC's transport runtime
+model, not as a separate Numba-only model.
+
+Why Two Structures?
+-------------------
+
+Python model objects may contain arrays whose sizes depend on the problem:
+energy grids, cross sections, mesh boundaries, motion tables, tally filters,
+and many others. Nested Python references and arbitrary array shapes cannot be
+embedded directly in a stable structured dtype.
+
+MC/DC separates fixed-layout metadata from variable-length values:
+
+.. image:: ../../images/developer_guide/architecture/runtime_data_layout.svg
+   :width: 100%
+   :alt: A structured simulation record using offsets, lengths, and shapes to describe fields stored in a flat data array.
+
+For a variable-length field such as ``mesh.z``, the mesh record stores values
+equivalent to:
+
+.. code-block:: text
+
+   z_offset = 120
+   z_length = 61
+
+and the values occupy:
+
+.. code-block:: text
+
+   data[120:181]
+
+For multidimensional arrays, annotated shape metadata supplies the strides used
+to reconstruct logical indexing. The payload itself is flattened when packed.
+
+Deriving the Layout
+-------------------
+
+Classes in ``mcdc/object_`` declare their runtime-visible fields with Python
+type annotations. ``generate_numba_layers`` collects those annotations and
+maps them to runtime fields:
+
+- Scalars become scalar structured fields.
+- Fixed-shape annotated arrays are embedded in structured records.
+- Variable-length arrays become ``<field>_offset`` and ``<field>_length``
+  metadata plus values in ``data``.
+- Object references become ``<field>_ID`` fields.
+- Lists of object references become ``N_<object>`` and
+  ``<object>_IDs_offset`` metadata plus IDs in ``data``.
+- Members named in a class's ``non_numba`` list are excluded from the packed
+  representation or handled specially.
+
+Polymorphic base and subtype collections receive separate structured dtypes.
+The base ``ID``, ``sub_type``, ``sub_ID``, and child ``base_ID`` fields connect
+those collections without Python references.
+
+Packing is performed in two passes:
+
+#. Walk the compiled objects to build records and calculate the required
+   ``data`` size.
+#. Allocate ``data`` and walk the objects again to copy flattened payloads into
+   their assigned regions.
+
+The structured ``simulation`` dtype can then be finalized because collection
+sizes, particle-bank sizes, and nested record types are known.
+
+The One-element Container
+-------------------------
+
+The generated simulation record is stored in a one-element NumPy array:
+
+.. code-block:: python
+
+   simulation_container, data = prepare(simulation_python)
+   simulation = simulation_container[0]
+
+The container gives Python, Numba, MPI, and GPU paths a consistent mutable
+reference to the structured state. Transport drivers receive the container and
+``data``; individual kernels generally operate on the record or its nested
+objects.
+
+Generated Access Helpers
+------------------------
+
+``mcdc.code_factory`` generates modules under ``mcdc/mcdc_get`` and
+``mcdc/mcdc_set`` for variable-length fields. These helpers hide offset and
+stride arithmetic from transport code and remain callable from both Python and
+Numba-compiled functions.
+
+Conceptually, a generated element getter performs:
+
+.. code-block:: python
+
+   def z(index, mesh, data):
+       offset = mesh["z_offset"]
+       return data[offset + index]
+
+Generated helpers also provide operations for complete arrays, final elements,
+chunks, vectors, and multidimensional elements as appropriate. Transport code
+can therefore express logical access such as:
+
+.. code-block:: python
+
+   boundary = mcdc_get.structured_mesh.z(index, mesh, data)
+
+without depending on where that mesh's z-grid happens to reside in ``data``.
+
+Transport Consumption
+---------------------
+
+Modules under ``mcdc/transport`` consume only the runtime representation and
+primitive transport records. They use:
+
+- Direct structured-field access for fixed-size values and metadata.
+- Base and subtype IDs to navigate registered objects.
+- ``mcdc_get`` and ``mcdc_set`` for variable-length values.
+- The same function signatures in Python and Numba-CPU modes.
+
+The layout is fixed for the duration of a prepared run. Transport may update
+allocated values, tally bins, particle banks, and runtime counters, but it
+cannot resize a field or introduce a new model object. Changing the model
+requires a new model compilation and runtime-preparation pass.
+
+Execution Backends
+------------------
+
+Continue with :doc:`python_numba_cpu_execution` to see how Python mode and
+Numba-CPU mode consume this shared layout. GPU allocation and Harmonize
+integration are described in :doc:`numba_gpu_execution`.
diff --git a/docs/source/developer_guide/architecture/simulation_compilation.rst b/docs/source/developer_guide/architecture/simulation_compilation.rst
new file mode 100644
index 000000000..4225c89c3
--- /dev/null
+++ b/docs/source/developer_guide/architecture/simulation_compilation.rst
@@ -0,0 +1,335 @@
+.. _simulation_compilation:
+
+======================
+Simulation Compilation
+======================
+
+MC/DC begins with normal Python objects. Materials, surfaces, cells, sources,
+tallies, settings, and techniques can contain nested references and
+arbitrary-sized arrays. A :class:`mcdc.Simulation` owns the roots of one model
+and turns that connected object graph into a deterministic, simulation-local
+snapshot.
+
+This first compilation stage is entirely a Python operation. It establishes
+the model that later runtime preparation will pack for Python, Numba-CPU, or
+Numba-GPU execution.
+
+Why a Simulation Context Is Needed
+----------------------------------
+
+A Monte Carlo transport model is a connected system rather than a collection
+of independent definitions. A cell is not complete without its bounding
+surfaces and fill; a material may depend on nuclides, elements, reactions, and
+their data; and sources and tallies may refer to distributions, meshes, or
+geometry objects. The same object may also be shared by several parts of the
+model.
+
+These relationships are assembled incrementally with ordinary Python
+references. While the model is being built, an individual object cannot know
+its final position among all objects of the same kind, whether another branch
+of the model will refer to it, or which subtype-specific collection will
+contain it. Finalizing each object when it is created would therefore make
+model construction depend on definition order and require process-wide
+registration.
+
+:class:`mcdc.Simulation` provides the owning context for this delayed
+finalization. After the model cells, sources, tallies, settings, and techniques
+have been configured, compilation can inspect the complete reachable object
+graph at once. It registers shared objects only once, resolves relationships
+into simulation-local identifiers, and produces a consistent snapshot for
+runtime preparation.
+
+Here, *context* means the explicit model scope owned by a ``Simulation``
+instance, not a Python ``with`` context manager.
+
+Terminology
+-----------
+
+MC/DC uses several related forms of compilation:
+
+.. list-table::
+   :header-rows: 1
+   :widths: 24 38 38
+
+   * - Term
+     - Responsibility
+     - Primary implementation
+   * - Model compilation
+     - Discover objects, register them once, and assign local IDs.
+     - ``Simulation.compile`` and
+       ``mcdc/code_factory/python_objects_compiler.py``
+   * - Runtime preparation
+     - Derive run state and pack the model into ``simulation`` and ``data``.
+     - ``mcdc.main.prepare`` and
+       ``mcdc/code_factory/numba_layers_generator.py``
+   * - Backend compilation
+     - Compile shared transport functions for a CPU or GPU target.
+     - Numba and, for GPUs, Harmonize
+
+Unless otherwise qualified, this page uses *compilation* to mean model
+compilation.
+
+Ownership and Roots
+-------------------
+
+Every calculation begins with an explicit simulation:
+
+.. code-block:: python
+
+   simulation = mcdc.Simulation("Shielding")
+   simulation.set_model([source_cell, shield_cell])
+   simulation.set_sources([source])
+   simulation.set_tallies([flux_tally])
+
+The setter calls identify the roots of the user model:
+
+- ``set_model`` places cells in the simulation's root universe.
+- ``set_sources`` retains the sources sampled by transport.
+- ``set_tallies`` retains the requested scoring definitions.
+- Settings and transport techniques are embedded objects already owned by the
+  simulation.
+
+There is no process-wide model singleton. Multiple ``Simulation`` instances can
+be constructed and configured in the same Python process, provided each owns a
+distinct object graph. Model objects are included only when they are reachable
+from a simulation's roots or embedded configuration.
+
+Ownership Boundary and Process Model
+------------------------------------
+
+MC/DC intentionally uses a serial-in-process execution model: one
+``Simulation`` is compiled, prepared, or executed at a time within a Python
+process. A model-object instance belongs to one simulation context.
+
+References may be shared freely within that context. For example, several
+cells may use the same material, and compilation will register that material
+once. The same material instance must not be attached to a second
+``Simulation``. Compilation metadata such as ``compile_ID``, ``ID``, and
+``sub_ID`` is stored on the Python object and describes only its owning
+simulation's current snapshot.
+
+This ownership rule keeps ordinary model construction and recursive
+compilation lightweight. Applications that need concurrent calculations should
+create an independent model graph in each process and manage those processes
+from an outer Python driver, workflow system, or batch scheduler. Process-level
+orchestration is the supported parallelism boundary for multiple independent
+simulations.
+
+The MC/DC Object Hierarchy
+--------------------------
+
+The classes in ``mcdc/object_/base.py`` give every part of the model a common
+compilation lifecycle:
+
+.. code-block:: text
+
+   MCDCBase
+   └── MCDCObject
+       └── MCDCPolymorphic
+
+The distinction between these classes is about identity in a compiled
+simulation. All three can contribute fields to the packed runtime layout, but
+only ``MCDCObject`` and ``MCDCPolymorphic`` instances are registered as
+independently addressable model entities.
+
+``MCDCBase``: Embedded State and Traversal
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+``MCDCBase`` is the foundation for Python-side model and runtime definitions.
+Each subclass declares a ``label`` and type-annotated fields. The annotations
+serve two related purposes:
+
+- Assignment validation catches incompatible model values during construction.
+- The Numba-layer generator uses the annotations to derive structured fields,
+  object references, and variable-length data access.
+
+An ``MCDCBase`` instance participates in recursive compilation and carries a
+``compile_ID``, but it does not receive an object ``ID`` or occupy a
+simulation-level registry. This behavior is appropriate for state that belongs
+to a parent rather than representing a separately addressable model entity.
+Examples include ``Simulation``, ``Settings``, transport-technique
+configuration, particle-bank metadata, and GPU metadata.
+``Simulation`` is the special root of this hierarchy: it starts compilation
+and owns the resulting registries instead of being registered in one.
+
+The default compilation method visits object-valued members and lists of
+members recursively. Fields named in ``non_numba`` are excluded from this
+default traversal and packed representation; the owning class handles them
+explicitly when special processing is required.
+
+``MCDCObject``: Registered Model Entities
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+``MCDCObject`` extends ``MCDCBase`` for entities that must be collected and
+referenced by transport. Examples include cells, surfaces, universes, lattices,
+sources, nuclides, and elements.
+
+When compilation reaches an ``MCDCObject``, ``register_object`` places it in
+the corresponding collection owned by the current ``Simulation`` and assigns
+its simulation-local ``ID``. Registration happens before the object's members
+are traversed. Consequently, another reference to the same Python instance can
+recognize that it is already registered, which both preserves sharing and
+terminates cycles.
+
+An ``ID`` identifies object position within one compiled simulation; it is not
+a permanent identity belonging to the Python object. Recompiling its owning
+simulation may assign a different ``ID``. Attaching the same object instance to
+another simulation is outside the ownership model.
+
+``MCDCPolymorphic``: Base and Concrete Representations
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+``MCDCPolymorphic`` extends ``MCDCObject`` for categories with multiple
+runtime representations. Meshes, distributions, tallies, and neutron and
+electron reactions use this pattern. For example, ``Tally`` defines the shared
+tally category, while ``TallySurfaceCrossing``, ``TallyCollision``, and
+``TallyTracklength`` provide estimator-specific representations.
+
+Each concrete polymorphic class declares a ``sub_type`` code. During
+registration, an instance receives two positions:
+
+- ``ID`` locates its base record in the heterogeneous category collection.
+- ``sub_ID`` locates its concrete record among objects with the same
+  ``sub_type``.
+
+By convention, the shared category class uses ``sub_type = -1`` and concrete
+subclasses use named integer constants. Their distinct ``label`` values also
+name the corresponding structured layouts and generated accessor modules.
+
+The packed base record stores ``sub_type`` and ``sub_ID``; the concrete record
+stores ``base_ID``. Transport can therefore move between the common category
+view and the subtype-specific data without retaining Python references or
+depending on Python dynamic dispatch.
+
+For the implementation steps required to add a field, registered category, or
+polymorphic subtype, see
+:doc:`../extending/extending_the_object_model`.
+
+Recursive Discovery
+-------------------
+
+``Simulation.compile`` assigns a new ``compile_ID``, clears the previous
+registries, and walks the object graph:
+
+#. Reserved ``None`` representations are registered.
+#. The root universe recursively reaches cells, regions, surfaces, fills,
+   universes, lattices, materials, nuclear data, and distributions.
+#. Sources and tallies are traversed from their explicit root lists.
+#. Settings, techniques, and their members are traversed from the simulation.
+
+The common lifecycle defined by the object hierarchy makes this traversal
+uniform: embedded ``MCDCBase`` members are visited in place, while
+``MCDCObject`` members are registered before their descendants are explored.
+
+.. image:: ../../images/developer_guide/architecture/object_graph_compilation.svg
+   :width: 100%
+   :alt: Shared Python model objects discovered recursively from simulation roots and registered once in simulation-local collections.
+
+Discovery follows actual Python references. For example, a root cell reaches
+its region, the region reaches its surfaces, and the cell's fill reaches its
+material or child universe. Users therefore attach root cells rather than
+manually registering every referenced object.
+
+Deduplication and Cycles
+------------------------
+
+An object's ``compile_ID`` records the compilation snapshot in which it most
+recently participated. When the traversal reaches the same object again during
+that snapshot, registration stops for that branch.
+
+This behavior has two purposes:
+
+- A material, surface, mesh, or other object shared in several places is
+  registered once.
+- Cycles among embedded configuration objects do not cause infinite
+  recursion.
+
+Deduplication is based on Python object identity within one compilation, not on
+equal field values. Two separately constructed materials with identical cross
+sections remain two objects unless a class performs its own canonicalization.
+
+Simulation-local IDs
+--------------------
+
+Registered objects receive identifiers that are meaningful only within the
+current compiled simulation:
+
+``ID``
+   Position in the corresponding simulation collection, such as all surfaces
+   or all materials.
+
+``sub_type``
+   Integer code identifying the concrete representation of a polymorphic
+   object, such as a surface-crossing, collision, or track-length tally.
+
+``sub_ID``
+   Position in the collection for that concrete subtype.
+
+The packed child record also carries ``base_ID`` so transport can move between
+the subtype-specific and base representations.
+
+For example, transport can inspect a tally base record's ``sub_type`` and
+``sub_ID`` and then select its estimator-specific record. These IDs replace
+Python object references in the runtime layer.
+
+Snapshot Lifecycle
+------------------
+
+``set_model``, ``set_sources``, and ``set_tallies`` invalidate the compiled
+state. ``run`` and ``visualize_model`` call ``compile`` automatically when the
+simulation is not compiled, so most user inputs do not need an explicit call.
+
+An explicit call is useful for inspecting discovered objects and assigned IDs:
+
+.. code-block:: python
+
+   simulation.compile()
+
+   print(simulation.materials)
+   print(source_cell.ID)
+   print(source_region_material.ID)
+
+IDs can change whenever the simulation is compiled again. They must not be
+stored as durable identifiers outside the current snapshot.
+
+Directly mutating an already attached object does not notify its owning
+simulation. After such a change to an explicitly compiled or visualized model,
+call ``simulation.compile()`` again before inspecting or visualizing the new
+snapshot. ``simulation.run()`` marks the snapshot uncompiled after execution,
+so a subsequent run recompiles it.
+
+Iterative Partial Updates
+^^^^^^^^^^^^^^^^^^^^^^^^^
+
+An iterative study can keep one simulation and change only part of its owned
+model between runs. For example, two sources can be reweighted while the
+geometry, materials, and tallies remain unchanged:
+
+.. code-block:: python
+
+   simulation.set_sources([source_left, source_right])
+
+   for iteration, left_fraction in enumerate([0.2, 0.5, 0.8]):
+       source_left.probability = left_fraction
+       source_right.probability = 1.0 - left_fraction
+       simulation.settings.output_name = f"source_mix_{iteration}"
+
+       simulation.compile()
+       simulation.run()
+
+Each call to ``compile`` assigns a new ``compile_ID`` and rebuilds a complete,
+consistent snapshot even though only the source probabilities changed. The
+objects remain owned by the same ``Simulation`` throughout the study.
+See :ref:`example_iterative_source_reweighting` for a complete executable
+example and comparison script.
+
+From Objects to Runtime Data
+----------------------------
+
+Model compilation leaves the original Python objects intact and populates the
+simulation's ordered registries. Runtime preparation then reads those objects,
+derives structured dtypes from their annotations, and packs their values.
+
+Continue with :doc:`runtime_data_layout` for that conversion. For the
+user-facing construct-to-output workflow, see
+:doc:`../../user_guide/simulation_lifecycle`.
diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
new file mode 100644
index 000000000..4768f2187
--- /dev/null
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -0,0 +1,335 @@
+.. _extending_the_object_model:
+
+==========================
+Extending the Object Model
+==========================
+
+MC/DC extensions normally begin as ordinary Python model objects, but an
+extension is complete only when its state and behavior are available in every
+required execution mode. This page describes how to extend the object model
+without breaking simulation-local compilation or the generated runtime layout.
+
+Read :doc:`../architecture/simulation_compilation` first for the
+``MCDCBase``--``MCDCObject``--``MCDCPolymorphic`` hierarchy. Read
+:doc:`../architecture/runtime_data_layout` for the structured ``simulation``
+record, flat ``data`` array, and generated accessors.
+
+When the new state is consumed during particle transport, continue with
+:doc:`writing_numba_compatible_transport_code` for type, dispatch, allocation,
+CPU/GPU compatibility, and verification guidance.
+
+Choose the Extension Type
+-------------------------
+
+Choose the narrowest extension that represents the new concept:
+
+.. list-table::
+   :header-rows: 1
+   :widths: 24 24 52
+
+   * - Change
+     - Starting point
+     - Use when
+   * - Add a field
+     - Existing class
+     - The concept already belongs to an existing model or configuration
+       object.
+   * - Add embedded state
+     - ``MCDCBase``
+     - The state belongs to one parent and does not need an independently
+       addressable entry in a simulation registry.
+   * - Add a registered category
+     - ``MCDCObject``
+     - Transport must refer to independently registered instances by
+       simulation-local ``ID``.
+   * - Add a representation to an existing category
+     - ``MCDCPolymorphic``
+     - The extension shares a category interface but needs a distinct packed
+       layout and dispatch code.
+
+Prefer adding a subtype to an existing polymorphic family over creating a new
+registered category when the new object has the same conceptual role. A new
+tally estimator, for example, belongs under ``Tally``; it does not need an
+unrelated top-level registry.
+
+The Common Class Contract
+-------------------------
+
+Every MC/DC model class must follow the conventions used by the compiler and
+Numba-layer generator.
+
+``label``
+   Provide a unique, stable, lower-case label such as ``structured_mesh``. The
+   label names generated structured layouts and the corresponding modules
+   under ``mcdc_get`` and ``mcdc_set``.
+
+Type annotations
+   Annotate every field that must be represented at runtime. Annotations define
+   scalar fields, embedded structures, object-ID references, and
+   variable-length payloads.
+
+Initialization
+   Assign every runtime-visible field a valid initial value. Subclasses of
+   ``MCDCObject`` must call ``super().__init__()`` so ``ID`` is initialized;
+   subclasses of ``MCDCPolymorphic`` must do the same so both ``ID`` and
+   ``sub_ID`` are initialized.
+
+``non_numba``
+   List Python-only fields that should not be traversed or packed
+   automatically. The class must explicitly convert any required information
+   from those fields into annotated runtime-visible fields before packing.
+
+Compilation hook
+   Use the inherited ``_compile_into_simulation`` implementation unless the
+   class must canonicalize objects, compile excluded references, or derive
+   fields from assigned object IDs.
+
+Ownership boundary
+   Design each model-object instance for one ``Simulation`` context. Reuse the
+   instance within that model when sharing is intentional, but construct a new
+   object graph for another simulation or process. Extension code must not keep
+   process-wide singleton model objects that can be attached to several
+   simulations.
+
+Represent Fields Deliberately
+-----------------------------
+
+The layer generator interprets annotations according to the field's role:
+
+.. list-table::
+   :header-rows: 1
+   :widths: 34 30 36
+
+   * - Example annotation
+     - Runtime representation
+     - Access pattern
+   * - ``active: bool`` or ``count: int``
+     - Scalar structured field
+     - Direct structured access
+   * - ``vector: Annotated[NDArray[float64], (3,)]``
+     - Fixed-size embedded array
+     - Direct structured access
+   * - ``grid: NDArray[float64]``
+     - Offset and length plus values in ``data``
+     - Generated accessor
+   * - ``table: Annotated[NDArray[float64], ("N", 3)]``
+     - Offset, length, and shape metadata plus flattened values
+     - Generated multidimensional accessor
+   * - ``mesh: MeshBase``
+     - Simulation-local object ID
+     - Lookup through the mesh collection
+   * - ``tallies: list[Tally]``
+     - Count and offset to IDs stored in ``data``
+     - Generated ID accessor
+
+Use an integer-only shape when an array is always the same size. Use symbolic
+dimensions when a shape depends on the model. Do not store a Python reference
+in transport-visible state; annotate it as an ``MCDCObject`` or polymorphic
+base so the packed layer records an ID.
+
+Adding a Field to an Existing Class
+-----------------------------------
+
+#. Add the annotation to the class that owns the concept.
+#. Initialize the field for every construction path.
+#. Decide whether it is fixed-size, variable-length, an embedded
+   ``MCDCBase``, or an ``MCDCObject`` reference.
+#. Update any compile hook that derives the field or converts a Python-only
+   input into its runtime representation.
+#. Consume the field through direct structured access or its generated
+   ``mcdc_get`` and ``mcdc_set`` helpers.
+#. Update the public docstring and API documentation when users can configure
+   the field.
+
+Avoid adding parallel state in several classes. If a value belongs to the
+simulation as a whole, place it in ``Simulation`` or one of its embedded
+configuration objects and pass or access that representation consistently.
+
+Adding Embedded ``MCDCBase`` State
+----------------------------------
+
+Use ``MCDCBase`` for configuration or runtime state that is owned by one
+parent. A minimal class has a label, annotated fields, and initialized values:
+
+.. code-block:: python
+
+   class NewTechnique(MCDCBase):
+       label = "new_technique"
+
+       active: bool
+       strength: float
+
+       def __init__(self) -> None:
+           super().__init__()
+           self.active = False
+           self.strength = 1.0
+
+Add an annotated field for the object to its owner and instantiate it with the
+owner. For simulation-wide configuration, this normally means adding the field
+to ``Simulation`` and constructing it in ``Simulation.__init__``. The embedded
+object participates in recursive compilation but does not require a registry
+branch or object ID.
+
+If the embedded object refers to an ``MCDCObject``, annotate that reference.
+The default traversal will register the referenced object when compilation
+reaches the embedded configuration.
+
+Adding a New ``MCDCObject`` Category
+------------------------------------
+
+A genuinely new registered category requires coordinated changes:
+
+#. Define the class with a unique ``label``, annotations, initialized fields,
+   and a call to ``super().__init__()``.
+#. Add the category collection to ``Simulation`` annotations and initialize or
+   reset it in ``Simulation._reset_model``.
+#. Import the category in
+   ``mcdc/code_factory/python_objects_compiler.py`` and add an
+   ``isinstance`` branch in ``register_object`` that selects its simulation
+   collection.
+#. Ensure the object is reachable from an existing simulation root or add an
+   explicit root and compilation step.
+#. Ensure the class's module is imported before
+   ``numba_layers_generator.py`` discovers the classes. A public class is
+   normally imported through ``mcdc/__init__.py``; an internal class must be
+   imported by another module in the compilation path.
+#. Add the collection and lookup behavior required by transport.
+
+Do not add a fallback registration branch that silently accepts unknown
+objects. An explicit category branch keeps registry ownership and runtime
+layout reviewable.
+
+Adding a Polymorphic Subtype
+----------------------------
+
+Adding a concrete subtype to an existing family is more localized than adding
+a category:
+
+#. Add a unique integer constant for the subtype.
+#. Inherit from the existing polymorphic base, such as ``MeshBase`` or
+   ``Tally``.
+#. Set a unique concrete ``label`` and the new ``sub_type`` constant.
+#. Call the base initializer so shared fields, ``ID``, and ``sub_ID`` are
+   initialized.
+#. Annotate and initialize subtype-specific fields.
+#. Import the subtype before layer generation and expose it from
+   ``mcdc/__init__.py`` when it is public.
+#. Add transport dispatch for the new ``sub_type`` and implement the
+   subtype-specific behavior.
+
+For example, the structural part of a mesh subtype follows this pattern:
+
+.. code-block:: python
+
+   class MeshNew(MeshBase):
+       label = "new_mesh"
+       sub_type = MESH_NEW
+
+       boundaries: NDArray[float64]
+
+       def __init__(self, boundaries, name="") -> None:
+           super().__init__(name)
+           self.boundaries = np.asarray(boundaries, dtype=float64)
+
+No new ``register_object`` branch is needed for a subtype of an already
+registered family. The existing ``isinstance(..., MeshBase)`` or corresponding
+category check places it in the base collection, while ``sub_type`` and
+``sub_ID`` connect it to its concrete packed collection.
+
+Custom Compilation Hooks
+------------------------
+
+Override ``_compile_into_simulation`` only when the default recursive traversal
+is insufficient. The common post-registration pattern is:
+
+.. code-block:: python
+
+   def _compile_into_simulation(self, simulation) -> bool:
+       if not super()._compile_into_simulation(simulation):
+           return False
+
+       # Referenced objects now have simulation-local IDs.
+       self.runtime_field = self.python_reference.ID
+       return True
+
+Calling ``super`` first registers an ``MCDCObject`` and recursively compiles its
+ordinary members. The Boolean return prevents repeated work when the same
+object is reached again.
+
+Some classes must canonicalize or replace members before the default traversal.
+In that case, check ``compile_ID`` before doing the work, update the
+runtime-visible members, and then call ``super`` exactly once:
+
+.. code-block:: python
+
+   def _compile_into_simulation(self, simulation) -> bool:
+       if self.compile_ID == simulation.compile_ID:
+           return False
+
+       self._resolve_python_inputs(simulation)
+
+       if not super()._compile_into_simulation(simulation):
+           return False
+
+       self._derive_post_registration_fields()
+       return True
+
+Do not assign ``compile_ID``, ``ID``, or ``sub_ID`` manually. The shared
+compiler owns those values.
+
+Generated Runtime Layers and Accessors
+--------------------------------------
+
+``numba_layers_generator.py`` derives the structured dtypes, flat-data
+metadata, and accessor targets from the completed model classes. It writes:
+
+- ``mcdc/numba_types.py`` for structured dtype definitions.
+- ``mcdc/mcdc_get/<label>.py`` for generated reads.
+- ``mcdc/mcdc_set/<label>.py`` for generated writes.
+- ``mcdc_get/__init__.py`` and ``mcdc_set/__init__.py`` for generated module
+  imports.
+
+Do not implement a generated accessor by hand. Express the field correctly in
+the class annotation, prepare a representative simulation, and allow the layer
+generator to regenerate the modules. Then use the generated helper from
+transport code. Fixed-size fields do not need helpers and can be accessed
+directly from the structured record.
+
+Public API and Documentation
+----------------------------
+
+For a user-facing class or constructor:
+
+#. Export the class from ``mcdc/__init__.py``.
+#. Add it to the appropriate autosummary group in
+   ``docs/source/reference/python_api/index.rst``.
+#. Document parameters, units, defaults, constraints, and at least one usable
+   example in the class docstring.
+#. Update the User Guide when the extension changes how users construct or run
+   a model.
+
+Internal helper classes should remain under ``mcdc.object_`` and should not be
+exported merely to make discovery work. Import them explicitly in the
+compilation path instead.
+
+Verification Checklist
+----------------------
+
+An object-model extension should verify all affected layers:
+
+- Construction accepts valid input and rejects invalid shapes or types.
+- Compilation discovers the object from the intended root.
+- Shared references register once, and recompilation produces a valid new
+  snapshot.
+- Separate simulations use independently constructed model-object instances.
+- Packed fields, object IDs, offsets, and generated accessors contain the
+  expected values.
+- Python and Numba-CPU modes produce equivalent behavior.
+- GPU execution is covered when the changed transport path supports GPUs.
+- Public examples compile under the example validator when the API changes.
+- API and developer documentation build without warnings.
+
+Add focused unit tests near ``test/unit/test_object_compilation.py`` for
+compilation behavior and near the relevant transport tests for runtime
+behavior. Use :doc:`../../contributing/example_validation` when an extension
+changes public examples.
diff --git a/docs/source/developer_guide/extending/index.rst b/docs/source/developer_guide/extending/index.rst
new file mode 100644
index 000000000..4e62e60d3
--- /dev/null
+++ b/docs/source/developer_guide/extending/index.rst
@@ -0,0 +1,26 @@
+.. _extending_mcdc:
+
+===============
+Extending MC/DC
+===============
+
+This section provides implementation-oriented guidance for adding new model
+concepts and transport capabilities to MC/DC. It complements the
+:doc:`../architecture/index`, which explains the existing design, by describing
+the changes an extension must make across the Python model, compilation,
+generated runtime layers, transport implementation, public API, and tests.
+
+Start with :doc:`extending_the_object_model` when adding a field to an existing
+model class, introducing simulation-owned configuration, creating a registered
+model-object category, or implementing a new polymorphic subtype. Continue with
+:doc:`writing_numba_compatible_transport_code` when the extension adds or
+changes code executed during particle transport.
+
+Use the :doc:`../../contributing/index` for repository setup, test commands,
+continuous-integration coverage, and pull-request requirements.
+
+.. toctree::
+   :maxdepth: 1
+
+   extending_the_object_model
+   writing_numba_compatible_transport_code
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
new file mode 100644
index 000000000..1b5206880
--- /dev/null
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -0,0 +1,236 @@
+.. _writing_numba_compatible_transport_code:
+
+=======================================
+Writing Numba-Compatible Transport Code
+=======================================
+
+Transport code in MC/DC is written in Python but may execute as Python,
+Numba-compiled CPU code, or Numba-compiled GPU device code. A successful
+extension begins with correct Python behavior, then preserves that behavior
+while moving through the increasingly restrictive CPU and GPU compilation
+targets.
+
+Read :doc:`../architecture/python_first_numba_accelerated_design` first for the
+reason behind this development model. If the change introduces new model
+state, also read :doc:`extending_the_object_model` and
+:doc:`../architecture/runtime_data_layout`.
+
+Choose the Host or Transport Layer
+----------------------------------
+
+Place work on the host when it changes the model or prepares execution:
+
+- Validate and normalize user input.
+- Traverse Python objects or inspect their classes.
+- Add, remove, or resize model data.
+- Read files, construct tables, or derive run-wide configuration.
+- Allocate the packed state needed by transport.
+
+Place work in transport when it must be performed during particle execution:
+
+- Inspect or mutate particle records.
+- Evaluate geometry or physics from prepared numerical data.
+- Sample distributions and update the random-number state.
+- Score tallies or update preallocated banks and counters.
+
+Do as much irregular work as practical before transport. A small amount of
+host-side preparation can turn a dynamic operation into simple indexed access
+inside a frequently called kernel.
+
+Work Python First
+-----------------
+
+An exploratory method may begin as unrestricted pure Python, using whichever
+data structures make the algorithm easiest to understand and verify. This
+prototype is a valid stopping point for a small study that does not need
+compiled performance.
+
+Integration into MC/DC begins by adapting the verified method to the packed
+runtime inputs used by transport. Decorate the integrated function with
+``@njit`` like the surrounding transport functions; in Python mode, MC/DC
+disables JIT compilation and calls the same function as Python.
+
+.. code-block:: python
+
+   from numba import njit
+
+
+   @njit
+   def apply_weight_factor(particle_container, factor):
+       particle = particle_container[0]
+       particle["w"] *= factor
+
+Keep the function small enough that its inputs, outputs, and mutations are
+clear. First exercise it in Python mode to verify the algorithm and obtain an
+ordinary traceback. Then run it in Numba-CPU mode to verify type inference.
+Finally, adapt and validate it for Numba-GPU. Each stage may reveal constraints
+that were irrelevant to the preceding implementation.
+
+Use Runtime Data, Not Model Objects
+-----------------------------------
+
+A transport function should accept scalars, NumPy arrays, structured records,
+one-element record containers, and the packed ``simulation`` and ``data``
+state. It should not accept an ``MCDCObject`` instance or follow Python object
+references.
+
+Use the representation appropriate to each field:
+
+- Read fixed-size values directly from a structured record.
+- Follow registered relationships with their integer IDs.
+- Use ``sub_type`` and ``sub_ID`` for polymorphic dispatch.
+- Use generated ``mcdc_get`` and ``mcdc_set`` helpers for variable-length
+  fields in ``data``.
+- Mutate only state allocated during runtime preparation.
+
+If the required value is unavailable in this form, extend the object model and
+generated runtime layer before writing the transport behavior. Do not create a
+parallel Python-only lookup inside the kernel.
+
+Keep Types Stable
+-----------------
+
+Numba determines a compiled function's types from its arguments and control
+flow. Make those types unambiguous:
+
+- Initialize local variables on every path before use.
+- Return the same number and compatible types of values from every branch.
+- Avoid changing a variable from a scalar to an array or from an integer to an
+  unrelated object.
+- Use explicit integer and floating-point constants when their width or
+  signedness affects an operation.
+- Keep structured-record field names fixed; do not compute field names at run
+  time.
+- Avoid heterogeneous Python lists, dictionaries, sets, generators, and
+  dynamically created classes in transport.
+
+Numba may accept a construct on the CPU without making it available on the GPU.
+When a function is shared, compatibility with the stricter target is the
+relevant standard.
+
+Represent Variable-Length Data Explicitly
+-----------------------------------------
+
+Do not recover variable-length model data by allocating a new Python
+container. Read it from ``data`` using the metadata in its owning record.
+Prefer the generated accessor because it preserves the layout convention:
+
+.. code-block:: python
+
+   value = mcdc_get.tally.energy(index, tally, data)
+
+An ``*_all`` or ``*_chunk`` helper may expose a view when an algorithm needs a
+range. Element access is preferable when the kernel only needs one value. Do
+not resize the returned view or retain it beyond the prepared run.
+
+For a new variable-length field, declare the field on the Python model class
+and regenerate its accessors as described in
+:doc:`extending_the_object_model`. Do not hand-maintain offset arithmetic in
+several transport modules.
+
+Use Explicit Dispatch
+---------------------
+
+Dispatch on integer constants through a small interface function rather than
+using Python ``isinstance`` checks or methods on runtime records:
+
+.. code-block:: python
+
+   @njit
+   def get_mesh_x(index, mesh, simulation, data):
+       sub_ID = mesh["sub_ID"]
+       if mesh["sub_type"] == MESH_STRUCTURED:
+           concrete = simulation["structured_meshes"][sub_ID]
+           return mcdc_get.structured_mesh.x(index, concrete, data)
+       if mesh["sub_type"] == MESH_UNIFORM:
+           concrete = simulation["uniform_meshes"][sub_ID]
+           return concrete["x0"] + index * concrete["dx"]
+       return 0.0
+
+Use the actual category interface and constants already defined for that
+family. When adding a subtype, update every exhaustive dispatch site and test
+an unsupported value deliberately if the interface defines fallback behavior.
+
+Control Allocation and Mutation
+-------------------------------
+
+Particle histories repeatedly execute transport functions, so temporary
+allocation can be both expensive and difficult to support consistently across
+targets.
+
+- Reuse particle containers, banks, tally arrays, and scratch state allocated
+  during preparation.
+- Update structured fields or ``data`` through explicit assignments and
+  generated setters.
+- Prefer scalar calculations or bounded loops over constructing intermediate
+  Python collections.
+- Do not append a new model entity or change a field's shape during transport.
+- Preserve the one-element container convention when a mutable record must be
+  shared across function boundaries.
+
+The owner of each mutation should be evident from the function signature.
+Avoid hidden module-level mutable state.
+
+Stay Within the CPU/GPU Common Subset
+-------------------------------------
+
+For code intended to run on both targets:
+
+- Use numerical control flow and operations already established in nearby
+  shared transport modules.
+- Avoid Python exceptions as ordinary control flow.
+- Keep file access, printing, timing, MPI orchestration, and other host
+  services outside device functions.
+- Do not use Numba ``objmode`` in a path that must execute on the GPU.
+- Avoid relying on a CPU-only Numba feature merely because Numba-CPU compiles
+  it.
+- Keep target-specific atomics, memory operations, and scheduling behind the
+  existing GPU adaptation layer.
+
+Backend-specific code is appropriate when the execution model truly differs.
+Keep the shared numerical operation in ``mcdc/transport`` when possible, and
+put only the required adaptation under ``mcdc/code_factory/gpu``. Document why
+the paths differ and test their physical equivalence.
+
+Debug in Layers
+---------------
+
+When a change fails, isolate the layer:
+
+#. **Python construction** -- confirm that the model compiles and the expected
+   objects, IDs, offsets, and data are present.
+#. **Python transport** -- verify the algorithm and state mutation with JIT
+   disabled.
+#. **Numba-CPU** -- resolve typing, unsupported-operation, and compiled-runtime
+   failures.
+#. **Numba-GPU** -- resolve device compilation, memory, atomic, and scheduling
+   failures.
+
+Do not begin by diagnosing a GPU compiler error if the same calculation is
+already incorrect in Python. Conversely, a passing Python test does not prove
+that the function is type-stable or device compatible.
+
+Verification Checklist
+----------------------
+
+Before considering a transport extension complete:
+
+- The model compiles into the expected packed representation.
+- Focused unit tests exercise the new numerical behavior in Python.
+- The same tests or representative regression case pass in Numba-CPU mode.
+- Python and Numba-CPU results agree within the test's numerical tolerance.
+- A supported GPU environment exercises the path.
+- GPU results preserve the same physical behavior within appropriate
+  numerical and statistical tolerances.
+- Existing examples still construct successfully when the public API or model
+  compilation changed.
+- User and developer documentation describe any new behavior or limitation.
+
+A general feature merged and maintained as part of MC/DC must complete all
+three execution stages unless the maintainers explicitly accept and document a
+backend-specific limitation. Experimental or study-specific work may stop at
+Python or Numba-CPU when that stage already satisfies its purpose.
+
+Repository commands, continuous-integration coverage, and regression-test
+options belong in the :doc:`../../contributing/index`. For changes affecting
+public inputs, follow :doc:`../../contributing/example_validation`.
diff --git a/docs/source/developer_guide/index.rst b/docs/source/developer_guide/index.rst
index 0a94de59a..5b9b5ab0a 100644
--- a/docs/source/developer_guide/index.rst
+++ b/docs/source/developer_guide/index.rst
@@ -7,16 +7,20 @@ Developer Guide
 The Developer Guide explains how MC/DC works internally and how to extend or
 maintain its implementation.
 
-- Read :doc:`architecture/index` to understand the execution framework and
-  major internal layers.
+- Read :doc:`architecture/index` for MC/DC's Python-first design and to follow
+  the model through compilation, runtime preparation, CPU execution, and GPU
+  execution.
+- Read :doc:`extending/index` when adding model fields, registered objects,
+  polymorphic subtypes, or Numba-compatible transport behavior.
 - Read :doc:`documentation/index` when writing or reviewing project
   documentation.
 - Use the :doc:`../contributing/index` for repository setup, development
   workflow, testing, and pull-request requirements.
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
 
    architecture/index
+   extending/index
    documentation/index
    Contributing <../contributing/index>
diff --git a/docs/source/examples/index.rst b/docs/source/examples/index.rst
index ce8ea6417..0a0154c65 100644
--- a/docs/source/examples/index.rst
+++ b/docs/source/examples/index.rst
@@ -20,7 +20,9 @@ parameter changes for further exploration.
 
 If you are learning MC/DC for the first time, complete the
 :doc:`../user_guide/getting_started/first_simulation` before using these examples as
-templates. For individual API details, consult the :doc:`../reference/index`.
+templates. The :doc:`../user_guide/simulation_lifecycle` explains the workflow
+shared by every input. For individual API details, consult the
+:doc:`../reference/index`.
 
 Basic Examples
 --------------
@@ -29,6 +31,7 @@ Basic Examples
    :maxdepth: 1
 
    slab_shielding
+   iterative_source_reweighting
    kobayashi_dog_leg
    kobayashi_td
 
diff --git a/docs/source/examples/iterative_source_reweighting.rst b/docs/source/examples/iterative_source_reweighting.rst
new file mode 100644
index 000000000..c1c6c91f5
--- /dev/null
+++ b/docs/source/examples/iterative_source_reweighting.rst
@@ -0,0 +1,48 @@
+.. _example_iterative_source_reweighting:
+
+============================
+Iterative Source Reweighting
+============================
+
+This one-group fixed-source example demonstrates partial model updates across
+several runs of one :class:`mcdc.Simulation`. A homogeneous slab contains
+symmetric left and right sources. Each iteration changes only their relative
+probabilities, compiles a complete new snapshot, and writes a separate output
+file.
+
+The three source mixtures are 20/80, 50/50, and 80/20. Because the geometry and
+material are symmetric, the 20/80 and 80/20 flux profiles should approximately
+mirror one another, while the 50/50 profile should be approximately symmetric
+about the slab midpoint.
+
+Full Input
+----------
+
+.. literalinclude:: ../../../examples/iterative_source_reweighting/input.py
+   :language: python
+   :linenos:
+
+Post-processing
+---------------
+
+.. literalinclude:: ../../../examples/iterative_source_reweighting/process-output.py
+   :language: python
+   :linenos:
+
+The post-processing script overlays the three spatial flux profiles, prints
+the integrated flux in each half of the slab, and reports two symmetry
+comparisons.
+
+How to Run
+----------
+
+From inside ``examples/iterative_source_reweighting``:
+
+.. code-block:: sh
+
+   python input.py
+   python process-output.py
+
+The calculation writes ``source_mix_left_20.h5``,
+``source_mix_left_50.h5``, and ``source_mix_left_80.h5``. Post-processing
+writes ``iterative_source_comparison.png``.
diff --git a/docs/source/images/developer_guide/architecture/architecture_flow.svg b/docs/source/images/developer_guide/architecture/architecture_flow.svg
new file mode 100644
index 000000000..ed9a7b365
--- /dev/null
+++ b/docs/source/images/developer_guide/architecture/architecture_flow.svg
@@ -0,0 +1 @@
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new file mode 100644
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diff --git a/docs/source/images/theory/gpu_comp/amd_flow.png b/docs/source/images/developer_guide/architecture/numba_gpu_amd_flow.png
similarity index 100%
rename from docs/source/images/theory/gpu_comp/amd_flow.png
rename to docs/source/images/developer_guide/architecture/numba_gpu_amd_flow.png
diff --git a/docs/source/images/theory/gpu_comp/nvcc_flow.png b/docs/source/images/developer_guide/architecture/numba_gpu_nvidia_flow.png
similarity index 100%
rename from docs/source/images/theory/gpu_comp/nvcc_flow.png
rename to docs/source/images/developer_guide/architecture/numba_gpu_nvidia_flow.png
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+  <text x="500" y="363" class="mono">capture_length = 2</text>
+
+  <line x1="335" y1="190" x2="440" y2="190" style="stroke:#566573;stroke-width:2.5"/>
+  <line x1="335" y1="320" x2="440" y2="320" style="stroke:#566573;stroke-width:2.5"/>
+  <text x="387" y="175" text-anchor="middle" class="body">metadata</text>
+
+  <rect x="875" y="75" width="290" height="330" class="box" fill="#e8f8f5"/>
+  <text x="1020" y="108" text-anchor="middle" class="label">flat data array</text>
+
+  <rect x="905" y="145" width="230" height="54" class="box" fill="#d6eaf8"/>
+  <text x="1020" y="168" text-anchor="middle" class="mono">0 · 1 · 2 · 3</text>
+  <text x="1020" y="190" text-anchor="middle" class="body">mesh.z</text>
+
+  <rect x="905" y="215" width="230" height="54" class="box" fill="#d5f5e3"/>
+  <text x="1020" y="238" text-anchor="middle" class="mono">0.1 · 0.2</text>
+  <text x="1020" y="260" text-anchor="middle" class="body">material.capture</text>
+
+  <rect x="905" y="285" width="230" height="54" class="box" fill="#f5eef8"/>
+  <text x="1020" y="308" text-anchor="middle" class="mono">… flattened scatter …</text>
+  <text x="1020" y="330" text-anchor="middle" class="body">next payload</text>
+
+  <text x="1020" y="370" text-anchor="middle" class="mono">data[0:N]</text>
+  <line x1="765" y1="190" x2="865" y2="190" style="stroke:#566573;stroke-width:2.5"/>
+  <line x1="765" y1="330" x2="865" y2="330" style="stroke:#566573;stroke-width:2.5"/>
+  <text x="815" y="175" text-anchor="middle" class="body">offsets</text>
+
+  <rect x="180" y="465" width="840" height="90" class="box" fill="#f4ecf7"/>
+  <text x="600" y="495" text-anchor="middle" class="label">generated mcdc_get / mcdc_set helpers</text>
+  <text x="600" y="523" text-anchor="middle" class="mono">z(i, mesh, data) → data[mesh["z_offset"] + i]</text>
+  <text x="600" y="546" text-anchor="middle" class="body">transport uses logical fields without embedding Python references</text>
+
+  <line x1="607" y1="405" x2="607" y2="455" style="stroke:#566573;stroke-width:2.5"/>
+  <path d="M1020 405 C1020 445, 900 450, 845 465" style="stroke:#566573;stroke-width:2.5;fill:none"/>
+</svg>
diff --git a/docs/source/project/index.rst b/docs/source/project/index.rst
index 6659011bf..fbbd72b4f 100644
--- a/docs/source/project/index.rst
+++ b/docs/source/project/index.rst
@@ -8,9 +8,11 @@ Project information collects material about MC/DC as a research software
 project rather than instructions for using or developing the code.
 
 Use :doc:`publications` to find overview and method-specific references for
-published work.
+published work. Read :doc:`release_policy` for the project's release cadence
+and handling of bug-fix releases.
 
 .. toctree::
    :maxdepth: 1
 
    publications
+   release_policy
diff --git a/docs/source/project/release_policy.rst b/docs/source/project/release_policy.rst
new file mode 100644
index 000000000..809ecf04c
--- /dev/null
+++ b/docs/source/project/release_policy.rst
@@ -0,0 +1,30 @@
+.. _release_policy:
+
+==============
+Release Policy
+==============
+
+MC/DC follows `Semantic Versioning <https://semver.org/>`_ and maintains its
+release history in
+`CHANGELOG.md <https://github.com/mcdc-project/mcdc/blob/dev/CHANGELOG.md>`_.
+
+Minor Releases
+--------------
+
+MC/DC plans a minor release each month. These releases collect compatible
+features, improvements, and fixes that have passed the project's required
+review and validation.
+
+The monthly schedule is a target rather than a reason to release unverified
+work. A release may be delayed when additional testing, documentation, or
+integration work is needed.
+
+Patch Releases
+--------------
+
+Bug fixes are not held until the next monthly minor release. Once a fix has
+passed review and the relevant validation and release checks, MC/DC publishes
+a patch release as soon as practical.
+
+Published versions and release notes are available from the
+`MC/DC releases page <https://github.com/mcdc-project/mcdc/releases>`_.
diff --git a/docs/source/reference/python_api/index.rst b/docs/source/reference/python_api/index.rst
index 1dd2dc234..6e1584618 100644
--- a/docs/source/reference/python_api/index.rst
+++ b/docs/source/reference/python_api/index.rst
@@ -21,7 +21,9 @@ sources, and tallies to a simulation, and then visualize or run that simulation:
    simulation.run()
 
 The complete public interfaces and additional examples are documented on each
-linked API page.
+linked API page. For a task-oriented explanation of how these objects move
+through construction, compilation, execution, and output, see
+:doc:`../../user_guide/simulation_lifecycle`.
 
 
 Simulation
@@ -141,3 +143,7 @@ needed, executes particle transport, and writes the configured output.
 ``simulation.visualize_model(...)`` similarly compiles when needed before
 rendering the model. Use ``simulation.compile()`` when an explicit compiled
 snapshot is required before either operation.
+
+The internal compilation and packing stages are documented in
+:doc:`../../developer_guide/architecture/simulation_compilation` and
+:doc:`../../developer_guide/architecture/runtime_data_layout`.
diff --git a/docs/source/user_guide/execution/cpu.rst b/docs/source/user_guide/execution/cpu.rst
index 76c9f9436..472cacf68 100644
--- a/docs/source/user_guide/execution/cpu.rst
+++ b/docs/source/user_guide/execution/cpu.rst
@@ -11,6 +11,9 @@ The instructions below assume you have an existing MC/DC installation.
 MPI can be quite tricky to configure if on an HPC; if you're having trouble,
 consult our :ref:`installation`, your HPC admin, or our `GitHub issues page <https://github.com/mcdc-project/mcdc/issues>`_.
 
+For the architectural relationship between Python and Numba-CPU execution, see
+:doc:`../../developer_guide/architecture/python_numba_cpu_execution`.
+
 Pure Python Mode
 ----------------
 
@@ -29,7 +32,8 @@ Numba Mode
 
 When running in Numba mode a significant amount of time is taken compiling Python functions to performant binaries.
 Only the functions used in a specific simulation will be compiled.
-These binaries will be cached, meaning that in subsequent runs of the same simulation the compilation step can be avoided.
+When ``--caching`` is enabled, compiled binaries can be reused by subsequent
+runs of a compatible simulation.
 The cache can be used as an effective ahead-of-time compilation scheme where binaries can be compiled once and shared between machines.
 For more information on caching, see :ref:`contributing/index:Caching` and
 `Numba Caching <https://numba.readthedocs.io/en/stable/developer/caching.html>`_.
diff --git a/docs/source/user_guide/execution/gpu.rst b/docs/source/user_guide/execution/gpu.rst
index 704a19d8d..da98f8fea 100644
--- a/docs/source/user_guide/execution/gpu.rst
+++ b/docs/source/user_guide/execution/gpu.rst
@@ -10,6 +10,9 @@ When targeting GPUs execution MC/DC uses the Harmonize library to schedule event
 Harmonize acts as the GPU runtime for MC/DC and has two major scheduling schemes including a novel asynchronous event scheduler.
 For more information on Harmonize and how we compile MC/DC with it see our publications in M&C 2025.
 
+For the developer-level compilation and runtime design, see
+:doc:`../../developer_guide/architecture/numba_gpu_execution`.
+
 Single GPU Launches
 -------------------
 
diff --git a/docs/source/user_guide/getting_started/first_simulation.rst b/docs/source/user_guide/getting_started/first_simulation.rst
index e13506a12..293789924 100644
--- a/docs/source/user_guide/getting_started/first_simulation.rst
+++ b/docs/source/user_guide/getting_started/first_simulation.rst
@@ -12,6 +12,9 @@ components: materials, geometry, particle sources, tallies, and simulation
 settings. In MC/DC, these components are represented by Python objects and
 assembled into a :class:`mcdc.Simulation`.
 
+This tutorial applies the general :doc:`../simulation_lifecycle` to one
+complete problem.
+
 The example uses multigroup data defined directly in the input, so it does not
 require an external nuclear-data library. Its complete, executable source is
 available in ``examples/slab_shielding``.
@@ -19,12 +22,13 @@ available in ``examples/slab_shielding``.
 MC/DC Workflow
 --------------
 
-An MC/DC calculation follows four main steps:
+An MC/DC calculation follows five main steps:
 
 #. Construct the materials, geometry, sources, and tallies.
 #. Create a simulation and attach the model objects to it.
-#. Configure settings and transport techniques.
-#. Run particle transport and analyze the output.
+#. Configure settings and compile the connected object graph.
+#. Visualize or run the prepared model.
+#. Generate and post-process the output.
 
 .. important::
 
diff --git a/docs/source/user_guide/index.rst b/docs/source/user_guide/index.rst
index 99cc9c63d..3c5d71fed 100644
--- a/docs/source/user_guide/index.rst
+++ b/docs/source/user_guide/index.rst
@@ -24,9 +24,13 @@ complete your first transport calculation.
 Modeling and Results
 --------------------
 
+Follow :doc:`simulation_lifecycle` for the complete construct, compile,
+visualize, execute, and post-process workflow.
+
 .. toctree::
    :maxdepth: 1
 
+   simulation_lifecycle
    tallies
 
 Execution
diff --git a/docs/source/user_guide/simulation_lifecycle.rst b/docs/source/user_guide/simulation_lifecycle.rst
new file mode 100644
index 000000000..5df61b023
--- /dev/null
+++ b/docs/source/user_guide/simulation_lifecycle.rst
@@ -0,0 +1,189 @@
+.. _simulation_lifecycle:
+
+====================
+Simulation Lifecycle
+====================
+
+An MC/DC calculation is owned by a :class:`mcdc.Simulation`. The simulation
+collects one model, its sources and tallies, its settings and techniques, and
+the runtime state needed to visualize or execute it.
+
+The normal workflow has five stages:
+
+#. Construct model objects.
+#. Attach the model roots to a simulation.
+#. Compile the connected object graph.
+#. Visualize or run the prepared model.
+#. Generate and post-process output.
+
+Most inputs call only ``visualize_model`` or ``run`` explicitly. MC/DC performs
+the required compilation and runtime preparation automatically.
+
+1. Construct Model Objects
+--------------------------
+
+Materials, surfaces, cells, sources, meshes, and tallies are ordinary Python
+objects:
+
+.. code-block:: python
+
+   material = mcdc.MaterialMG(
+       capture=np.array([0.1]),
+       scatter=np.array([[0.9]]),
+   )
+   left = mcdc.Surface.PlaneZ(z=0.0, boundary_condition="vacuum")
+   right = mcdc.Surface.PlaneZ(z=2.0, boundary_condition="vacuum")
+   cell = mcdc.Cell(region=+left & -right, fill=material)
+
+Objects can refer to other objects. In this example the cell retains its
+region, the region retains its surfaces, and the cell retains its material.
+
+2. Attach Roots to a Simulation
+-------------------------------
+
+Create a simulation and attach the roots from which MC/DC can discover the
+complete model:
+
+.. code-block:: python
+
+   simulation = mcdc.Simulation("Slab")
+   simulation.set_model([cell])
+   simulation.set_sources([source])
+   simulation.set_tallies([tally])
+
+``set_model`` accepts the cells in the root universe. Materials, surfaces,
+child universes, lattices, and meshes that are reachable from those cells do
+not need separate registration calls.
+
+Sources and tallies are explicit roots because they are not necessarily
+reachable from the geometry. Settings and techniques belong directly to the
+simulation:
+
+.. code-block:: python
+
+   simulation.settings.N_particle = 10_000
+   simulation.settings.N_batch = 20
+   simulation.implicit_capture()
+
+This explicit ownership replaces the former process-wide singleton workflow.
+
+Process Ownership
+^^^^^^^^^^^^^^^^^
+
+MC/DC runs one active simulation context at a time within a Python process.
+Objects may be shared within one model—for example, several cells may use the
+same material—but the same object instance should not be attached to different
+``Simulation`` instances.
+
+Multiple simulations can be constructed in one process when they have
+independent object graphs and are run serially. For concurrent calculations,
+construct each model and run its simulation in a separate process. A Python
+driver, workflow system, or batch scheduler can manage those processes.
+
+3. Compile the Object Graph
+---------------------------
+
+Compilation discovers every object reachable from the simulation, registers
+shared objects once, and assigns simulation-local IDs. Normally it is
+automatic:
+
+- ``simulation.visualize_model(...)`` compiles when needed.
+- ``simulation.run()`` compiles when needed.
+
+Call ``simulation.compile()`` directly only when you need to inspect the
+compiled object lists or IDs before visualization or execution:
+
+.. code-block:: python
+
+   simulation.compile()
+   print(simulation.cells)
+   print(material.ID)
+
+Compiled IDs describe one snapshot and may change after recompilation. Do not
+use them as persistent identifiers in an input or post-processing workflow.
+
+The three setter methods invalidate the current snapshot. If you directly
+modify an attached object after explicitly compiling or visualizing the model,
+call ``simulation.compile()`` again before inspecting or visualizing the
+change.
+
+4. Visualize or Run
+-------------------
+
+Visualization is a useful geometry check before transport:
+
+.. code-block:: python
+
+   simulation.visualize_model(
+       vis_plane="xz",
+       x=[-1.0, 1.0],
+       y=0.0,
+       z=[0.0, 2.0],
+       pixels=(100, 200),
+       colors=None,
+       time=[0.0],
+       save_as="slab_geometry",
+   )
+
+Run transport after validating the model:
+
+.. code-block:: python
+
+   simulation.run()
+
+Begin in Python mode:
+
+.. code-block:: sh
+
+   python input.py --mode=python
+
+After the model and workflow are correct, enable Numba-CPU:
+
+.. code-block:: sh
+
+   python input.py --mode=numba
+
+GPU execution adds another acceleration and runtime layer:
+
+.. code-block:: sh
+
+   python input.py --mode=numba --target=gpu
+
+See :doc:`execution/cpu` and :doc:`execution/gpu` for operational guidance.
+
+5. Process Output
+-----------------
+
+``simulation.run()`` writes the configured HDF5 output. Use stable tally names
+and a companion post-processing script so the relationship between an input
+and its analysis remains clear:
+
+.. code-block:: python
+
+   tally = mcdc.Tally(
+       name="slab_flux",
+       mesh=mesh,
+       scores=["flux"],
+   )
+   simulation.set_tallies([tally])
+   simulation.settings.output_name = "slab"
+
+The tally is then available under ``tallies/slab_flux`` in ``slab.h5``.
+
+Complete Workflows
+------------------
+
+The example suite demonstrates the lifecycle in complete inputs:
+
+- :ref:`example_slab_shielding` — fixed-source execution, model
+  visualization, and output processing.
+- :ref:`example_iterative_source_reweighting` — partial model updates and
+  repeated compilation within one simulation.
+- :ref:`example_moving_source` — transient fixed-source transport.
+- :ref:`example_c5g7_k_eigenvalue` — k-eigenvalue execution.
+- :ref:`example_c5g7_transient` — a larger reactor transient.
+
+For exact public signatures, use the :doc:`../reference/python_api/index`.
+Framework developers can continue with
+:doc:`../developer_guide/architecture/simulation_compilation` and
+:doc:`../developer_guide/architecture/runtime_data_layout`.
diff --git a/examples/iterative_source_reweighting/input.py b/examples/iterative_source_reweighting/input.py
new file mode 100644
index 000000000..d9ff586f0
--- /dev/null
+++ b/examples/iterative_source_reweighting/input.py
@@ -0,0 +1,60 @@
+import numpy as np
+
+import mcdc
+
+simulation = mcdc.Simulation("Iterative source reweighting")
+
+# Homogeneous one-group slab
+material = mcdc.MaterialMG(
+    capture=np.array([0.2]),
+    scatter=np.array([[0.8]]),
+)
+left_boundary = mcdc.Surface.PlaneZ(z=0.0, boundary_condition="vacuum")
+right_boundary = mcdc.Surface.PlaneZ(z=10.0, boundary_condition="vacuum")
+slab = mcdc.Cell(
+    region=+left_boundary & -right_boundary,
+    fill=material,
+)
+simulation.set_model([slab])
+
+# Symmetric source regions
+source_left = mcdc.Source(
+    name="Left source",
+    z=[1.0, 2.0],
+    isotropic=True,
+    energy_group=0,
+)
+source_right = mcdc.Source(
+    name="Right source",
+    z=[8.0, 9.0],
+    isotropic=True,
+    energy_group=0,
+)
+simulation.set_sources([source_left, source_right])
+
+# One tally is reused by every iteration
+mesh = mcdc.MeshStructured(z=np.linspace(0.0, 10.0, 51))
+flux_tally = mcdc.Tally(
+    name="source_mix_flux",
+    mesh=mesh,
+    scores=["flux"],
+)
+simulation.set_tallies([flux_tally])
+
+simulation.settings.N_particle = 20_000
+simulation.settings.N_batch = 10
+
+# Partially update the same owned model and compile a fresh snapshot each time.
+source_mixes = (
+    ("left_20", 0.2),
+    ("left_50", 0.5),
+    ("left_80", 0.8),
+)
+
+for case_name, left_fraction in source_mixes:
+    source_left.probability = left_fraction
+    source_right.probability = 1.0 - left_fraction
+    simulation.settings.output_name = f"source_mix_{case_name}"
+
+    simulation.compile()
+    simulation.run()
diff --git a/examples/iterative_source_reweighting/process-output.py b/examples/iterative_source_reweighting/process-output.py
new file mode 100644
index 000000000..4fd1a75ec
--- /dev/null
+++ b/examples/iterative_source_reweighting/process-output.py
@@ -0,0 +1,84 @@
+from pathlib import Path
+
+import h5py
+import matplotlib.pyplot as plt
+import numpy as np
+
+cases = (
+    ("left_20", "20% left / 80% right"),
+    ("left_50", "50% left / 50% right"),
+    ("left_80", "80% left / 20% right"),
+)
+
+profiles = {}
+uncertainties = {}
+z = None
+
+for case_name, _ in cases:
+    output_path = Path(f"source_mix_{case_name}.h5")
+    with h5py.File(output_path, "r") as output:
+        tally = output["tallies/source_mix_flux"]
+        case_z = tally["grid/z"][:]
+        flux = tally["flux/mean"][:]
+        flux_sdev = tally["flux/sdev"][:]
+
+    if z is None:
+        z = case_z
+    elif not np.array_equal(z, case_z):
+        raise ValueError(f"Inconsistent tally grid in {output_path}")
+
+    dz = case_z[1:] - case_z[:-1]
+    profiles[case_name] = flux / dz
+    uncertainties[case_name] = flux_sdev / dz
+
+z_mid = 0.5 * (z[:-1] + z[1:])
+dz = z[1:] - z[:-1]
+left_half = z_mid < 5.0
+right_half = ~left_half
+
+print("Integrated flux comparison")
+print("--------------------------")
+for case_name, label in cases:
+    profile = profiles[case_name]
+    left_flux = np.sum(profile[left_half] * dz[left_half])
+    right_flux = np.sum(profile[right_half] * dz[right_half])
+    print(
+        f"{label:24s}  left={left_flux:.6e}  right={right_flux:.6e}  "
+        f"left/right={left_flux / right_flux:.4f}"
+    )
+
+mirror_difference = np.linalg.norm(profiles["left_20"] - profiles["left_80"][::-1])
+mirror_scale = np.linalg.norm(0.5 * (profiles["left_20"] + profiles["left_80"][::-1]))
+balanced_difference = np.linalg.norm(profiles["left_50"] - profiles["left_50"][::-1])
+balanced_scale = np.linalg.norm(profiles["left_50"])
+
+print()
+print(
+    "20/80 versus mirrored 80/20 relative RMS difference: "
+    f"{mirror_difference / mirror_scale:.4e}"
+)
+print(
+    "50/50 profile relative left-right asymmetry: "
+    f"{balanced_difference / balanced_scale:.4e}"
+)
+
+figure, axis = plt.subplots()
+for case_name, label in cases:
+    profile = profiles[case_name]
+    uncertainty = uncertainties[case_name]
+    axis.plot(z_mid, profile, label=label)
+    axis.fill_between(
+        z_mid,
+        profile - uncertainty,
+        profile + uncertainty,
+        alpha=0.15,
+    )
+
+axis.axvline(5.0, color="black", linestyle="--", linewidth=1.0)
+axis.set_xlabel("z [cm]")
+axis.set_ylabel("Flux")
+axis.grid()
+axis.legend()
+figure.tight_layout()
+figure.savefig("iterative_source_comparison.png", dpi=150)
+plt.close(figure)
diff --git a/mcdc/code_factory/numba_objects_generator.py b/mcdc/code_factory/numba_layers_generator.py
similarity index 99%
rename from mcdc/code_factory/numba_objects_generator.py
rename to mcdc/code_factory/numba_layers_generator.py
index 3702421fc..e7ac5a739 100644
--- a/mcdc/code_factory/numba_objects_generator.py
+++ b/mcdc/code_factory/numba_layers_generator.py
@@ -83,13 +83,13 @@
 ]
 
 # ======================================================================================
-# Numba object creation
+# Numba layer creation
 # ======================================================================================
 
 
-def generate_numba_objects(simulation):
+def generate_numba_layers(simulation):
     # ==================================================================================
-    # Allocate key items for the Numba object:
+    # Allocate key items for the Numba runtime layers:
     #   - Python annotations
     #   - Numba structures
     #   - Records
@@ -311,7 +311,10 @@ def generate_numba_objects(simulation):
     # Print the fields
     if MPI.COMM_WORLD.Get_rank() == 0:
         with open(f"{Path(mcdc.__file__).parent}/numba_types.py", "w") as f:
-            text = "# The following is automatically generated by code_factory.py\n\n"
+            text = (
+                "# The following is automatically generated by "
+                "numba_layers_generator.py\n\n"
+            )
             text += "from numpy import bool_\n"
             text += "from numpy import float64\n"
             text += "from numpy import int64\n"
@@ -319,7 +322,7 @@ def generate_numba_objects(simulation):
             text += "from numpy import uintp\n"
             text += "\n###\n\n"
             text += (
-                "from mcdc.code_factory.numba_objects_generator import into_dtype\n\n"
+                "from mcdc.code_factory.numba_layers_generator import into_dtype\n\n"
             )
 
             for label in structures.keys():
diff --git a/mcdc/main.py b/mcdc/main.py
index 3a18296d6..01ee56487 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -235,15 +235,15 @@ def prepare(simulationPy):
     simulationPy.bank_future.size[0] = size_future
 
     # ==================================================================================
-    # Generate Numba-supported "Objects"
+    # Generate Numba runtime layers
     # ==================================================================================
 
-    from mcdc.code_factory.numba_objects_generator import generate_numba_objects
+    from mcdc.code_factory.numba_layers_generator import generate_numba_layers
     from mcdc.code_factory.literals_generator import make_literals
 
     make_literals(simulationPy)
 
-    simulation_container, data = generate_numba_objects(simulationPy)
+    simulation_container, data = generate_numba_layers(simulationPy)
     simulation = simulation_container[0]
 
     # Reload mcdc getters and setters
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index 5ee16a2c4..2dd5832c2 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -1,4 +1,4 @@
-# The following is automatically generated by code_factory.py
+# The following is automatically generated by numba_layers_generator.py
 
 from numpy import bool_
 from numpy import float64
@@ -8,7 +8,7 @@
 
 ###
 
-from mcdc.code_factory.numba_objects_generator import into_dtype
+from mcdc.code_factory.numba_layers_generator import into_dtype
 
 particle_data = into_dtype([
     ('x', float64),
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 051e431af..538494235 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -60,6 +60,11 @@ class Simulation(MCDCBase):
     resulting object graph, assigns IDs, and prepares it for conversion to the
     packed arrays consumed by :mod:`mcdc.transport`.
 
+    MC/DC uses one active simulation context per Python process. A model-object
+    instance belongs to one simulation, although it may be referenced multiple
+    times within that model. Construct independent object graphs and use
+    separate processes for concurrent simulations.
+
     Each simulation owns its execution settings. Access them through
     ``simulation.settings`` by assigning values such as
     :attr:`settings.N_particle <mcdc.Simulation.settings.N_particle>` or by
diff --git a/test/unit/test_example_inputs.py b/test/unit/test_example_inputs.py
new file mode 100644
index 000000000..5eb7475e3
--- /dev/null
+++ b/test/unit/test_example_inputs.py
@@ -0,0 +1,41 @@
+import runpy
+from pathlib import Path
+
+import pytest
+
+import mcdc
+
+EXAMPLES_ROOT = Path(__file__).parents[2] / "examples"
+EXAMPLE_INPUTS = tuple(sorted(EXAMPLES_ROOT.glob("**/input.py")))
+assert EXAMPLE_INPUTS, "No example inputs found"
+
+
+def example_id(input_path):
+    return str(input_path.relative_to(EXAMPLES_ROOT).parent)
+
+
+@pytest.mark.parametrize("input_path", EXAMPLE_INPUTS, ids=example_id)
+def test_example_constructs_and_compiles_simulation(input_path, monkeypatch):
+    """Validate every example input without running particle transport."""
+    compiled_simulations = []
+
+    def compile_only(simulation, *args, **kwargs):
+        simulation.compile()
+        compiled_simulations.append(simulation)
+
+    monkeypatch.setattr(mcdc.Simulation, "run", compile_only)
+    monkeypatch.setattr(mcdc.Simulation, "visualize_model", compile_only)
+    monkeypatch.chdir(input_path.parent)
+
+    runpy.run_path(input_path.name, run_name="__main__")
+
+    assert compiled_simulations
+    unique_simulations = {
+        id(simulation): simulation for simulation in compiled_simulations
+    }
+    assert len(unique_simulations) == 1
+    simulation = next(iter(unique_simulations.values()))
+    assert simulation.compiled
+    assert simulation.cells
+    assert simulation.sources
+    assert simulation.tallies

From 048b45b553b3d3320a486be0f2197fb6678b5cd8 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 31 Jul 2026 17:33:01 +0700
Subject: [PATCH 068/202] add docs on numba use

---
 .../python_first_numba_accelerated_design.rst | 349 ++++++++++++------
 .../python_numba_cpu_execution.rst            |  14 +
 ...riting_numba_compatible_transport_code.rst |  36 +-
 3 files changed, 269 insertions(+), 130 deletions(-)

diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
index 5df62e992..cbed17505 100644
--- a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -4,23 +4,150 @@
 Python-First, Numba-Accelerated Design
 ======================================
 
-MC/DC is designed for Monte Carlo methods development in Python while retaining
-an execution path suitable for large transport calculations. Python is the
-language in which users construct models and developers express transport
-algorithms. Numba is the acceleration layer that specializes those algorithms
-for CPUs and helps make them available to GPU execution.
+MC/DC is a Python-based environment for developing Monte Carlo transport
+methods, but large calculations also require compiled performance.
+*Python-first* means that developers can build and validate a method with the
+full Python language and ecosystem before addressing the requirements of
+accelerated execution. Numba provides the bridge between these goals—but what
+is Numba, and why is it a good fit for MC/DC?
+
+What Is Numba?
+--------------
+
+`Numba <https://numba.readthedocs.io/en/stable/user/5minguide.html>`_ is a
+just-in-time (JIT) compiler for numerical Python. When a function marked with a
+Numba decorator such as ``@njit`` is called, Numba examines the argument types
+and translates supported Python, NumPy, and loop operations into machine code
+specialized for those types. Compilation happens as the program runs rather
+than in a separate build step.
+
+Numba does not compile the entire Python language. Efficient compilation
+requires numerical types, predictable control flow, and supported operations.
+Arbitrary Python objects, dynamic behavior, and calls into unsupported
+packages remain useful during prototyping but must be removed, replaced, or
+moved outside compiled functions.
+
+MC/DC uses Numba as the bridge between Python development and accelerated
+transport. Its common transport path supports three *execution backends*, or
+environments that run the integrated functions:
+
+- **Python** executes the functions through the interpreter with JIT
+  compilation disabled.
+- **Numba-CPU** compiles the functions into machine code for the host CPU.
+- **Numba-GPU** compiles device functions for an accelerator, while Harmonize
+  provides the GPU runtime that schedules particle work.
 
-*Python-first* describes the order in which MC/DC is understood and developed:
-establish correct behavior in Python, accelerate the same typed transport path
-with Numba-CPU, and then satisfy the additional constraints of Numba-GPU and
-Harmonize. It does not mean that transport operates directly on the rich
-Python object graph.
+Why MC/DC Uses Numba
+--------------------
+
+Numba lets MC/DC keep its maintained transport algorithms in Python while
+specializing them for the model and hardware used by a calculation. This
+supports several project goals:
+
+- New transport methods can begin in the language and scientific ecosystem
+  already used to construct MC/DC models.
+- The integrated Python backend provides ordinary Python tracebacks while
+  exercising the same transport functions and data flow used by acceleration.
+- Numba-CPU accelerates those functions without requiring a separate
+  implementation in C, C++, or Fortran.
+- The typed transport interfaces provide a common foundation for CPU and GPU
+  execution, with backend-specific adaptation where the hardware requires it.
+
+The choice therefore preserves an expressive starting point while providing a
+path to compiled execution. It also introduces the constraints discussed in
+the remainder of this page.
+
+Staged Methods Development
+--------------------------
 
-Where Each Layer Runs
----------------------
+Pure-Python Prototype
+^^^^^^^^^^^^^^^^^^^^^
 
-MC/DC deliberately separates flexible model construction from constrained
-transport execution:
+A method may begin as a pure-Python prototype, either independently or through
+direct modifications to MC/DC. At this stage, the priority is to establish the
+method's correctness, understand its behavior, and test it on problems small
+enough that compiled performance is unnecessary.
+
+The prototype may use arbitrary Python objects, module-level global state,
+manual imports, dynamic dispatch, callbacks, hard-coded assumptions, or direct
+edits to transport routines. It may call packages such as SciPy or Matplotlib
+during transport, perform file I/O, or visualize intermediate state. These
+choices are acceptable because the prototype prioritizes scientific
+expressiveness and rapid validation over performance, encapsulation,
+dependency discipline, and compiler compatibility.
+
+No prototype framework or service is required. Researchers may use the most
+direct implementation that answers the question being studied. Prototype-only
+packages do not need to become MC/DC dependencies, and the prototype is not
+expected to remain in its original form.
+
+This freedom is permission, not a required style. A developer familiar with
+MC/DC and Numba may voluntarily use typed data, the packed representation, and
+compiler-compatible operations from the beginning. A nearly Numba-compatible
+prototype can substantially reduce later porting work without turning
+Python-first development into a compiler-first requirement.
+
+MC/DC Integration and Python Execution
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Integration begins when the method adopts MC/DC's standard execution path.
+User-facing model objects are compiled into an ordered, simulation-owned model
+and then packed into numerical runtime state. Here, *model compilation* means
+discovering connected Python objects and assigning simulation-local integer
+IDs; it is distinct from Numba JIT compilation.
+
+The packed runtime has two main parts: a structured ``simulation`` record for
+fixed-layout state and a flat ``data`` array for variable-length values. MC/DC
+Python mode runs the integrated transport functions against this
+representation with JIT compilation disabled. It therefore provides ordinary
+Python tracebacks while exercising the same data flow and function interfaces
+used by the accelerated backends.
+
+Numba-CPU Compilation
+^^^^^^^^^^^^^^^^^^^^^
+
+Once the method is verified and larger calculations require more performance,
+Numba JIT compilation can be enabled for the CPU. Unless the prototype was
+already written against the compatible subset, reaching this stage requires
+deliberate porting rather than simply changing an execution option. Python
+constructs that Numba cannot type or compile are removed or replaced with
+explicit numerical types, stable control flow, packed runtime data, and
+supported operations.
+
+Numba-GPU Compilation
+^^^^^^^^^^^^^^^^^^^^^
+
+GPU execution is a further stage. Device code typically imposes additional
+constraints involving memory placement, allocation, interaction with the host
+CPU, synchronized updates, and Harmonize scheduling. Some code that works with
+Numba-CPU therefore requires further adaptation before it can execute on a
+GPU.
+
+Valid Stopping Points
+^^^^^^^^^^^^^^^^^^^^^
+
+Each stage can be a useful endpoint:
+
+- **Pure-Python prototype** is sufficient for exploring a method and answering
+  a focused research question.
+- **MC/DC Python** is sufficient for integrated debugging and small
+  calculations.
+- **Numba-CPU** is sufficient when compiled CPU performance meets the
+  calculation's needs.
+- **Numba-GPU** provides the final portability stage when accelerator
+  performance is required.
+
+This staged workflow allows researchers to stop when their immediate objective
+has been achieved. A general feature intended to be merged and maintained as
+part of MC/DC, however, must work in MC/DC Python, Numba-CPU, and Numba-GPU
+unless the maintainers explicitly accept and document a backend-specific
+limitation.
+
+The Standard Execution Path
+---------------------------
+
+After prototyping, MC/DC's standard path separates flexible model construction
+from constrained transport execution:
 
 .. list-table::
    :header-rows: 1
@@ -45,84 +172,27 @@ transport execution:
      - HDF5 output and analysis objects
      - Python
 
-The Python stages may use object-oriented interfaces, variable-length
-collections, validation, and other features that make model construction
-clear. The transport stage uses stable numerical types, arrays, integer IDs,
-and explicit function calls that compilation targets can understand.
-
-Why MC/DC Uses Numba
---------------------
-
-Numba lets MC/DC preserve a Python implementation of its numerical algorithms
-while compiling type-stable functions for a hardware target at run time. This
-supports several project goals:
-
-- Researchers can implement and inspect transport methods in Python.
-- Python mode provides a direct path for debugging algorithm and data-flow
-  errors.
-- Numba-CPU can specialize the same transport functions without maintaining a
-  separate implementation in another language.
-- The typed runtime representation and transport interfaces provide a
-  foundation for GPU code generation and Harmonize scheduling.
-
-The result is one conceptual transport implementation, with backend-specific
-adaptation where the hardware requires it. GPU support is not automatic for
-arbitrary Python or arbitrary Numba-CPU code; transport intended for all three
-modes must stay within their supported common subset.
-
-Staged Methods Development
---------------------------
-
-Python-first also describes how new methods are typically developed. A method
-usually begins as a pure-Python prototype, either independently or in MC/DC's
-Python execution mode. At this stage, the priority is to establish the
-method's correctness, understand its behavior, and test it on problems small
-enough that compiled performance is unnecessary.
-
-Once the method is verified and larger calculations require more performance,
-the implementation can advance to Numba-CPU. This step is more than enabling
-JIT compilation: Python constructs that Numba cannot type or compile may need
-to be replaced with explicit numerical types, stable control flow, packed
-runtime data, and supported operations.
-
-Numba-GPU is a further stage. Device execution typically imposes additional
-constraints involving memory placement, allocation, host interaction, atomics,
-and Harmonize scheduling. Some code that works with Numba-CPU therefore
-requires further adaptation before it can execute on a GPU.
-
-Each stage is a useful endpoint:
-
-- **Python** is sufficient for prototyping methods, diagnosing behavior, and
-  running small problems.
-- **Numba-CPU** is sufficient when compiled CPU performance meets the
-  calculation's needs.
-- **Numba-GPU** provides the final portability stage when accelerator
-  performance is required.
-
-This staged workflow allows researchers to stop when their immediate objective
-has been achieved. A general feature intended to be merged and maintained as
-part of MC/DC, however, must work in Python, Numba-CPU, and Numba-GPU unless
-the maintainers explicitly accept and document a backend-specific limitation.
-
-An independent pure-Python prototype may use data structures chosen only for
-exploration. Once integrated into MC/DC, however, Python mode still performs
-model compilation and runtime preparation. It is the reference execution mode
-for the same packed transport path that later stages accelerate.
+Model construction and preparation may use object-oriented interfaces,
+variable-length collections, validation, and other expressive Python features.
+The boundary occurs at integrated transport, where compilation targets require
+stable numerical types, arrays, integer IDs, and explicit function calls.
 
 Architectural Consequences
 --------------------------
 
-Using Numba shapes the boundary between MC/DC's model and execution layers.
-The following are architectural requirements rather than incidental
-implementation details.
+Once a method enters the integrated path, Numba shapes the boundary between
+MC/DC's model and execution layers. The following requirements do not constrain
+the initial prototype, but they are fundamental to maintained transport code.
 
 Model Objects Are Not Runtime Objects
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 Materials, cells, sources, tallies, and related objects are convenient
-descriptions of a model. Before transport, MC/DC discovers the complete object
-graph and converts Python references into simulation-local IDs. Transport
-receives packed records and arrays, not instances of ``MCDCObject``.
+descriptions of a model. Before integrated transport, MC/DC discovers the
+complete object graph and converts Python references into simulation-local
+IDs. The maintained transport path receives packed records and arrays, not
+instances of ``MCDCObject``, the base class for independently registered model
+entities.
 
 See :doc:`simulation_compilation` for the owning ``Simulation`` context,
 recursive discovery, and the ``MCDCBase``--``MCDCObject``--
@@ -133,8 +203,8 @@ Execution Data Has a Stable Layout
 
 The types and collection sizes needed by a run are finalized before transport.
 Fixed-layout values are stored in the structured ``simulation`` record.
-Variable-length and ragged numerical values are flattened into ``data`` and
-described by offsets, lengths, and shapes.
+Variable-length numerical values, including nested arrays whose lengths differ,
+are flattened into ``data`` and described by offsets, lengths, and shapes.
 
 This representation avoids dynamic Python containers in transport and gives
 all backends the same logical state. Generated ``mcdc_get`` and ``mcdc_set``
@@ -145,9 +215,10 @@ Dispatch Is Explicit
 ^^^^^^^^^^^^^^^^^^^^
 
 Python dynamic dispatch is replaced by integer type codes and explicit
-branches in transport interfaces. A polymorphic base record stores
-``sub_type`` and ``sub_ID``; transport uses them to select the concrete packed
-record and implementation.
+branches in transport interfaces. For a model category with several concrete
+representations, its common record stores ``sub_type`` and ``sub_ID``.
+Transport uses those values to select the concrete packed record and
+implementation.
 
 This makes the possible execution paths visible to Numba and keeps runtime
 behavior independent of Python object identity.
@@ -166,7 +237,8 @@ CPU and GPU Share a Deliberate Subset
 Numba-CPU supports some operations that are unavailable or unsuitable inside a
 GPU device function. Code shared by the two targets must use explicit numeric
 types, supported NumPy operations, predictable control flow, and preallocated
-state. Host callbacks, Python objects, and object-mode escapes must remain
+state. Host callbacks, Python objects, and Numba ``objmode`` blocks—which
+temporarily return compiled CPU code to the Python interpreter—must remain
 outside GPU transport paths.
 
 MC/DC may use target-specific modules when execution, memory, atomics, or
@@ -176,50 +248,85 @@ default so that backend implementations do not drift apart.
 Design Tradeoffs
 ----------------
 
-The architecture makes methods development and compiled execution share a
-language and much of an implementation, but the boundary has costs:
+The staged approach does not eliminate development cost; it defers some of that
+cost until a method has demonstrated enough value to justify integration.
 
-- Runtime-visible state must be declared and packed before execution.
-- Dynamic Python conveniences cannot be used inside compiled transport paths.
-- New model concepts often require coordinated object, layout, accessor,
-  transport, and test changes.
-- Just-in-time compilation adds startup work and can produce typing errors that
-  do not appear in Python mode.
-- GPU support may require additional code generation, memory management, and
-  backend-specific implementations.
+An unrestricted Python prototype maximizes scientific expressiveness and
+minimizes the effort required to test an idea. The tradeoff is that parts of
+the prototype may need to be redesigned or rewritten for Numba-CPU. Beginning
+with MC/DC's packed runtime representation and Numba-compatible operations can
+reduce that porting effort, but introduces implementation constraints earlier
+in the research process.
 
-These constraints are accepted at the execution boundary so that the
-user-facing model and host-side development workflow can remain expressive.
+Once integrated, the shared execution architecture introduces additional
+costs:
+
+- Runtime-visible state must be declared and packed before execution.
+- Dynamic Python behavior must be removed from compiled transport paths.
+- New model concepts may require coordinated changes to objects, layouts,
+  accessors, transport functions, and tests.
+- Supporting Python, Numba-CPU, and Numba-GPU increases validation work.
+- Just-in-time compilation adds startup time and compiler-specific failure
+  modes.
+- GPU execution may require additional memory management, code generation,
+  atomics, and scheduling support.
+
+MC/DC accepts possible prototype rework so that early methods development
+remains unconstrained. It accepts the stricter integrated architecture so that
+maintained features can share transport logic across execution backends rather
+than becoming separate Python, CPU, and GPU implementations.
 
 Related Design Choices
 ----------------------
 
-Other designs emphasize different tradeoffs. A pure-Python solver would
-maximize dynamism but would not provide MC/DC's compiled execution path.
-Handwritten C, C++, or Fortran kernels could provide direct low-level control
-but would split methods development across languages and require a binding
-boundary. Passing the object graph directly to execution would retain its
-structure but make types, ownership, and accelerator data movement harder to
-control. Padding every ragged field into a rectangular array would simplify
-some indexing while increasing storage and obscuring the field's natural
-shape.
-
-MC/DC instead uses rich Python model objects on the host and a generated,
-typed, flat representation for execution. This section describes the current
-design space; it should not be read as a claim that every alternative was
+Alternative designs place the boundary between expressiveness and portability
+elsewhere. Requiring every prototype to follow the Numba-compatible subset
+would reduce later porting, but constrain exploration before the method's value
+is known. Maintaining a complete Python solver alongside separate optimized
+backends would preserve Python freedom indefinitely, but duplicate transport
+logic and allow implementations to drift.
+
+Handwritten C, C++, or Fortran kernels would provide direct low-level control,
+but split methods development across languages and introduce a binding
+boundary. Passing rich Python objects directly to every execution backend
+would preserve the prototype representation, but make typing, ownership, and
+accelerator data movement difficult to control.
+
+MC/DC instead uses staged convergence. A prototype may begin anywhere on the
+spectrum from an ad hoc Python experiment to a nearly Numba-compatible
+implementation. When the method needs compiled performance or becomes a
+maintained MC/DC capability, it converges on the shared typed transport path.
+The generated structured and flat runtime representation provides that common
+execution boundary without dictating how the original prototype must be
+written.
+
+These are design-space comparisons, not a claim that every alternative was
 implemented and benchmarked by the project.
 
 Future Evolution
 ----------------
 
 The Python-first principle does not require the present implementation to
-remain fixed. Future work may revise compilation-state ownership, generated
-layer lifecycles, typed-container support, or the boundary between common and
-backend-specific transport. Such changes should preserve three properties:
-
-- A clear Python path for developing and diagnosing transport behavior.
-- An explicit conversion from user model to execution state.
-- Equivalent physical behavior across supported execution backends.
+remain fixed. Future work should make movement between stages easier without
+narrowing the freedom of pure-Python exploration.
+
+Potential improvements fall into three areas:
+
+- **Prototype access** -- optionally make the active Python model and arbitrary
+  prototype state easier to reach during Python execution without requiring a
+  formal prototype framework.
+- **Integration assistance** -- improve inspection and conversion of model
+  state, generated layouts and accessors, and diagnostics that identify
+  compiler-incompatible code.
+- **Execution infrastructure** -- evolve where compilation state is stored,
+  when generated runtime layers are created and refreshed, how Numba typed
+  containers are used, and the boundary between shared and backend-specific
+  transport.
+
+Future changes should preserve the ability to stop at any development stage,
+keep the transition into maintained execution state explicit and reviewable,
+and retain equivalent physical behavior across the supported backends of an
+integrated feature.
 
 For the mechanisms behind this boundary, see :doc:`simulation_compilation` and
 :doc:`runtime_data_layout`. If following the main Architecture path, return to
diff --git a/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst b/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
index 46f3d5bf3..0faf6393b 100644
--- a/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
+++ b/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
@@ -59,6 +59,20 @@ Python mode is best for:
 Python mode does not bypass simulation compilation or runtime packing. It
 bypasses machine-code generation for the CPU transport functions.
 
+Exploratory Python Prototypes
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The description above is the standard MC/DC Python execution path. During
+initial methods development, researchers may temporarily depart from it in a
+standalone prototype or a locally modified MC/DC checkout. Prototype transport
+may access arbitrary Python objects or global state, import external packages,
+perform I/O or visualization, and use hard-coded or dynamic behavior.
+
+Such code is intentionally outside the common execution architecture and is
+not expected to compile with Numba unchanged. Advancing the method to
+Numba-CPU requires porting it back to the packed runtime representation and
+compiler-compatible interfaces.
+
 Before Numba Acceleration
 -------------------------
 
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index 1b5206880..a8056126b 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -4,17 +4,19 @@
 Writing Numba-Compatible Transport Code
 =======================================
 
-Transport code in MC/DC is written in Python but may execute as Python,
-Numba-compiled CPU code, or Numba-compiled GPU device code. A successful
-extension begins with correct Python behavior, then preserves that behavior
-while moving through the increasingly restrictive CPU and GPU compilation
-targets.
+Integrated transport code in MC/DC is written in Python but may execute as
+Python, Numba-compiled CPU code, or Numba-compiled GPU device code. A method may
+begin as a disposable pure-Python prototype before being ported into this
+shared execution path.
 
 Read :doc:`../architecture/python_first_numba_accelerated_design` first for the
 reason behind this development model. If the change introduces new model
 state, also read :doc:`extending_the_object_model` and
 :doc:`../architecture/runtime_data_layout`.
 
+The rules below apply when a prototype is being integrated and maintained as
+part of MC/DC. They are not restrictions on initial pure-Python exploration.
+
 Choose the Host or Transport Layer
 ----------------------------------
 
@@ -45,6 +47,22 @@ data structures make the algorithm easiest to understand and verify. This
 prototype is a valid stopping point for a small study that does not need
 compiled performance.
 
+At this stage, use module-level global state, arbitrary Python objects, ad hoc
+imports, dynamic behavior, file I/O, callbacks, visualization, hard-coded
+assumptions, or direct transport edits whenever they help answer the research
+question. Calls to packages such as SciPy and Matplotlib are acceptable even
+during transport. A formal prototype service or abstraction is not required.
+
+Keep prototype-only dependencies local to the experiment rather than adding
+them to MC/DC's required dependencies. The prototype is allowed to be
+disposable and is not expected to compile unchanged.
+
+Unrestricted prototyping is optional. A developer already familiar with MC/DC
+and Numba may begin with packed runtime inputs, stable types, and supported
+operations, producing an implementation that is nearly Numba-compatible from
+the start. This can minimize the deliberate porting work while preserving the
+freedom to use ordinary Python whenever it helps establish the method.
+
 Integration into MC/DC begins by adapting the verified method to the packed
 runtime inputs used by transport. Decorate the integrated function with
 ``@njit`` like the surrounding transport functions; in Python mode, MC/DC
@@ -69,10 +87,10 @@ that were irrelevant to the preceding implementation.
 Use Runtime Data, Not Model Objects
 -----------------------------------
 
-A transport function should accept scalars, NumPy arrays, structured records,
-one-element record containers, and the packed ``simulation`` and ``data``
-state. It should not accept an ``MCDCObject`` instance or follow Python object
-references.
+An integrated transport function should accept scalars, NumPy arrays,
+structured records, one-element record containers, and the packed
+``simulation`` and ``data`` state. It should not accept an ``MCDCObject``
+instance or follow Python object references.
 
 Use the representation appropriate to each field:
 

From 2f26243d621a4fc432bd7b9529f4a6225080a114 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 31 Jul 2026 17:47:09 +0700
Subject: [PATCH 069/202] use plain language in numba pge

---
 .../python_first_numba_accelerated_design.rst | 201 +++++++++---------
 1 file changed, 101 insertions(+), 100 deletions(-)

diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
index cbed17505..2c1a42d27 100644
--- a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -34,8 +34,8 @@ environments that run the integrated functions:
 - **Python** executes the functions through the interpreter with JIT
   compilation disabled.
 - **Numba-CPU** compiles the functions into machine code for the host CPU.
-- **Numba-GPU** compiles device functions for an accelerator, while Harmonize
-  provides the GPU runtime that schedules particle work.
+- **Numba-GPU** compiles device functions for an accelerator, while a
+  supporting runtime called Harmonize schedules particle work.
 
 Why MC/DC Uses Numba
 --------------------
@@ -82,26 +82,26 @@ packages do not need to become MC/DC dependencies, and the prototype is not
 expected to remain in its original form.
 
 This freedom is permission, not a required style. A developer familiar with
-MC/DC and Numba may voluntarily use typed data, the packed representation, and
-compiler-compatible operations from the beginning. A nearly Numba-compatible
-prototype can substantially reduce later porting work without turning
-Python-first development into a compiler-first requirement.
+MC/DC and Numba may voluntarily begin with simple numerical data and
+predictable operations that are already close to the compiled form. This can
+substantially reduce later porting work without turning Python-first
+development into a compiler-first requirement. Practical guidance is provided
+in :doc:`../extending/writing_numba_compatible_transport_code`.
 
 MC/DC Integration and Python Execution
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 Integration begins when the method adopts MC/DC's standard execution path.
-User-facing model objects are compiled into an ordered, simulation-owned model
-and then packed into numerical runtime state. Here, *model compilation* means
-discovering connected Python objects and assigning simulation-local integer
-IDs; it is distinct from Numba JIT compilation.
-
-The packed runtime has two main parts: a structured ``simulation`` record for
-fixed-layout state and a flat ``data`` array for variable-length values. MC/DC
-Python mode runs the integrated transport functions against this
-representation with JIT compilation disabled. It therefore provides ordinary
-Python tracebacks while exercising the same data flow and function interfaces
-used by the accelerated backends.
+MC/DC first gathers the complete user-defined model into a consistent snapshot
+for one simulation. This process is called *model compilation* and is distinct
+from Numba JIT compilation. See :doc:`simulation_compilation` for model
+ownership, discovery, and finalization.
+
+MC/DC then converts that snapshot into compact numerical execution data shared
+by all backends. Python mode runs the integrated transport functions against
+this data with JIT compilation disabled, providing ordinary Python tracebacks
+while exercising the same data flow used by acceleration. The conversion is
+described in :doc:`runtime_data_layout`.
 
 Numba-CPU Compilation
 ^^^^^^^^^^^^^^^^^^^^^
@@ -110,18 +110,21 @@ Once the method is verified and larger calculations require more performance,
 Numba JIT compilation can be enabled for the CPU. Unless the prototype was
 already written against the compatible subset, reaching this stage requires
 deliberate porting rather than simply changing an execution option. Python
-constructs that Numba cannot type or compile are removed or replaced with
-explicit numerical types, stable control flow, packed runtime data, and
-supported operations.
+features that Numba cannot compile are replaced with supported numerical forms
+and predictable control flow. See :doc:`python_numba_cpu_execution` for the
+execution path and
+:doc:`../extending/writing_numba_compatible_transport_code` for coding
+guidance.
 
 Numba-GPU Compilation
 ^^^^^^^^^^^^^^^^^^^^^
 
 GPU execution is a further stage. Device code typically imposes additional
-constraints involving memory placement, allocation, interaction with the host
-CPU, synchronized updates, and Harmonize scheduling. Some code that works with
-Numba-CPU therefore requires further adaptation before it can execute on a
-GPU.
+constraints on how data is stored and moved, how the GPU interacts with the
+host CPU, and how concurrent particle work is coordinated. Some code that
+works with Numba-CPU therefore requires further adaptation before it can
+execute on a GPU. These additional layers are described in
+:doc:`numba_gpu_execution`.
 
 Valid Stopping Points
 ^^^^^^^^^^^^^^^^^^^^^
@@ -157,16 +160,16 @@ from constrained transport execution:
      - Representation
      - Execution environment
    * - Model definition
-     - User-facing Python objects and references
+     - Flexible Python objects and relationships
      - Python
    * - Model compilation
-     - Simulation-owned, ordered object graph
+     - Complete, internally consistent model snapshot
      - Python
    * - Runtime preparation
-     - Structured ``simulation`` state and flat ``data``
+     - Compact numerical execution data
      - Python and NumPy
    * - Transport
-     - Typed functions operating on packed state
+     - Shared numerical algorithms
      - Python, Numba-CPU, or Numba-GPU
    * - Output and postprocessing
      - HDF5 output and analysis objects
@@ -175,7 +178,10 @@ from constrained transport execution:
 Model construction and preparation may use object-oriented interfaces,
 variable-length collections, validation, and other expressive Python features.
 The boundary occurs at integrated transport, where compilation targets require
-stable numerical types, arrays, integer IDs, and explicit function calls.
+predictable numerical data and explicit behavior. See
+:doc:`simulation_compilation` and :doc:`runtime_data_layout` for the two
+preparation stages, then :doc:`python_numba_cpu_execution` and
+:doc:`numba_gpu_execution` for backend execution.
 
 Architectural Consequences
 --------------------------
@@ -184,66 +190,55 @@ Once a method enters the integrated path, Numba shapes the boundary between
 MC/DC's model and execution layers. The following requirements do not constrain
 the initial prototype, but they are fundamental to maintained transport code.
 
-Model Objects Are Not Runtime Objects
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Materials, cells, sources, tallies, and related objects are convenient
-descriptions of a model. Before integrated transport, MC/DC discovers the
-complete object graph and converts Python references into simulation-local
-IDs. The maintained transport path receives packed records and arrays, not
-instances of ``MCDCObject``, the base class for independently registered model
-entities.
-
-See :doc:`simulation_compilation` for the owning ``Simulation`` context,
-recursive discovery, and the ``MCDCBase``--``MCDCObject``--
-``MCDCPolymorphic`` hierarchy.
+Model Description Becomes Execution Data
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Execution Data Has a Stable Layout
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Python objects are well suited for describing materials, geometry, sources,
+tallies, and their relationships. Compiled transport instead needs numerical
+data with predictable types and connections. MC/DC therefore turns the
+complete Python model into a simulation-specific numerical representation
+before execution.
 
-The types and collection sizes needed by a run are finalized before transport.
-Fixed-layout values are stored in the structured ``simulation`` record.
-Variable-length numerical values, including nested arrays whose lengths differ,
-are flattened into ``data`` and described by offsets, lengths, and shapes.
+The ownership and finalization of the Python model are explained in
+:doc:`simulation_compilation`. Its numerical representation is explained in
+:doc:`runtime_data_layout`.
 
-This representation avoids dynamic Python containers in transport and gives
-all backends the same logical state. Generated ``mcdc_get`` and ``mcdc_set``
-helpers centralize the corresponding indexing rules. See
-:doc:`runtime_data_layout` for the complete representation.
+The Execution Structure Is Fixed Before Transport
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Dispatch Is Explicit
-^^^^^^^^^^^^^^^^^^^^
+Preparation determines which model entities and data arrays exist for a run.
+Transport can update particle state, scores, banks, and counters, but it does
+not add new model entities or resize the model structure. Changing the model
+requires preparing a new execution snapshot.
 
-Python dynamic dispatch is replaced by integer type codes and explicit
-branches in transport interfaces. For a model category with several concrete
-representations, its common record stores ``sub_type`` and ``sub_ID``.
-Transport uses those values to select the concrete packed record and
-implementation.
+See :doc:`simulation_compilation` for the snapshot lifecycle and
+:doc:`runtime_data_layout` for what transport may read and update.
 
-This makes the possible execution paths visible to Numba and keeps runtime
-behavior independent of Python object identity.
+Dynamic Choices Become Explicit
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Mutation Is Bounded
-^^^^^^^^^^^^^^^^^^^
+Ordinary Python can choose behavior dynamically from object types and methods.
+Compiled transport makes those choices visible through numerical tags,
+explicit branches, and stable function interfaces. This allows Numba to see
+the possible execution paths before generating machine code.
 
-Transport updates particle state, banks, tallies, and counters in storage
-allocated during preparation. It does not add model objects or resize the
-model's runtime layout. A model change therefore produces a new compilation
-snapshot and a newly prepared runtime representation.
+The object relationships behind this conversion are covered in
+:doc:`simulation_compilation`. Contributors adding a new representation should
+follow :doc:`../extending/extending_the_object_model` and
+:doc:`../extending/writing_numba_compatible_transport_code`.
 
 CPU and GPU Share a Deliberate Subset
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Numba-CPU supports some operations that are unavailable or unsuitable inside a
-GPU device function. Code shared by the two targets must use explicit numeric
-types, supported NumPy operations, predictable control flow, and preallocated
-state. Host callbacks, Python objects, and Numba ``objmode`` blocks—which
-temporarily return compiled CPU code to the Python interpreter—must remain
-outside GPU transport paths.
+Some operations accepted by Numba-CPU are unavailable or unsuitable in GPU
+device code. Transport shared by both targets therefore uses a common set of
+numerical operations and predictable control flow. Hardware-specific memory,
+synchronization, and scheduling behavior is isolated where the targets truly
+differ.
 
-MC/DC may use target-specific modules when execution, memory, atomics, or
-scheduling genuinely differs. The common transport path should remain the
-default so that backend implementations do not drift apart.
+Read :doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution` for the
+two compiled backends. Practical compatibility rules belong in
+:doc:`../extending/writing_numba_compatible_transport_code`.
 
 Design Tradeoffs
 ----------------
@@ -254,28 +249,34 @@ cost until a method has demonstrated enough value to justify integration.
 An unrestricted Python prototype maximizes scientific expressiveness and
 minimizes the effort required to test an idea. The tradeoff is that parts of
 the prototype may need to be redesigned or rewritten for Numba-CPU. Beginning
-with MC/DC's packed runtime representation and Numba-compatible operations can
-reduce that porting effort, but introduces implementation constraints earlier
-in the research process.
+with simple numerical data and operations that Numba supports can reduce that
+porting effort, but introduces implementation constraints earlier in the
+research process. See
+:doc:`../extending/writing_numba_compatible_transport_code` for the practical
+constraints.
 
 Once integrated, the shared execution architecture introduces additional
 costs:
 
-- Runtime-visible state must be declared and packed before execution.
-- Dynamic Python behavior must be removed from compiled transport paths.
-- New model concepts may require coordinated changes to objects, layouts,
-  accessors, transport functions, and tests.
+- Information needed during transport must be prepared before execution.
+- Dynamic Python behavior cannot remain inside accelerated transport code.
+- A new model concept may require coordinated changes to the user interface,
+  preparation steps, transport algorithms, and tests.
 - Supporting Python, Numba-CPU, and Numba-GPU increases validation work.
 - Just-in-time compilation adds startup time and compiler-specific failure
   modes.
-- GPU execution may require additional memory management, code generation,
-  atomics, and scheduling support.
+- GPU execution may require additional work for data movement, synchronized
+  updates, and particle scheduling.
 
 MC/DC accepts possible prototype rework so that early methods development
 remains unconstrained. It accepts the stricter integrated architecture so that
 maintained features can share transport logic across execution backends rather
 than becoming separate Python, CPU, and GPU implementations.
 
+The preparation costs are detailed in :doc:`simulation_compilation` and
+:doc:`runtime_data_layout`. The backend-specific costs are detailed in
+:doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`.
+
 Related Design Choices
 ----------------------
 
@@ -295,10 +296,11 @@ accelerator data movement difficult to control.
 MC/DC instead uses staged convergence. A prototype may begin anywhere on the
 spectrum from an ad hoc Python experiment to a nearly Numba-compatible
 implementation. When the method needs compiled performance or becomes a
-maintained MC/DC capability, it converges on the shared typed transport path.
-The generated structured and flat runtime representation provides that common
-execution boundary without dictating how the original prototype must be
-written.
+maintained MC/DC capability, it converges on common numerical data and
+transport interfaces. This provides a shared execution path without dictating
+how the original prototype must be written. The data boundary is described in
+:doc:`runtime_data_layout`; contributor guidance is provided in
+:doc:`../extending/writing_numba_compatible_transport_code`.
 
 These are design-space comparisons, not a claim that every alternative was
 implemented and benchmarked by the project.
@@ -315,21 +317,20 @@ Potential improvements fall into three areas:
 - **Prototype access** -- optionally make the active Python model and arbitrary
   prototype state easier to reach during Python execution without requiring a
   formal prototype framework.
-- **Integration assistance** -- improve inspection and conversion of model
-  state, generated layouts and accessors, and diagnostics that identify
-  compiler-incompatible code.
-- **Execution infrastructure** -- evolve where compilation state is stored,
-  when generated runtime layers are created and refreshed, how Numba typed
-  containers are used, and the boundary between shared and backend-specific
-  transport.
+- **Integration assistance** -- provide better tools for inspecting a Python
+  model, preparing its numerical data, and identifying code that an
+  accelerated backend cannot run.
+- **Execution infrastructure** -- make the creation and ownership of prepared
+  data clearer, and keep hardware-specific behavior separated from the common
+  transport algorithms.
 
 Future changes should preserve the ability to stop at any development stage,
 keep the transition into maintained execution state explicit and reviewable,
 and retain equivalent physical behavior across the supported backends of an
 integrated feature.
 
-For the mechanisms behind this boundary, see :doc:`simulation_compilation` and
-:doc:`runtime_data_layout`. If following the main Architecture path, return to
-the Numba-CPU section of :doc:`python_numba_cpu_execution`, then continue with
-:doc:`numba_gpu_execution`. When implementing a transport change, use
+For the preparation process, see :doc:`simulation_compilation` and
+:doc:`runtime_data_layout`. For execution, continue with
+:doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`. When
+implementing a transport change, use
 :doc:`../extending/writing_numba_compatible_transport_code`.

From adef1f4f07399718e24888e5799f8ee2f0322539 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 31 Jul 2026 18:14:54 +0700
Subject: [PATCH 070/202] make python mode discussion consistent

---
 .../python_first_numba_accelerated_design.rst | 191 +++++++++---------
 .../python_numba_cpu_execution.rst            |  34 ++--
 ...riting_numba_compatible_transport_code.rst |  27 +--
 3 files changed, 125 insertions(+), 127 deletions(-)

diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
index 2c1a42d27..5114365ef 100644
--- a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -6,10 +6,11 @@ Python-First, Numba-Accelerated Design
 
 MC/DC is a Python-based environment for developing Monte Carlo transport
 methods, but large calculations also require compiled performance.
-*Python-first* means that developers can build and validate a method with the
-full Python language and ecosystem before addressing the requirements of
-accelerated execution. Numba provides the bridge between these goals—but what
-is Numba, and why is it a good fit for MC/DC?
+*Python-first* means that developers can build and validate a method through
+MC/DC's normal Python execution while using the full Python language and
+ecosystem. They can address the requirements of accelerated execution later.
+Numba provides the bridge between these goals—but what is Numba, and why is it
+a good fit for MC/DC?
 
 What Is Numba?
 --------------
@@ -24,12 +25,13 @@ than in a separate build step.
 Numba does not compile the entire Python language. Efficient compilation
 requires numerical types, predictable control flow, and supported operations.
 Arbitrary Python objects, dynamic behavior, and calls into unsupported
-packages remain useful during prototyping but must be removed, replaced, or
-moved outside compiled functions.
+packages remain useful while prototyping in MC/DC Python. They must be removed,
+replaced, or moved outside compiled functions before the method can use an
+accelerated backend.
 
 MC/DC uses Numba as the bridge between Python development and accelerated
 transport. Its common transport path supports three *execution backends*, or
-environments that run the integrated functions:
+environments that run the transport functions:
 
 - **Python** executes the functions through the interpreter with JIT
   compilation disabled.
@@ -46,8 +48,8 @@ supports several project goals:
 
 - New transport methods can begin in the language and scientific ecosystem
   already used to construct MC/DC models.
-- The integrated Python backend provides ordinary Python tracebacks while
-  exercising the same transport functions and data flow used by acceleration.
+- The Python backend provides ordinary Python tracebacks while exercising the
+  same MC/DC model lifecycle used by acceleration.
 - Numba-CPU accelerates those functions without requiring a separate
   implementation in C, C++, or Fortran.
 - The typed transport interfaces provide a common foundation for CPU and GPU
@@ -60,26 +62,31 @@ the remainder of this page.
 Staged Methods Development
 --------------------------
 
-Pure-Python Prototype
-^^^^^^^^^^^^^^^^^^^^^
-
-A method may begin as a pure-Python prototype, either independently or through
-direct modifications to MC/DC. At this stage, the priority is to establish the
-method's correctness, understand its behavior, and test it on problems small
-enough that compiled performance is unnecessary.
+MC/DC Python: Prototyping and Validation
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-The prototype may use arbitrary Python objects, module-level global state,
-manual imports, dynamic dispatch, callbacks, hard-coded assumptions, or direct
-edits to transport routines. It may call packages such as SciPy or Matplotlib
-during transport, perform file I/O, or visualize intermediate state. These
-choices are acceptable because the prototype prioritizes scientific
-expressiveness and rapid validation over performance, encapsulation,
-dependency discipline, and compiler compatibility.
+A new method can be developed through MC/DC's Python backend. It still follows
+the normal MC/DC path: the user defines a valid model, MC/DC prepares the
+complete model and its numerical execution data, and transport runs through
+the Python interpreter with JIT compilation disabled. The preparation process
+is described in :doc:`simulation_compilation` and
+:doc:`runtime_data_layout`.
 
-No prototype framework or service is required. Researchers may use the most
-direct implementation that answers the question being studied. Prototype-only
-packages do not need to become MC/DC dependencies, and the prototype is not
-expected to remain in its original form.
+Within those minimum requirements, prototype transport code may use arbitrary
+Python objects, module-level global state, manual imports, dynamic dispatch,
+callbacks, hard-coded assumptions, or direct edits to transport routines. It
+may call packages such as SciPy or Matplotlib during transport, perform file
+I/O, or visualize intermediate state. It may also reach beyond MC/DC's prepared
+transport data through ordinary Python mechanisms. These choices are
+acceptable because this stage prioritizes scientific expressiveness and rapid
+validation over performance, encapsulation, dependency discipline, and
+compiler compatibility.
+
+No special prototype framework or service is required. Researchers may use
+the most direct implementation within MC/DC Python that answers the question
+being studied. Prototype-only packages do not need to become MC/DC
+dependencies, and temporary implementation choices are not expected to remain
+in their original form.
 
 This freedom is permission, not a required style. A developer familiar with
 MC/DC and Numba may voluntarily begin with simple numerical data and
@@ -88,30 +95,15 @@ substantially reduce later porting work without turning Python-first
 development into a compiler-first requirement. Practical guidance is provided
 in :doc:`../extending/writing_numba_compatible_transport_code`.
 
-MC/DC Integration and Python Execution
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Integration begins when the method adopts MC/DC's standard execution path.
-MC/DC first gathers the complete user-defined model into a consistent snapshot
-for one simulation. This process is called *model compilation* and is distinct
-from Numba JIT compilation. See :doc:`simulation_compilation` for model
-ownership, discovery, and finalization.
-
-MC/DC then converts that snapshot into compact numerical execution data shared
-by all backends. Python mode runs the integrated transport functions against
-this data with JIT compilation disabled, providing ordinary Python tracebacks
-while exercising the same data flow used by acceleration. The conversion is
-described in :doc:`runtime_data_layout`.
-
 Numba-CPU Compilation
 ^^^^^^^^^^^^^^^^^^^^^
 
 Once the method is verified and larger calculations require more performance,
-Numba JIT compilation can be enabled for the CPU. Unless the prototype was
-already written against the compatible subset, reaching this stage requires
-deliberate porting rather than simply changing an execution option. Python
-features that Numba cannot compile are replaced with supported numerical forms
-and predictable control flow. See :doc:`python_numba_cpu_execution` for the
+it can be adapted for Numba-CPU. Unless the Python implementation was already
+written against the compatible subset, reaching this stage requires deliberate
+porting rather than simply changing an execution option. Python features that
+Numba cannot compile are replaced with supported numerical forms and
+predictable control flow. See :doc:`python_numba_cpu_execution` for the
 execution path and
 :doc:`../extending/writing_numba_compatible_transport_code` for coding
 guidance.
@@ -131,10 +123,8 @@ Valid Stopping Points
 
 Each stage can be a useful endpoint:
 
-- **Pure-Python prototype** is sufficient for exploring a method and answering
-  a focused research question.
-- **MC/DC Python** is sufficient for integrated debugging and small
-  calculations.
+- **MC/DC Python** is sufficient for prototyping, debugging, and small
+  calculations. Prototype code may use unrestricted Python where needed.
 - **Numba-CPU** is sufficient when compiled CPU performance meets the
   calculation's needs.
 - **Numba-GPU** provides the final portability stage when accelerator
@@ -149,8 +139,9 @@ limitation.
 The Standard Execution Path
 ---------------------------
 
-After prototyping, MC/DC's standard path separates flexible model construction
-from constrained transport execution:
+Every backend follows MC/DC's standard model and execution path. What changes
+between development stages is how transport runs and which Python features it
+may use:
 
 .. list-table::
    :header-rows: 1
@@ -177,8 +168,9 @@ from constrained transport execution:
 
 Model construction and preparation may use object-oriented interfaces,
 variable-length collections, validation, and other expressive Python features.
-The boundary occurs at integrated transport, where compilation targets require
-predictable numerical data and explicit behavior. See
+Transport in the Python backend may also use ordinary Python facilities beyond
+the prepared execution data. The accelerated backends require predictable
+numerical data and explicit behavior. See
 :doc:`simulation_compilation` and :doc:`runtime_data_layout` for the two
 preparation stages, then :doc:`python_numba_cpu_execution` and
 :doc:`numba_gpu_execution` for backend execution.
@@ -186,18 +178,19 @@ preparation stages, then :doc:`python_numba_cpu_execution` and
 Architectural Consequences
 --------------------------
 
-Once a method enters the integrated path, Numba shapes the boundary between
-MC/DC's model and execution layers. The following requirements do not constrain
-the initial prototype, but they are fundamental to maintained transport code.
+All MC/DC backends follow the standard model and execution path. Preparing a
+method for acceleration narrows the freedom available inside transport. A
+prototype in MC/DC Python may temporarily work around the following
+requirements, but portable, maintained transport code must satisfy them.
 
 Model Description Becomes Execution Data
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 Python objects are well suited for describing materials, geometry, sources,
-tallies, and their relationships. Compiled transport instead needs numerical
-data with predictable types and connections. MC/DC therefore turns the
-complete Python model into a simulation-specific numerical representation
-before execution.
+tallies, and their relationships. MC/DC turns this model into a
+simulation-specific numerical representation before every execution. A
+prototype in MC/DC Python may also access other Python state, but accelerated
+transport needs data with predictable types and connections.
 
 The ownership and finalization of the Python model are explained in
 :doc:`simulation_compilation`. Its numerical representation is explained in
@@ -244,21 +237,23 @@ Design Tradeoffs
 ----------------
 
 The staged approach does not eliminate development cost; it defers some of that
-cost until a method has demonstrated enough value to justify integration.
+cost until a method has demonstrated enough value to justify acceleration and
+long-term maintenance.
 
-An unrestricted Python prototype maximizes scientific expressiveness and
+Prototyping through MC/DC Python maximizes scientific expressiveness and
 minimizes the effort required to test an idea. The tradeoff is that parts of
-the prototype may need to be redesigned or rewritten for Numba-CPU. Beginning
-with simple numerical data and operations that Numba supports can reduce that
-porting effort, but introduces implementation constraints earlier in the
-research process. See
+the Python implementation may need to be redesigned or rewritten for
+Numba-CPU. Beginning with simple numerical data and operations that Numba
+supports can reduce that porting effort, but introduces implementation
+constraints earlier in the research process. See
 :doc:`../extending/writing_numba_compatible_transport_code` for the practical
 constraints.
 
-Once integrated, the shared execution architecture introduces additional
-costs:
+Making the method portable across the accelerated backends introduces
+additional costs:
 
-- Information needed during transport must be prepared before execution.
+- Information used by accelerated transport must be expressible in the
+  prepared execution data.
 - Dynamic Python behavior cannot remain inside accelerated transport code.
 - A new model concept may require coordinated changes to the user interface,
   preparation steps, transport algorithms, and tests.
@@ -268,10 +263,10 @@ costs:
 - GPU execution may require additional work for data movement, synchronized
   updates, and particle scheduling.
 
-MC/DC accepts possible prototype rework so that early methods development
-remains unconstrained. It accepts the stricter integrated architecture so that
-maintained features can share transport logic across execution backends rather
-than becoming separate Python, CPU, and GPU implementations.
+MC/DC accepts possible porting work so that early methods development in
+Python remains unconstrained. It accepts stricter requirements for accelerated
+execution so that maintained features can share transport logic across
+backends rather than becoming separate Python, CPU, and GPU implementations.
 
 The preparation costs are detailed in :doc:`simulation_compilation` and
 :doc:`runtime_data_layout`. The backend-specific costs are detailed in
@@ -281,25 +276,26 @@ Related Design Choices
 ----------------------
 
 Alternative designs place the boundary between expressiveness and portability
-elsewhere. Requiring every prototype to follow the Numba-compatible subset
-would reduce later porting, but constrain exploration before the method's value
-is known. Maintaining a complete Python solver alongside separate optimized
-backends would preserve Python freedom indefinitely, but duplicate transport
-logic and allow implementations to drift.
+elsewhere. Requiring all transport development to follow the Numba-compatible
+subset from the beginning would reduce later porting, but constrain
+exploration before the method's value is known. Maintaining a complete Python
+solver alongside separate optimized backends would preserve Python freedom
+indefinitely, but duplicate transport logic and allow implementations to
+drift.
 
 Handwritten C, C++, or Fortran kernels would provide direct low-level control,
 but split methods development across languages and introduce a binding
 boundary. Passing rich Python objects directly to every execution backend
-would preserve the prototype representation, but make typing, ownership, and
+would preserve Python-mode flexibility, but make typing, ownership, and
 accelerator data movement difficult to control.
 
-MC/DC instead uses staged convergence. A prototype may begin anywhere on the
-spectrum from an ad hoc Python experiment to a nearly Numba-compatible
-implementation. When the method needs compiled performance or becomes a
-maintained MC/DC capability, it converges on common numerical data and
-transport interfaces. This provides a shared execution path without dictating
-how the original prototype must be written. The data boundary is described in
-:doc:`runtime_data_layout`; contributor guidance is provided in
+MC/DC instead uses staged convergence within its standard execution path. A
+method in MC/DC Python may range from an ad hoc implementation to one that is
+already nearly Numba-compatible. When the method needs compiled performance or
+becomes a maintained MC/DC capability, it converges on common numerical data
+and transport interfaces. This preserves a shared execution path without
+dictating how the Python implementation must begin. The data boundary is
+described in :doc:`runtime_data_layout`; contributor guidance is provided in
 :doc:`../extending/writing_numba_compatible_transport_code`.
 
 These are design-space comparisons, not a claim that every alternative was
@@ -310,24 +306,23 @@ Future Evolution
 
 The Python-first principle does not require the present implementation to
 remain fixed. Future work should make movement between stages easier without
-narrowing the freedom of pure-Python exploration.
+narrowing the freedom of prototyping in MC/DC Python.
 
 Potential improvements fall into three areas:
 
-- **Prototype access** -- optionally make the active Python model and arbitrary
-  prototype state easier to reach during Python execution without requiring a
-  formal prototype framework.
-- **Integration assistance** -- provide better tools for inspecting a Python
-  model, preparing its numerical data, and identifying code that an
-  accelerated backend cannot run.
+- **Python-mode flexibility** -- make the active Python model and arbitrary
+  development state easier to reach during Python execution without requiring
+  a formal prototype framework.
+- **Porting assistance** -- provide better tools for inspecting a Python
+  implementation and identifying code that an accelerated backend cannot run.
 - **Execution infrastructure** -- make the creation and ownership of prepared
   data clearer, and keep hardware-specific behavior separated from the common
   transport algorithms.
 
 Future changes should preserve the ability to stop at any development stage,
-keep the transition into maintained execution state explicit and reviewable,
-and retain equivalent physical behavior across the supported backends of an
-integrated feature.
+keep the transition from an MC/DC-Python-only implementation to a portable
+maintained implementation explicit and reviewable, and retain equivalent
+physical behavior across the supported backends of a maintained feature.
 
 For the preparation process, see :doc:`simulation_compilation` and
 :doc:`runtime_data_layout`. For execution, continue with
diff --git a/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst b/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
index 0faf6393b..19326fbb3 100644
--- a/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
+++ b/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
@@ -51,7 +51,7 @@ and packed runtime inputs used by accelerated execution.
 
 Python mode is best for:
 
-- Developing and inspecting transport logic.
+- Prototyping, developing, and inspecting transport logic.
 - Checking model construction and object compilation.
 - Obtaining ordinary Python tracebacks.
 - Running small smoke tests before enabling acceleration.
@@ -59,28 +59,28 @@ Python mode is best for:
 Python mode does not bypass simulation compilation or runtime packing. It
 bypasses machine-code generation for the CPU transport functions.
 
-Exploratory Python Prototypes
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Python Prototyping
+^^^^^^^^^^^^^^^^^^
 
-The description above is the standard MC/DC Python execution path. During
-initial methods development, researchers may temporarily depart from it in a
-standalone prototype or a locally modified MC/DC checkout. Prototype transport
-may access arbitrary Python objects or global state, import external packages,
-perform I/O or visualization, and use hard-coded or dynamic behavior.
+The standard MC/DC Python execution path is also the environment for initial
+methods development. A prototype remains a complete MC/DC calculation and
+does not bypass model compilation, runtime preparation, or transport. Because
+JIT compilation is disabled, its transport code may temporarily access
+arbitrary Python objects or global state, import external packages, perform I/O
+or visualization, and use hard-coded or dynamic behavior.
 
-Such code is intentionally outside the common execution architecture and is
-not expected to compile with Numba unchanged. Advancing the method to
-Numba-CPU requires porting it back to the packed runtime representation and
-compiler-compatible interfaces.
+These freedoms do not form a separate execution architecture. Advancing the
+method to Numba-CPU requires adapting the parts used by accelerated transport
+to the packed runtime representation and compiler-compatible interfaces.
 
 Before Numba Acceleration
 -------------------------
 
-At this transition, :doc:`python_first_numba_accelerated_design` becomes the
-main conceptual guide. It explains why MC/DC converts its flexible Python
-model into typed runtime data, which parts remain shared across execution
-backends, and which constraints follow from supporting Numba-CPU and
-Numba-GPU.
+At the transition from an MC/DC-Python-only method to Numba acceleration,
+:doc:`python_first_numba_accelerated_design` is the main conceptual guide. It
+explains why MC/DC converts its flexible Python model into typed runtime data,
+which parts remain shared across execution backends, and which constraints
+follow from supporting Numba-CPU and Numba-GPU.
 
 If you have not already read that design page as an overview, read it before
 continuing when developing MC/DC or studying its acceleration architecture.
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index a8056126b..3c3127f8a 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -4,18 +4,19 @@
 Writing Numba-Compatible Transport Code
 =======================================
 
-Integrated transport code in MC/DC is written in Python but may execute as
+Maintained transport code in MC/DC is written in Python but may execute as
 Python, Numba-compiled CPU code, or Numba-compiled GPU device code. A method may
-begin as a disposable pure-Python prototype before being ported into this
-shared execution path.
+be prototyped within the MC/DC Python backend before it is adapted for the two
+accelerated backends.
 
 Read :doc:`../architecture/python_first_numba_accelerated_design` first for the
 reason behind this development model. If the change introduces new model
 state, also read :doc:`extending_the_object_model` and
 :doc:`../architecture/runtime_data_layout`.
 
-The rules below apply when a prototype is being integrated and maintained as
-part of MC/DC. They are not restrictions on initial pure-Python exploration.
+The rules below apply when an MC/DC Python prototype is being made portable and
+maintained as part of MC/DC. They are not restrictions on temporary
+Python-only behavior during initial exploration.
 
 Choose the Host or Transport Layer
 ----------------------------------
@@ -42,9 +43,10 @@ inside a frequently called kernel.
 Work Python First
 -----------------
 
-An exploratory method may begin as unrestricted pure Python, using whichever
-data structures make the algorithm easiest to understand and verify. This
-prototype is a valid stopping point for a small study that does not need
+An exploratory method may begin in MC/DC Python, using whichever Python data
+structures make the algorithm easiest to understand and verify. It still runs
+through MC/DC's normal model preparation and transport path. This Python-only
+implementation is a valid stopping point for a small study that does not need
 compiled performance.
 
 At this stage, use module-level global state, arbitrary Python objects, ad hoc
@@ -63,10 +65,11 @@ operations, producing an implementation that is nearly Numba-compatible from
 the start. This can minimize the deliberate porting work while preserving the
 freedom to use ordinary Python whenever it helps establish the method.
 
-Integration into MC/DC begins by adapting the verified method to the packed
-runtime inputs used by transport. Decorate the integrated function with
-``@njit`` like the surrounding transport functions; in Python mode, MC/DC
-disables JIT compilation and calls the same function as Python.
+Porting for accelerated execution begins by adapting the verified method so
+that the required information and behavior use the packed runtime inputs
+available to transport. Decorate the maintained function with ``@njit`` like
+the surrounding transport functions; in Python mode, MC/DC disables JIT
+compilation and calls the same function as Python.
 
 .. code-block:: python
 

From 59b06170f757bf7ac527ceeef05ccdd6d1d5a6f4 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 31 Jul 2026 18:55:23 +0700
Subject: [PATCH 071/202] finalize numba page

---
 .../python_first_numba_accelerated_design.rst | 189 ++++++------------
 1 file changed, 60 insertions(+), 129 deletions(-)

diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
index 5114365ef..518b61fc5 100644
--- a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -16,18 +16,14 @@ What Is Numba?
 --------------
 
 `Numba <https://numba.readthedocs.io/en/stable/user/5minguide.html>`_ is a
-just-in-time (JIT) compiler for numerical Python. When a function marked with a
-Numba decorator such as ``@njit`` is called, Numba examines the argument types
-and translates supported Python, NumPy, and loop operations into machine code
-specialized for those types. Compilation happens as the program runs rather
-than in a separate build step.
-
-Numba does not compile the entire Python language. Efficient compilation
-requires numerical types, predictable control flow, and supported operations.
-Arbitrary Python objects, dynamic behavior, and calls into unsupported
-packages remain useful while prototyping in MC/DC Python. They must be removed,
-replaced, or moved outside compiled functions before the method can use an
-accelerated backend.
+just-in-time (JIT) compiler for numerical Python. It translates compatible
+Python functions into machine code as a calculation runs, allowing MC/DC to
+accelerate Python transport algorithms without maintaining a second
+implementation in a lower-level language.
+
+Numba does not support every feature of Python. A prototype in MC/DC Python may
+use the full Python language and ecosystem, but an accelerated implementation
+must express the relevant data and behavior in forms that Numba can compile.
 
 MC/DC uses Numba as the bridge between Python development and accelerated
 transport. Its common transport path supports three *execution backends*, or
@@ -36,8 +32,8 @@ environments that run the transport functions:
 - **Python** executes the functions through the interpreter with JIT
   compilation disabled.
 - **Numba-CPU** compiles the functions into machine code for the host CPU.
-- **Numba-GPU** compiles device functions for an accelerator, while a
-  supporting runtime called Harmonize schedules particle work.
+- **Numba-GPU** compiles functions for an accelerator, with Harmonize providing
+  the supporting GPU runtime.
 
 Why MC/DC Uses Numba
 --------------------
@@ -48,11 +44,11 @@ supports several project goals:
 
 - New transport methods can begin in the language and scientific ecosystem
   already used to construct MC/DC models.
-- The Python backend provides ordinary Python tracebacks while exercising the
-  same MC/DC model lifecycle used by acceleration.
+- The Python backend supports unrestricted methods development and ordinary
+  Python debugging within MC/DC's normal model lifecycle.
 - Numba-CPU accelerates those functions without requiring a separate
   implementation in C, C++, or Fortran.
-- The typed transport interfaces provide a common foundation for CPU and GPU
+- Common transport interfaces provide a shared foundation for CPU and GPU
   execution, with backend-specific adaptation where the hardware requires it.
 
 The choice therefore preserves an expressive starting point while providing a
@@ -89,11 +85,10 @@ dependencies, and temporary implementation choices are not expected to remain
 in their original form.
 
 This freedom is permission, not a required style. A developer familiar with
-MC/DC and Numba may voluntarily begin with simple numerical data and
-predictable operations that are already close to the compiled form. This can
-substantially reduce later porting work without turning Python-first
-development into a compiler-first requirement. Practical guidance is provided
-in :doc:`../extending/writing_numba_compatible_transport_code`.
+MC/DC and Numba may begin with an implementation already close to the compiled
+form, reducing later porting work without making compiler compatibility a
+requirement for initial exploration. Practical guidance is provided in
+:doc:`../extending/writing_numba_compatible_transport_code`.
 
 Numba-CPU Compilation
 ^^^^^^^^^^^^^^^^^^^^^
@@ -101,21 +96,17 @@ Numba-CPU Compilation
 Once the method is verified and larger calculations require more performance,
 it can be adapted for Numba-CPU. Unless the Python implementation was already
 written against the compatible subset, reaching this stage requires deliberate
-porting rather than simply changing an execution option. Python features that
-Numba cannot compile are replaced with supported numerical forms and
-predictable control flow. See :doc:`python_numba_cpu_execution` for the
-execution path and
-:doc:`../extending/writing_numba_compatible_transport_code` for coding
-guidance.
+porting rather than simply changing an execution option. See
+:doc:`python_numba_cpu_execution` for the execution path and
+:doc:`../extending/writing_numba_compatible_transport_code` for the practical
+porting requirements.
 
 Numba-GPU Compilation
 ^^^^^^^^^^^^^^^^^^^^^
 
-GPU execution is a further stage. Device code typically imposes additional
-constraints on how data is stored and moved, how the GPU interacts with the
-host CPU, and how concurrent particle work is coordinated. Some code that
-works with Numba-CPU therefore requires further adaptation before it can
-execute on a GPU. These additional layers are described in
+GPU execution is a further stage with additional hardware constraints. Some
+code that works with Numba-CPU therefore requires further adaptation before it
+can execute on a GPU. These additional layers are described in
 :doc:`numba_gpu_execution`.
 
 Valid Stopping Points
@@ -178,60 +169,24 @@ preparation stages, then :doc:`python_numba_cpu_execution` and
 Architectural Consequences
 --------------------------
 
-All MC/DC backends follow the standard model and execution path. Preparing a
-method for acceleration narrows the freedom available inside transport. A
-prototype in MC/DC Python may temporarily work around the following
-requirements, but portable, maintained transport code must satisfy them.
-
-Model Description Becomes Execution Data
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Python objects are well suited for describing materials, geometry, sources,
-tallies, and their relationships. MC/DC turns this model into a
-simulation-specific numerical representation before every execution. A
-prototype in MC/DC Python may also access other Python state, but accelerated
-transport needs data with predictable types and connections.
+Preparing a method for acceleration narrows the freedom available inside
+transport and has three broad architectural consequences.
 
-The ownership and finalization of the Python model are explained in
-:doc:`simulation_compilation`. Its numerical representation is explained in
-:doc:`runtime_data_layout`.
-
-The Execution Structure Is Fixed Before Transport
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Preparation determines which model entities and data arrays exist for a run.
-Transport can update particle state, scores, banks, and counters, but it does
-not add new model entities or resize the model structure. Changing the model
-requires preparing a new execution snapshot.
+**Flexible models become predictable execution data.** Python objects remain
+the natural way to describe a problem, but accelerated transport operates on a
+numerical representation prepared for one simulation. The transformation is
+covered in :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
 
-See :doc:`simulation_compilation` for the snapshot lifecycle and
-:doc:`runtime_data_layout` for what transport may read and update.
+**Transport behavior becomes explicit.** Dynamic Python techniques that are
+useful during prototyping must be expressed in forms the compiler can
+understand when the method is accelerated. Contributor guidance belongs in
+:doc:`../extending/writing_numba_compatible_transport_code` and
+:doc:`../extending/extending_the_object_model`.
 
-Dynamic Choices Become Explicit
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Ordinary Python can choose behavior dynamically from object types and methods.
-Compiled transport makes those choices visible through numerical tags,
-explicit branches, and stable function interfaces. This allows Numba to see
-the possible execution paths before generating machine code.
-
-The object relationships behind this conversion are covered in
-:doc:`simulation_compilation`. Contributors adding a new representation should
-follow :doc:`../extending/extending_the_object_model` and
-:doc:`../extending/writing_numba_compatible_transport_code`.
-
-CPU and GPU Share a Deliberate Subset
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Some operations accepted by Numba-CPU are unavailable or unsuitable in GPU
-device code. Transport shared by both targets therefore uses a common set of
-numerical operations and predictable control flow. Hardware-specific memory,
-synchronization, and scheduling behavior is isolated where the targets truly
-differ.
-
-Read :doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution` for the
-two compiled backends. Practical compatibility rules belong in
-:doc:`../extending/writing_numba_compatible_transport_code`.
+**CPU and GPU share a portable core.** Common transport algorithms use behavior
+supported by both accelerated targets, while hardware-specific concerns remain
+isolated. The two execution paths are described in
+:doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`.
 
 Design Tradeoffs
 ----------------
@@ -245,49 +200,25 @@ minimizes the effort required to test an idea. The tradeoff is that parts of
 the Python implementation may need to be redesigned or rewritten for
 Numba-CPU. Beginning with simple numerical data and operations that Numba
 supports can reduce that porting effort, but introduces implementation
-constraints earlier in the research process. See
-:doc:`../extending/writing_numba_compatible_transport_code` for the practical
-constraints.
-
-Making the method portable across the accelerated backends introduces
-additional costs:
-
-- Information used by accelerated transport must be expressible in the
-  prepared execution data.
-- Dynamic Python behavior cannot remain inside accelerated transport code.
-- A new model concept may require coordinated changes to the user interface,
-  preparation steps, transport algorithms, and tests.
-- Supporting Python, Numba-CPU, and Numba-GPU increases validation work.
-- Just-in-time compilation adds startup time and compiler-specific failure
-  modes.
-- GPU execution may require additional work for data movement, synchronized
-  updates, and particle scheduling.
-
-MC/DC accepts possible porting work so that early methods development in
-Python remains unconstrained. It accepts stricter requirements for accelerated
-execution so that maintained features can share transport logic across
-backends rather than becoming separate Python, CPU, and GPU implementations.
-
-The preparation costs are detailed in :doc:`simulation_compilation` and
-:doc:`runtime_data_layout`. The backend-specific costs are detailed in
-:doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`.
+constraints earlier in the research process.
+
+Portability also increases compiler, backend, and validation work. MC/DC
+accepts these costs so that maintained features can share transport logic
+across Python, CPU, and GPU execution rather than becoming separate
+implementations that may drift apart. Practical constraints are covered in
+:doc:`../extending/writing_numba_compatible_transport_code`; backend-specific
+costs are covered in :doc:`python_numba_cpu_execution` and
+:doc:`numba_gpu_execution`.
 
 Related Design Choices
 ----------------------
 
 Alternative designs place the boundary between expressiveness and portability
-elsewhere. Requiring all transport development to follow the Numba-compatible
-subset from the beginning would reduce later porting, but constrain
-exploration before the method's value is known. Maintaining a complete Python
-solver alongside separate optimized backends would preserve Python freedom
-indefinitely, but duplicate transport logic and allow implementations to
-drift.
-
-Handwritten C, C++, or Fortran kernels would provide direct low-level control,
-but split methods development across languages and introduce a binding
-boundary. Passing rich Python objects directly to every execution backend
-would preserve Python-mode flexibility, but make typing, ownership, and
-accelerator data movement difficult to control.
+elsewhere. Requiring Numba compatibility from the beginning would reduce later
+porting but constrain early exploration. Maintaining separate Python and
+optimized solvers would preserve unrestricted Python behavior but duplicate
+transport logic. Handwritten kernels would provide more low-level control but
+split methods development across languages.
 
 MC/DC instead uses staged convergence within its standard execution path. A
 method in MC/DC Python may range from an ad hoc implementation to one that is
@@ -298,9 +229,6 @@ dictating how the Python implementation must begin. The data boundary is
 described in :doc:`runtime_data_layout`; contributor guidance is provided in
 :doc:`../extending/writing_numba_compatible_transport_code`.
 
-These are design-space comparisons, not a claim that every alternative was
-implemented and benchmarked by the project.
-
 Future Evolution
 ----------------
 
@@ -324,8 +252,11 @@ keep the transition from an MC/DC-Python-only implementation to a portable
 maintained implementation explicit and reviewable, and retain equivalent
 physical behavior across the supported backends of a maintained feature.
 
-For the preparation process, see :doc:`simulation_compilation` and
-:doc:`runtime_data_layout`. For execution, continue with
-:doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`. When
-implementing a transport change, use
+Where to Go Next
+----------------
+
+For model preparation, continue with :doc:`simulation_compilation` and
+:doc:`runtime_data_layout`. For execution, read
+:doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`. Contributors
+implementing a transport change should use
 :doc:`../extending/writing_numba_compatible_transport_code`.

From 6ebfe54e2f40dde2d057260b48227d90897f100a Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 31 Jul 2026 19:20:42 +0700
Subject: [PATCH 072/202] remove unnecessary image

---
 .../architecture/simulation_compilation.rst   |  4 -
 .../architecture/object_graph_compilation.svg | 86 -------------------
 2 files changed, 90 deletions(-)
 delete mode 100644 docs/source/images/developer_guide/architecture/object_graph_compilation.svg

diff --git a/docs/source/developer_guide/architecture/simulation_compilation.rst b/docs/source/developer_guide/architecture/simulation_compilation.rst
index 4225c89c3..26408d1fd 100644
--- a/docs/source/developer_guide/architecture/simulation_compilation.rst
+++ b/docs/source/developer_guide/architecture/simulation_compilation.rst
@@ -221,10 +221,6 @@ The common lifecycle defined by the object hierarchy makes this traversal
 uniform: embedded ``MCDCBase`` members are visited in place, while
 ``MCDCObject`` members are registered before their descendants are explored.
 
-.. image:: ../../images/developer_guide/architecture/object_graph_compilation.svg
-   :width: 100%
-   :alt: Shared Python model objects discovered recursively from simulation roots and registered once in simulation-local collections.
-
 Discovery follows actual Python references. For example, a root cell reaches
 its region, the region reaches its surfaces, and the cell's fill reaches its
 material or child universe. Users therefore attach root cells rather than
diff --git a/docs/source/images/developer_guide/architecture/object_graph_compilation.svg b/docs/source/images/developer_guide/architecture/object_graph_compilation.svg
deleted file mode 100644
index 6a4b027e5..000000000
--- a/docs/source/images/developer_guide/architecture/object_graph_compilation.svg
+++ /dev/null
@@ -1,86 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="650" viewBox="0 0 1200 650" role="img" aria-labelledby="title desc">
-  <title id="title">Simulation object graph compilation</title>
-  <desc id="desc">A Simulation owns root cells, sources, tallies, settings, and techniques. Recursive traversal discovers shared model objects, uses compile IDs to register each once, and creates simulation-local collections and IDs.</desc>
-  <defs>
-    <marker id="arrow" markerWidth="10" markerHeight="10" refX="8" refY="3" orient="auto">
-      <path d="M0,0 L0,6 L9,3 z" fill="#566573"/>
-    </marker>
-    <style>
-      .title { font-family: system-ui, sans-serif; font-size: 23px; font-weight: 700; fill: #17202a; }
-      .label { font-family: system-ui, sans-serif; font-size: 17px; font-weight: 650; fill: #17202a; }
-      .body { font-family: system-ui, sans-serif; font-size: 14px; fill: #273746; }
-      .box { stroke: #34495e; stroke-width: 2; rx: 10; }
-      .edge { stroke: #7f8c8d; stroke-width: 2.5; fill: none; }
-      .shared { stroke: #b03a2e; stroke-width: 3; stroke-dasharray: 7 5; fill: none; }
-    </style>
-  </defs>
-
-  <text x="600" y="35" text-anchor="middle" class="title">Compile the reachable Python object graph</text>
-
-  <rect x="465" y="65" width="270" height="75" class="box" fill="#eaf2f8"/>
-  <text x="600" y="98" text-anchor="middle" class="label">Simulation</text>
-  <text x="600" y="121" text-anchor="middle" class="body">new compile_ID for this snapshot</text>
-
-  <rect x="45" y="190" width="205" height="75" class="box" fill="#edf6ff"/>
-  <text x="147" y="222" text-anchor="middle" class="label">Root cells</text>
-  <text x="147" y="245" text-anchor="middle" class="body">root universe</text>
-
-  <rect x="280" y="190" width="205" height="75" class="box" fill="#edf6ff"/>
-  <text x="382" y="222" text-anchor="middle" class="label">Sources</text>
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-
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-  <line x1="892" y1="405" x2="700" y2="450" style="stroke:#7f8c8d;stroke-width:2.5"/>
-
-  <rect x="90" y="570" width="1020" height="55" class="box" fill="#f4ecf7"/>
-  <text x="600" y="594" text-anchor="middle" class="label">Simulation-local registries</text>
-  <text x="600" y="615" text-anchor="middle" class="body">cells · surfaces · materials · sources · tallies · meshes · universes · data · distributions · …</text>
-  <line x1="600" y1="525" x2="600" y2="560" style="stroke:#7f8c8d;stroke-width:2.5"/>
-  <text x="930" y="548" class="body">assign ID · sub_type · sub_ID</text>
-</svg>

From 9febfcd21d30850181df74a18d0ebf49eca03e7d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 31 Jul 2026 19:20:55 +0700
Subject: [PATCH 073/202] update changelog mention

---
 docs/source/project/release_policy.rst | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/source/project/release_policy.rst b/docs/source/project/release_policy.rst
index 809ecf04c..fbca4dc08 100644
--- a/docs/source/project/release_policy.rst
+++ b/docs/source/project/release_policy.rst
@@ -4,8 +4,8 @@
 Release Policy
 ==============
 
-MC/DC follows `Semantic Versioning <https://semver.org/>`_ and maintains its
-release history in
+MC/DC follows `Semantic Versioning <https://semver.org/>`_ and maintains a
+human-readable release history in
 `CHANGELOG.md <https://github.com/mcdc-project/mcdc/blob/dev/CHANGELOG.md>`_.
 
 Minor Releases

From e83c372a3f900d1e4058cc55876aa1025d7bd041 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 1 Aug 2026 13:33:36 +0700
Subject: [PATCH 074/202] update architecture index doc

---
 .../developer_guide/architecture/index.rst    | 70 +++++++++++++------
 .../architecture/architecture_flow.svg        |  2 +-
 2 files changed, 49 insertions(+), 23 deletions(-)

diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index 003fbc798..f95a6ea58 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -5,74 +5,100 @@ Architecture
 ============
 
 Architecture documentation explains how MC/DC translates flexible Python model
-definitions into particle-transport execution. The main path follows the model
-through compilation, runtime preparation, Python execution, Numba-CPU acceleration,
-and finally the Numba-GPU and Harmonize layers. MC/DC's architecture flow and
-component responsibilities are presented below.
+definitions into particle-transport executions. The main path follows the model
+through compilation, runtime preparation, Python execution, Numba-CPU
+acceleration, and finally the Numba-GPU and Harmonize layers.
+
+Begin with :doc:`python_first_numba_accelerated_design` for the rationale,
+boundaries, and tradeoffs behind this path. It explains why methods development
+begins with unrestricted MC/DC Python and may progress through Numba-CPU to
+Numba-GPU. The discussion below gives an overview on how the major stages and source
+components support that design.
 
 Architecture Flow
 -----------------
 
-MC/DC has three distinct preparation and execution stages:
+MC/DC begins with a Python model definition, then follows one preparation path
+and a choice of execution backend. The flow has three major processing stages:
 
 #. **Model compilation** discovers the Python objects owned by a
    :class:`mcdc.Simulation`, deduplicates them, and assigns simulation-local
-   identifiers.
+   identifiers. :doc:`simulation_compilation` explains the model's ownership,
+   discovery, and finalization.
 #. **Runtime preparation** converts the compiled model into the structured
    ``simulation`` state and flat ``data`` array consumed by transport.
+   :doc:`runtime_data_layout` explains this numerical representation and its
+   generated access helpers.
 #. **Backend execution** runs the shared transport implementation through
-   Python, Numba-CPU, or Numba-GPU.
+   Python, Numba-CPU, or Numba-GPU. The first two paths are described in
+   :doc:`python_numba_cpu_execution`; :doc:`numba_gpu_execution` continues into
+   GPU code generation, memory placement, and Harmonize scheduling.
 
 .. image:: ../../images/developer_guide/architecture/architecture_flow.svg
    :width: 100%
-   :alt: MC/DC architecture from Python model objects through compilation, runtime preparation, and execution backends.
+   :alt: Flow from model definition through model compilation and runtime preparation to shared transport, which runs with Python, Numba-CPU, or Numba-GPU.
 
 Component Responsibility
 ------------------------
 
+The source tree follows the same separation of responsibilities. Model-facing
+components define and collect the simulation, generated-data components prepare
+the representation used during transport, and transport components implement
+the numerical algorithms shared by the execution backends. The middle column
+of the table maps each component to the corresponding role in the figure.
+
 .. list-table::
    :header-rows: 1
-   :widths: 30 70
+   :widths: 28 22 50
 
    * - Component
+     - Architecture role
      - Responsibility
    * - ``mcdc/object_``
+     - Model definition
      - Defines the Python-side model, configuration, and runtime-state classes.
    * - :class:`mcdc.Simulation` in ``mcdc/object_/simulation.py``
+     - Model definition and control
      - Owns model roots and configuration and controls compilation,
        visualization, and execution.
    * - ``mcdc/code_factory/python_objects_compiler.py``
+     - Model compilation
      - Discovers and registers the connected Python object graph.
    * - ``mcdc/code_factory/numba_layers_generator.py``
+     - Runtime preparation
      - Derives structured dtypes, packs runtime state, generates accessors, and
        initiates GPU-specific preparation when requested.
    * - Runtime ``simulation`` and ``data``
+     - Prepared transport data
      - Generated by ``numba_layers_generator.py``; store fixed-layout state and
        variable-length numerical data,
        respectively.
    * - ``mcdc/mcdc_get`` and ``mcdc/mcdc_set``
+     - Transport data access
      - Provide generated, structured access to fields stored in ``data``.
    * - ``mcdc/transport``
+     - Shared transport
      - Implements the particle-transport algorithms consumed by every
        execution backend.
 
-What's Next
------------
-
-Begin with :doc:`python_first_numba_accelerated_design` for a high-level view of the
-rationale, boundaries, and tradeoffs that shape the architecture.
-
-Then read :doc:`simulation_compilation` to understand ownership of Python model objects,
-recursive object discovery, and simulation-local ID assignment. Continue with
-:doc:`runtime_data_layout` for the packed runtime representation and generated access
-helpers.
+The ``mcdc/object_`` modules, :class:`mcdc.Simulation`, and
+``python_objects_compiler.py`` form the Python model and compilation side of
+the architecture, corresponding to the first two boxes in the upper flow.
+Their relationships are traced in :doc:`simulation_compilation`; contributors
+changing them should also read :doc:`../extending/extending_the_object_model`.
 
-Next, read :doc:`python_numba_cpu_execution` to follow execution first in Python and
-then with Numba-CPU. Finish with :doc:`numba_gpu_execution` for GPU code generation,
-memory placement, and Harmonize scheduling.
+The ``numba_layers_generator.py``, runtime ``simulation`` and ``data``, and
+generated access modules form the data boundary between model construction and
+transport, implementing the runtime-preparation box. Their roles are developed
+in :doc:`runtime_data_layout`. Finally, ``mcdc/transport`` corresponds to the
+shared-transport box, while :doc:`python_numba_cpu_execution` and
+:doc:`numba_gpu_execution` explain the lower execution branches. Practical
+rules for extending the transport algorithms are collected in
+:doc:`../extending/writing_numba_compatible_transport_code`.
 
 .. toctree::
    :maxdepth: 1
+   :hidden:
 
    python_first_numba_accelerated_design
    simulation_compilation
diff --git a/docs/source/images/developer_guide/architecture/architecture_flow.svg b/docs/source/images/developer_guide/architecture/architecture_flow.svg
index ed9a7b365..35f659d51 100644
--- a/docs/source/images/developer_guide/architecture/architecture_flow.svg
+++ b/docs/source/images/developer_guide/architecture/architecture_flow.svg
@@ -1 +1 @@
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From 9fbf7bbe20bd1f14e25787189c2de143337a433f Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 1 Aug 2026 13:42:34 +0700
Subject: [PATCH 075/202] add iterative simulations eample

---
 .../developer_guide/architecture/index.rst    |  2 +-
 docs/source/user_guide/index.rst              |  5 +-
 .../user_guide/iterative_simulations.rst      | 75 +++++++++++++++++++
 .../user_guide/simulation_lifecycle.rst       |  3 +
 4 files changed, 83 insertions(+), 2 deletions(-)
 create mode 100644 docs/source/user_guide/iterative_simulations.rst

diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index f95a6ea58..d6995f25a 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -45,7 +45,7 @@ The source tree follows the same separation of responsibilities. Model-facing
 components define and collect the simulation, generated-data components prepare
 the representation used during transport, and transport components implement
 the numerical algorithms shared by the execution backends. The middle column
-of the table maps each component to the corresponding role in the figure.
+of the table below maps each component to the corresponding role in the figure above.
 
 .. list-table::
    :header-rows: 1
diff --git a/docs/source/user_guide/index.rst b/docs/source/user_guide/index.rst
index 3c5d71fed..626496cdd 100644
--- a/docs/source/user_guide/index.rst
+++ b/docs/source/user_guide/index.rst
@@ -25,12 +25,15 @@ Modeling and Results
 --------------------
 
 Follow :doc:`simulation_lifecycle` for the complete construct, compile,
-visualize, execute, and post-process workflow.
+visualize, execute, and post-process workflow. Use
+:doc:`iterative_simulations` when several runs reuse most of a model while
+changing selected inputs.
 
 .. toctree::
    :maxdepth: 1
 
    simulation_lifecycle
+   iterative_simulations
    tallies
 
 Execution
diff --git a/docs/source/user_guide/iterative_simulations.rst b/docs/source/user_guide/iterative_simulations.rst
new file mode 100644
index 000000000..2c423d851
--- /dev/null
+++ b/docs/source/user_guide/iterative_simulations.rst
@@ -0,0 +1,75 @@
+.. _iterative_simulations:
+
+=====================
+Iterative Simulations
+=====================
+
+Use an iterative simulation when several calculations share most of a model
+but change selected inputs between runs. Common applications include parameter
+sweeps, source updates, feedback iterations, and optimization studies.
+
+The workflow reuses one :class:`mcdc.Simulation` and its Python model objects.
+Each iteration still prepares a complete, consistent simulation for transport;
+MC/DC does not patch only the changed value into a previous execution.
+
+Build the Shared Model Once
+---------------------------
+
+Construct the geometry, materials, sources, tallies, settings, and techniques
+as usual. Attach them to one simulation before beginning the iteration. Objects
+that do not change can remain attached throughout the study.
+
+Use separate simulations only when the calculations require independent object
+graphs. See :doc:`simulation_lifecycle` for the normal construction workflow
+and process-ownership rules.
+
+Update, Compile, and Run
+------------------------
+
+Change the relevant Python objects at the beginning of each iteration. For
+example, the relative probabilities of two sources can be varied while the
+geometry, material, and tally remain unchanged:
+
+.. code-block:: python
+
+   source_mixes = (
+       ("left_20", 0.2),
+       ("left_50", 0.5),
+       ("left_80", 0.8),
+   )
+
+   for case_name, left_fraction in source_mixes:
+       source_left.probability = left_fraction
+       source_right.probability = 1.0 - left_fraction
+       simulation.settings.output_name = f"source_mix_{case_name}"
+
+       simulation.compile()
+       simulation.run()
+
+The explicit ``compile`` call establishes a fresh model snapshot after each
+partial update. It is particularly useful when the updated model will be
+inspected or visualized before execution.
+
+``simulation.run()`` automatically compiles an unprepared simulation and marks
+it unprepared again after execution. A simple loop that only updates and runs
+may therefore omit the explicit ``compile`` call. If an attached object is
+modified after an explicit compilation or visualization, compile again before
+inspecting, visualizing, or running the updated model.
+
+Keep Outputs Distinct
+---------------------
+
+Assign a unique ``simulation.settings.output_name`` before every run so that a
+later iteration does not replace an earlier result. Keep tally names stable
+when the same post-processing operation will be applied to every output.
+
+The driver or post-processing script can record the iteration parameters next
+to each output name. This makes plots and comparisons reproducible without
+depending on internal object identifiers.
+
+Complete Example
+----------------
+
+See :ref:`example_iterative_source_reweighting` for a complete runnable input.
+Its post-processing script overlays the flux profiles from three source
+mixtures and checks their expected symmetry.
diff --git a/docs/source/user_guide/simulation_lifecycle.rst b/docs/source/user_guide/simulation_lifecycle.rst
index 5df61b023..29e5198ac 100644
--- a/docs/source/user_guide/simulation_lifecycle.rst
+++ b/docs/source/user_guide/simulation_lifecycle.rst
@@ -170,6 +170,9 @@ and its analysis remains clear:
 
 The tally is then available under ``tallies/slab_flux`` in ``slab.h5``.
 
+For workflows that reuse most of a model while changing selected inputs between
+runs, continue with :doc:`iterative_simulations`.
+
 Complete Workflows
 ------------------
 

From 6384aa71878c220a488c521ef5298a83847700ac Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 1 Aug 2026 13:49:33 +0700
Subject: [PATCH 076/202] add space after table

---
 docs/source/_static/custom.css                     | 5 +++++
 docs/source/developer_guide/architecture/index.rst | 2 ++
 2 files changed, 7 insertions(+)

diff --git a/docs/source/_static/custom.css b/docs/source/_static/custom.css
index 67d32c29e..21cde4696 100644
--- a/docs/source/_static/custom.css
+++ b/docs/source/_static/custom.css
@@ -9,3 +9,8 @@ dt.sig.sig-object.py > em.property {
 .simulation-members {
     margin-left: 30px;
 }
+
+/* Separate the architecture component table from its follow-up discussion. */
+.architecture-component-followup {
+    margin-top: 1.5rem;
+}
diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index d6995f25a..8fe7d937b 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -81,6 +81,8 @@ of the table below maps each component to the corresponding role in the figure a
      - Implements the particle-transport algorithms consumed by every
        execution backend.
 
+.. rst-class:: architecture-component-followup
+
 The ``mcdc/object_`` modules, :class:`mcdc.Simulation`, and
 ``python_objects_compiler.py`` form the Python model and compilation side of
 the architecture, corresponding to the first two boxes in the upper flow.

From cd5c76384cafdde9daf0422d02ea032bb5ef94f2 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 1 Aug 2026 13:53:19 +0700
Subject: [PATCH 077/202] update architecture table

---
 .../developer_guide/architecture/index.rst       | 16 +++++++++-------
 1 file changed, 9 insertions(+), 7 deletions(-)

diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index 8fe7d937b..ab6dd3ee4 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -45,7 +45,9 @@ The source tree follows the same separation of responsibilities. Model-facing
 components define and collect the simulation, generated-data components prepare
 the representation used during transport, and transport components implement
 the numerical algorithms shared by the execution backends. The middle column
-of the table below maps each component to the corresponding role in the figure above.
+of the table below maps each component to the corresponding role in the figure
+above. Paths in the component column are relative to the top-level ``mcdc/``
+package.
 
 .. list-table::
    :header-rows: 1
@@ -54,17 +56,17 @@ of the table below maps each component to the corresponding role in the figure a
    * - Component
      - Architecture role
      - Responsibility
-   * - ``mcdc/object_``
+   * - ``object_/``
      - Model definition
      - Defines the Python-side model, configuration, and runtime-state classes.
-   * - :class:`mcdc.Simulation` in ``mcdc/object_/simulation.py``
+   * - :class:`mcdc.Simulation` in ``object_/simulation.py``
      - Model definition and control
      - Owns model roots and configuration and controls compilation,
        visualization, and execution.
-   * - ``mcdc/code_factory/python_objects_compiler.py``
+   * - ``code_factory/python_objects_compiler.py``
      - Model compilation
      - Discovers and registers the connected Python object graph.
-   * - ``mcdc/code_factory/numba_layers_generator.py``
+   * - ``code_factory/numba_layers_generator.py``
      - Runtime preparation
      - Derives structured dtypes, packs runtime state, generates accessors, and
        initiates GPU-specific preparation when requested.
@@ -73,10 +75,10 @@ of the table below maps each component to the corresponding role in the figure a
      - Generated by ``numba_layers_generator.py``; store fixed-layout state and
        variable-length numerical data,
        respectively.
-   * - ``mcdc/mcdc_get`` and ``mcdc/mcdc_set``
+   * - ``mcdc_get/`` and ``mcdc_set/``
      - Transport data access
      - Provide generated, structured access to fields stored in ``data``.
-   * - ``mcdc/transport``
+   * - ``transport/``
      - Shared transport
      - Implements the particle-transport algorithms consumed by every
        execution backend.

From 731a22159149726d9a12c5fd39fa5f312944705d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 1 Aug 2026 17:13:21 +0700
Subject: [PATCH 078/202] minor edit docs

---
 .../developer_guide/architecture/index.rst    | 19 ++++++++++---------
 1 file changed, 10 insertions(+), 9 deletions(-)

diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index ab6dd3ee4..3760537de 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -77,7 +77,8 @@ package.
        respectively.
    * - ``mcdc_get/`` and ``mcdc_set/``
      - Transport data access
-     - Provide generated, structured access to fields stored in ``data``.
+     - Generated by ``numba_layers_generator.py``; provide structured access to
+       fields stored in ``data``.
    * - ``transport/``
      - Shared transport
      - Implements the particle-transport algorithms consumed by every
@@ -86,16 +87,16 @@ package.
 .. rst-class:: architecture-component-followup
 
 The ``mcdc/object_`` modules, :class:`mcdc.Simulation`, and
-``python_objects_compiler.py`` form the Python model and compilation side of
-the architecture, corresponding to the first two boxes in the upper flow.
-Their relationships are traced in :doc:`simulation_compilation`; contributors
-changing them should also read :doc:`../extending/extending_the_object_model`.
+``python_objects_compiler.py`` form the Python model and compilation side (the
+first two boxes) of the architecture flow. Their relationships are discussed in
+:doc:`simulation_compilation`; contributors changing them should also read
+:doc:`../extending/extending_the_object_model`.
 
 The ``numba_layers_generator.py``, runtime ``simulation`` and ``data``, and
-generated access modules form the data boundary between model construction and
-transport, implementing the runtime-preparation box. Their roles are developed
-in :doc:`runtime_data_layout`. Finally, ``mcdc/transport`` corresponds to the
-shared-transport box, while :doc:`python_numba_cpu_execution` and
+generated access modules (``mcdc_get`` and ``mcdc_set``) form the data boundary
+between model construction and transport, implementing the runtime-preparation box.
+Their roles are discussed in :doc:`runtime_data_layout`. Finally, ``mcdc/transport``
+corresponds to the shared-transport box, while :doc:`python_numba_cpu_execution` and
 :doc:`numba_gpu_execution` explain the lower execution branches. Practical
 rules for extending the transport algorithms are collected in
 :doc:`../extending/writing_numba_compatible_transport_code`.

From c244c18f07dc787c2216478eed076e3cee514987 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 2 Aug 2026 12:43:01 +0700
Subject: [PATCH 079/202] update docs

---
 .../developer_guide/architecture/index.rst    |  47 +++----
 .../architecture/architecture_flow.svg        |   2 +-
 .../architecture/runtime_data_layout.svg      | 128 +++++++++++-------
 3 files changed, 93 insertions(+), 84 deletions(-)

diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index 3760537de..51005934f 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -4,39 +4,24 @@
 Architecture
 ============
 
-Architecture documentation explains how MC/DC translates flexible Python model
-definitions into particle-transport executions. The main path follows the model
-through compilation, runtime preparation, Python execution, Numba-CPU
-acceleration, and finally the Numba-GPU and Harmonize layers.
+Architecture documentation explains how MC/DC translates flexible Python model definitions into particle-transport execution:
 
-Begin with :doc:`python_first_numba_accelerated_design` for the rationale,
-boundaries, and tradeoffs behind this path. It explains why methods development
-begins with unrestricted MC/DC Python and may progress through Numba-CPU to
-Numba-GPU. The discussion below gives an overview on how the major stages and source
-components support that design.
-
-Architecture Flow
------------------
+.. image:: ../../images/developer_guide/architecture/architecture_flow.svg
+   :width: 100%
+   :alt: MC/DC's architecture flow from model definition through simulation compilation and runtime preparation to shared transport, which runs with Python, Numba-CPU, or Numba-GPU execution modes.
 
-MC/DC begins with a Python model definition, then follows one preparation path
-and a choice of execution backend. The flow has three major processing stages:
+The architecture flow follows a Monte Carlo transport model from definition through one common preparation path, then branches into the Python, Numba-CPU, or Numba-GPU execution modes.
+The flow has three major processing stages:
 
-#. **Model compilation** discovers the Python objects owned by a
-   :class:`mcdc.Simulation`, deduplicates them, and assigns simulation-local
-   identifiers. :doc:`simulation_compilation` explains the model's ownership,
-   discovery, and finalization.
-#. **Runtime preparation** converts the compiled model into the structured
-   ``simulation`` state and flat ``data`` array consumed by transport.
-   :doc:`runtime_data_layout` explains this numerical representation and its
-   generated access helpers.
-#. **Backend execution** runs the shared transport implementation through
-   Python, Numba-CPU, or Numba-GPU. The first two paths are described in
-   :doc:`python_numba_cpu_execution`; :doc:`numba_gpu_execution` continues into
-   GPU code generation, memory placement, and Harmonize scheduling.
+#. **Simulation compilation** discovers the Python objects owned by a :class:`mcdc.Simulation`, deduplicates them, and assigns simulation-local identifiers.
+   :doc:`simulation_compilation` explains model ownership, discovery, and finalization.
+#. **Runtime preparation** converts the compiled model into the structured ``simulation`` state and flat ``data`` array consumed by transport.
+   :doc:`runtime_data_layout` explains this numerical representation and its generated access helpers.
+#. **Transport execution** runs the common, adaptable transport implementation in the selected execution mode.
+   :doc:`python_numba_cpu_execution` describes Python and Numba-CPU execution, while :doc:`numba_gpu_execution` continues into GPU code generation, memory placement, and Harmonize scheduling.
 
-.. image:: ../../images/developer_guide/architecture/architecture_flow.svg
-   :width: 100%
-   :alt: Flow from model definition through model compilation and runtime preparation to shared transport, which runs with Python, Numba-CPU, or Numba-GPU.
+Visit :doc:`python_first_numba_accelerated_design` for the rationale, boundaries, and tradeoffs that shape MC/DC's architecture.
+It explains why method development begins in unrestricted Python mode and may progress through Numba-CPU to Numba-GPU.
 
 Component Responsibility
 ------------------------
@@ -45,7 +30,7 @@ The source tree follows the same separation of responsibilities. Model-facing
 components define and collect the simulation, generated-data components prepare
 the representation used during transport, and transport components implement
 the numerical algorithms shared by the execution backends. The middle column
-of the table below maps each component to the corresponding role in the figure
+of the table below maps each component to the corresponding role in the architecture flow shown in the figure
 above. Paths in the component column are relative to the top-level ``mcdc/``
 package.
 
@@ -64,7 +49,7 @@ package.
      - Owns model roots and configuration and controls compilation,
        visualization, and execution.
    * - ``code_factory/python_objects_compiler.py``
-     - Model compilation
+     - Simulation compilation
      - Discovers and registers the connected Python object graph.
    * - ``code_factory/numba_layers_generator.py``
      - Runtime preparation
diff --git a/docs/source/images/developer_guide/architecture/architecture_flow.svg b/docs/source/images/developer_guide/architecture/architecture_flow.svg
index 35f659d51..95eaddfc9 100644
--- a/docs/source/images/developer_guide/architecture/architecture_flow.svg
+++ b/docs/source/images/developer_guide/architecture/architecture_flow.svg
@@ -1 +1 @@
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fill-rule="nonzero" fill-opacity="1"/><path d="M3821.33 966 3821.33 1222.47 3466 1222.47 3472.88 1215.6 3472.88 1379.14 3459.13 1379.14 3459.13 1208.72 3814.45 1208.72 3807.58 1215.6 3807.58 966ZM3496 1341.36 3466 1392.79 3436 1341.36C3434.09 1338.08 3435.19 1333.87 3438.47 1331.95 3441.75 1330.04 3445.96 1331.15 3447.88 1334.43L3471.94 1375.68 3460.06 1375.68 3484.12 1334.43C3486.04 1331.15 3490.25 1330.04 3493.53 1331.95 3496.81 1333.87 3497.91 1338.08 3496 1341.36Z" fill="#000000" fill-rule="nonzero" fill-opacity="1"/><text fill="#000000" fill-opacity="1" font-family="Arial,Arial_MSFontService,sans-serif" font-style="normal" font-variant="normal" font-weight="700" font-stretch="normal" font-size="83" text-anchor="start" direction="ltr" writing-mode="lr-tb" unicode-bidi="normal" text-decoration="none" transform="matrix(1 0 0 1 1668.23 416)">MC/DC’s Architecture Flow</text></g></g></svg>
\ No newline at end of file
diff --git a/docs/source/images/developer_guide/architecture/runtime_data_layout.svg b/docs/source/images/developer_guide/architecture/runtime_data_layout.svg
index c9a683310..4eacbd26c 100644
--- a/docs/source/images/developer_guide/architecture/runtime_data_layout.svg
+++ b/docs/source/images/developer_guide/architecture/runtime_data_layout.svg
@@ -1,79 +1,103 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="590" viewBox="0 0 1200 590" role="img" aria-labelledby="title desc">
+<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="720" viewBox="0 0 1200 720" role="img" aria-labelledby="title desc">
   <title id="title">MC/DC runtime data layout</title>
-  <desc id="desc">Variable-sized Python arrays are flattened into a one-dimensional data array. Structured simulation records retain fixed fields and offsets, lengths, and shape metadata used by generated getters and setters.</desc>
+  <desc id="desc">A cell refers to its boundary surfaces, and a surface refers to an attached surface-crossing tally. The cell and surfaces are stored directly. The tally has a common base record and a concrete surface-crossing record. Their variable-length ID lists and tally values are flattened into a shared data array.</desc>
   <defs>
-    <marker id="arrow" markerWidth="10" markerHeight="10" refX="8" refY="3" orient="auto">
-      <path d="M0,0 L0,6 L9,3 z" fill="#566573"/>
-    </marker>
     <style>
       .title { font-family: system-ui, sans-serif; font-size: 23px; font-weight: 700; fill: #17202a; }
       .label { font-family: system-ui, sans-serif; font-size: 17px; font-weight: 650; fill: #17202a; }
-      .mono { font-family: ui-monospace, SFMono-Regular, Menlo, monospace; font-size: 15px; fill: #273746; }
+      .mono { font-family: ui-monospace, SFMono-Regular, Menlo, monospace; font-size: 14px; fill: #273746; }
       .body { font-family: system-ui, sans-serif; font-size: 14px; fill: #273746; }
+      .small { font-family: system-ui, sans-serif; font-size: 12px; fill: #566573; }
       .box { stroke: #34495e; stroke-width: 2; rx: 10; }
-      .arrow { stroke: #566573; stroke-width: 2.5; fill: none; }
     </style>
   </defs>
 
-  <text x="600" y="35" text-anchor="middle" class="title">Fixed-layout metadata describes variable-length payloads</text>
+  <text x="600" y="35" text-anchor="middle" class="title">Connected model objects become fixed-layout records and flat data</text>
 
-  <rect x="35" y="75" width="300" height="330" class="box" fill="#eaf2f8"/>
+  <rect x="35" y="75" width="300" height="470" class="box" fill="#eaf2f8"/>
   <text x="185" y="108" text-anchor="middle" class="label">Python model objects</text>
 
-  <rect x="65" y="140" width="240" height="95" class="box" fill="#ffffff"/>
-  <text x="85" y="168" class="mono">MeshStructured</text>
-  <text x="85" y="195" class="mono">z = [0, 1, 2, 3]</text>
-  <text x="85" y="218" class="body">problem-dependent length</text>
+  <line x1="185" y1="230" x2="185" y2="270" stroke="#566573" stroke-width="2.5"/>
+  <text x="200" y="255" class="small">bounded by</text>
+  <line x1="185" y1="375" x2="185" y2="415" stroke="#566573" stroke-width="2.5"/>
+  <text x="200" y="400" class="small">filters</text>
 
-  <rect x="65" y="265" width="240" height="110" class="box" fill="#ffffff"/>
-  <text x="85" y="293" class="mono">MaterialMG</text>
-  <text x="85" y="320" class="mono">capture = [0.1, 0.2]</text>
-  <text x="85" y="345" class="mono">scatter = [[…], […]]</text>
-  <text x="85" y="367" class="body">problem-dependent shape</text>
+  <rect x="65" y="130" width="240" height="100" class="box" fill="#ffffff"/>
+  <text x="85" y="160" class="mono">Cell</text>
+  <text x="85" y="188" class="mono">region = +lower &amp; -upper</text>
+  <text x="85" y="216" class="body">directly stored object</text>
 
-  <rect x="450" y="75" width="315" height="330" class="box" fill="#fef9e7"/>
-  <text x="607" y="108" text-anchor="middle" class="label">structured simulation</text>
+  <rect x="65" y="270" width="240" height="105" class="box" fill="#ffffff"/>
+  <text x="85" y="300" class="mono">lower = PlaneZ(z=0)</text>
+  <text x="85" y="328" class="mono">upper = PlaneZ(z=2)</text>
+  <text x="85" y="356" class="body">directly stored surfaces</text>
 
-  <rect x="480" y="140" width="255" height="120" class="box" fill="#ffffff"/>
-  <text x="500" y="168" class="mono">structured_mesh[0]</text>
-  <text x="500" y="195" class="mono">ID = 0</text>
-  <text x="500" y="220" class="mono">z_offset = 0</text>
-  <text x="500" y="245" class="mono">z_length = 4</text>
+  <rect x="65" y="415" width="240" height="110" class="box" fill="#ffffff"/>
+  <text x="85" y="445" class="mono">Tally</text>
+  <text x="85" y="473" class="mono">surface = upper</text>
+  <text x="85" y="501" class="mono">cell = cell</text>
+  <text x="85" y="518" class="body">surface-crossing tally</text>
 
-  <rect x="480" y="285" width="255" height="90" class="box" fill="#ffffff"/>
-  <text x="500" y="313" class="mono">material[0]</text>
-  <text x="500" y="338" class="mono">capture_offset = 4</text>
-  <text x="500" y="363" class="mono">capture_length = 2</text>
+  <rect x="400" y="75" width="420" height="470" class="box" fill="#fef9e7"/>
+  <text x="610" y="108" text-anchor="middle" class="label">structured simulation</text>
 
-  <line x1="335" y1="190" x2="440" y2="190" style="stroke:#566573;stroke-width:2.5"/>
-  <line x1="335" y1="320" x2="440" y2="320" style="stroke:#566573;stroke-width:2.5"/>
-  <text x="387" y="175" text-anchor="middle" class="body">metadata</text>
+  <line x1="610" y1="210" x2="610" y2="235" stroke="#566573" stroke-width="2.5"/>
+  <text x="625" y="228" class="small">surface IDs</text>
+  <line x1="610" y1="335" x2="610" y2="360" stroke="#566573" stroke-width="2.5"/>
+  <text x="625" y="353" class="small">tally ID</text>
+  <line x1="610" y1="440" x2="610" y2="455" stroke="#566573" stroke-width="2.5"/>
+  <text x="625" y="452" class="small">sub_ID</text>
 
-  <rect x="875" y="75" width="290" height="330" class="box" fill="#e8f8f5"/>
+  <rect x="425" y="125" width="370" height="85" class="box" fill="#ffffff"/>
+  <text x="445" y="154" class="mono">cells[0]</text>
+  <text x="445" y="180" class="mono">N_surface = 2</text>
+  <text x="445" y="203" class="mono">surface_IDs_offset = 0</text>
+
+  <rect x="425" y="235" width="370" height="100" class="box" fill="#ffffff"/>
+  <text x="445" y="264" class="mono">surfaces[0], surfaces[1]</text>
+  <text x="445" y="290" class="mono">type = SURFACE_PLANE_Z</text>
+  <text x="445" y="313" class="mono">surfaces[1].N_surface_crossing_tally = 1</text>
+  <text x="445" y="330" class="small">surface_crossing_tally_IDs_offset = 2</text>
+
+  <rect x="425" y="360" width="370" height="80" class="box" fill="#ffffff"/>
+  <text x="445" y="389" class="mono">tallies[0]</text>
+  <text x="445" y="413" class="mono">sub_type = TALLY_SURFACE_CROSSING</text>
+  <text x="445" y="434" class="mono">sub_ID = 0</text>
+
+  <rect x="425" y="455" width="370" height="80" class="box" fill="#ffffff"/>
+  <text x="445" y="482" class="mono">surface_crossing_tallies[0]</text>
+  <text x="445" y="505" class="mono">surface_filter_ID = 1</text>
+  <text x="445" y="528" class="mono">cell_filter_ID = 0</text>
+
+  <line x1="335" y1="180" x2="400" y2="168" stroke="#566573" stroke-width="2.5"/>
+  <line x1="335" y1="322" x2="400" y2="285" stroke="#566573" stroke-width="2.5"/>
+  <line x1="335" y1="470" x2="400" y2="398" stroke="#566573" stroke-width="2.5"/>
+
+  <rect x="875" y="75" width="290" height="470" class="box" fill="#e8f8f5"/>
   <text x="1020" y="108" text-anchor="middle" class="label">flat data array</text>
 
-  <rect x="905" y="145" width="230" height="54" class="box" fill="#d6eaf8"/>
-  <text x="1020" y="168" text-anchor="middle" class="mono">0 · 1 · 2 · 3</text>
-  <text x="1020" y="190" text-anchor="middle" class="body">mesh.z</text>
+  <rect x="905" y="145" width="230" height="55" class="box" fill="#d5f5e3"/>
+  <text x="1020" y="169" text-anchor="middle" class="mono">0 · 1</text>
+  <text x="1020" y="191" text-anchor="middle" class="body">cell.surface_IDs</text>
 
-  <rect x="905" y="215" width="230" height="54" class="box" fill="#d5f5e3"/>
-  <text x="1020" y="238" text-anchor="middle" class="mono">0.1 · 0.2</text>
-  <text x="1020" y="260" text-anchor="middle" class="body">material.capture</text>
+  <rect x="905" y="260" width="230" height="55" class="box" fill="#d6eaf8"/>
+  <text x="1020" y="284" text-anchor="middle" class="mono">0</text>
+  <text x="1020" y="306" text-anchor="middle" class="body">surface-crossing tally IDs</text>
 
-  <rect x="905" y="285" width="230" height="54" class="box" fill="#f5eef8"/>
-  <text x="1020" y="308" text-anchor="middle" class="mono">… flattened scatter …</text>
-  <text x="1020" y="330" text-anchor="middle" class="body">next payload</text>
+  <rect x="905" y="385" width="230" height="55" class="box" fill="#f5eef8"/>
+  <text x="1020" y="409" text-anchor="middle" class="mono">… scores and bins …</text>
+  <text x="1020" y="431" text-anchor="middle" class="body">tally variable fields</text>
 
-  <text x="1020" y="370" text-anchor="middle" class="mono">data[0:N]</text>
-  <line x1="765" y1="190" x2="865" y2="190" style="stroke:#566573;stroke-width:2.5"/>
-  <line x1="765" y1="330" x2="865" y2="330" style="stroke:#566573;stroke-width:2.5"/>
-  <text x="815" y="175" text-anchor="middle" class="body">offsets</text>
+  <text x="1020" y="505" text-anchor="middle" class="mono">data[0:N]</text>
+  <line x1="820" y1="168" x2="875" y2="172" stroke="#566573" stroke-width="2.5"/>
+  <line x1="820" y1="285" x2="875" y2="287" stroke="#566573" stroke-width="2.5"/>
+  <line x1="820" y1="398" x2="875" y2="412" stroke="#566573" stroke-width="2.5"/>
 
-  <rect x="180" y="465" width="840" height="90" class="box" fill="#f4ecf7"/>
-  <text x="600" y="495" text-anchor="middle" class="label">generated mcdc_get / mcdc_set helpers</text>
-  <text x="600" y="523" text-anchor="middle" class="mono">z(i, mesh, data) → data[mesh["z_offset"] + i]</text>
-  <text x="600" y="546" text-anchor="middle" class="body">transport uses logical fields without embedding Python references</text>
+  <rect x="180" y="590" width="840" height="95" class="box" fill="#f4ecf7"/>
+  <text x="600" y="620" text-anchor="middle" class="label">generated mcdc_get / mcdc_set helpers</text>
+  <text x="600" y="647" text-anchor="middle" class="mono">mcdc_get.cell.surface_IDs(i, cell, data)</text>
+  <text x="600" y="670" text-anchor="middle" class="mono">mcdc_get.surface.surface_crossing_tally_IDs(i, surface, data)</text>
 
-  <line x1="607" y1="405" x2="607" y2="455" style="stroke:#566573;stroke-width:2.5"/>
-  <path d="M1020 405 C1020 445, 900 450, 845 465" style="stroke:#566573;stroke-width:2.5;fill:none"/>
+  <line x1="610" y1="545" x2="610" y2="590" stroke="#566573" stroke-width="2.5"/>
+  <line x1="1020" y1="545" x2="845" y2="590" stroke="#566573" stroke-width="2.5"/>
 </svg>

From 4435d83f995a3fa08fc6548c3add12ad275713f5 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 2 Aug 2026 20:14:59 +0700
Subject: [PATCH 080/202] update docs

---
 docs/source/_static/custom.css                |  5 +
 .../developer_guide/architecture/index.rst    | 59 +++++-------
 .../architecture/runtime_data_layout.rst      | 93 ++++++++++++++-----
 docs/source/developer_guide/index.rst         | 16 +---
 4 files changed, 105 insertions(+), 68 deletions(-)

diff --git a/docs/source/_static/custom.css b/docs/source/_static/custom.css
index 21cde4696..d20b9f974 100644
--- a/docs/source/_static/custom.css
+++ b/docs/source/_static/custom.css
@@ -10,6 +10,11 @@ dt.sig.sig-object.py > em.property {
     margin-left: 30px;
 }
 
+/* Separate the architecture flow figure from its introductory discussion. */
+.architecture-flow-figure {
+    margin-bottom: 1.5rem;
+}
+
 /* Separate the architecture component table from its follow-up discussion. */
 .architecture-component-followup {
     margin-top: 1.5rem;
diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index 51005934f..1dfc17ec7 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -8,6 +8,7 @@ Architecture documentation explains how MC/DC translates flexible Python model d
 
 .. image:: ../../images/developer_guide/architecture/architecture_flow.svg
    :width: 100%
+   :class: architecture-flow-figure
    :alt: MC/DC's architecture flow from model definition through simulation compilation and runtime preparation to shared transport, which runs with Python, Numba-CPU, or Numba-GPU execution modes.
 
 The architecture flow follows a Monte Carlo transport model from definition through one common preparation path, then branches into the Python, Numba-CPU, or Numba-GPU execution modes.
@@ -16,7 +17,7 @@ The flow has three major processing stages:
 #. **Simulation compilation** discovers the Python objects owned by a :class:`mcdc.Simulation`, deduplicates them, and assigns simulation-local identifiers.
    :doc:`simulation_compilation` explains model ownership, discovery, and finalization.
 #. **Runtime preparation** converts the compiled model into the structured ``simulation`` state and flat ``data`` array consumed by transport.
-   :doc:`runtime_data_layout` explains this numerical representation and its generated access helpers.
+   :doc:`runtime_data_layout` explains this numerical representation and its generated access helpers, ``mcdc_get`` and ``mcdc_set``.
 #. **Transport execution** runs the common, adaptable transport implementation in the selected execution mode.
    :doc:`python_numba_cpu_execution` describes Python and Numba-CPU execution, while :doc:`numba_gpu_execution` continues into GPU code generation, memory placement, and Harmonize scheduling.
 
@@ -26,13 +27,12 @@ It explains why method development begins in unrestricted Python mode and may pr
 Component Responsibility
 ------------------------
 
-The source tree follows the same separation of responsibilities. Model-facing
-components define and collect the simulation, generated-data components prepare
-the representation used during transport, and transport components implement
-the numerical algorithms shared by the execution backends. The middle column
-of the table below maps each component to the corresponding role in the architecture flow shown in the figure
-above. Paths in the component column are relative to the top-level ``mcdc/``
-package.
+The source tree follows the same separation of responsibilities shown in the architecture flow.
+Model-facing components define and collect the simulation.
+Code-factory components compile the model and prepare its runtime representation.
+Transport components implement the numerical algorithms shared by all execution modes.
+The table maps each component to its corresponding architecture role.
+Paths in the component column are relative to the top-level ``mcdc/`` package.
 
 .. list-table::
    :header-rows: 1
@@ -46,45 +46,34 @@ package.
      - Defines the Python-side model, configuration, and runtime-state classes.
    * - :class:`mcdc.Simulation` in ``object_/simulation.py``
      - Model definition and control
-     - Owns model roots and configuration and controls compilation,
-       visualization, and execution.
+     - Owns model roots and configuration and controls compilation, visualization, and execution.
    * - ``code_factory/python_objects_compiler.py``
      - Simulation compilation
      - Discovers and registers the connected Python object graph.
    * - ``code_factory/numba_layers_generator.py``
      - Runtime preparation
-     - Derives structured dtypes, packs runtime state, generates accessors, and
-       initiates GPU-specific preparation when requested.
+     - Derives structured dtypes, packs runtime state, generates accessors, and initiates GPU-specific preparation when requested.
    * - Runtime ``simulation`` and ``data``
-     - Prepared transport data
-     - Generated by ``numba_layers_generator.py``; store fixed-layout state and
-       variable-length numerical data,
-       respectively.
+     - Prepared runtime data
+     - Store fixed-layout state and variable-length numerical data generated by ``numba_layers_generator.py``.
    * - ``mcdc_get/`` and ``mcdc_set/``
-     - Transport data access
-     - Generated by ``numba_layers_generator.py``; provide structured access to
-       fields stored in ``data``.
+     - Runtime data access
+     - Provide generated access to variable-length fields stored in ``data``.
    * - ``transport/``
      - Shared transport
-     - Implements the particle-transport algorithms consumed by every
-       execution backend.
+     - Implements the particle-transport algorithms used by every execution mode.
 
 .. rst-class:: architecture-component-followup
 
-The ``mcdc/object_`` modules, :class:`mcdc.Simulation`, and
-``python_objects_compiler.py`` form the Python model and compilation side (the
-first two boxes) of the architecture flow. Their relationships are discussed in
-:doc:`simulation_compilation`; contributors changing them should also read
-:doc:`../extending/extending_the_object_model`.
-
-The ``numba_layers_generator.py``, runtime ``simulation`` and ``data``, and
-generated access modules (``mcdc_get`` and ``mcdc_set``) form the data boundary
-between model construction and transport, implementing the runtime-preparation box.
-Their roles are discussed in :doc:`runtime_data_layout`. Finally, ``mcdc/transport``
-corresponds to the shared-transport box, while :doc:`python_numba_cpu_execution` and
-:doc:`numba_gpu_execution` explain the lower execution branches. Practical
-rules for extending the transport algorithms are collected in
-:doc:`../extending/writing_numba_compatible_transport_code`.
+The ``mcdc/object_`` modules, :class:`mcdc.Simulation`, and ``python_objects_compiler.py`` implement the model-definition and simulation-compilation stages.
+:doc:`simulation_compilation` explains their relationships, while :doc:`../extending/extending_the_object_model` explains how contributors can extend them.
+
+The ``numba_layers_generator.py``, runtime ``simulation`` and ``data``, and generated ``mcdc_get`` and ``mcdc_set`` modules implement runtime preparation and form the data boundary between model construction and transport.
+:doc:`runtime_data_layout` explains their roles.
+
+The ``mcdc/transport`` package implements the shared-transport stage.
+:doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution` explain how the execution modes run it.
+:doc:`../extending/writing_numba_compatible_transport_code` provides practical rules for extending its algorithms.
 
 .. toctree::
    :maxdepth: 1
diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index a9bd8802e..c1375e616 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -16,9 +16,13 @@ The representation has two complementary parts:
    A contiguous one-dimensional NumPy array containing variable-length
    numerical payloads and lists of object IDs.
 
-The same logical representation is used by Python, Numba-CPU, and Numba-GPU
-execution. It should therefore be understood as MC/DC's transport runtime
-model, not as a separate Numba-only model.
+The same logical representation is supplied to Python, Numba-CPU, and
+Numba-GPU execution. It should therefore be understood as MC/DC's transport
+runtime model, not as a separate Numba-only model. During Python-only
+prototyping, transport code may also access arbitrary Python state alongside
+this representation. A method intended for portable, maintained execution must
+express the state required by transport through the prepared representation.
+See :doc:`python_first_numba_accelerated_design` for this development model.
 
 Why Two Structures?
 -------------------
@@ -32,21 +36,67 @@ MC/DC separates fixed-layout metadata from variable-length values:
 
 .. image:: ../../images/developer_guide/architecture/runtime_data_layout.svg
    :width: 100%
-   :alt: A structured simulation record using offsets, lengths, and shapes to describe fields stored in a flat data array.
+   :alt: A cell, its boundary surfaces, and a surface-crossing tally become connected runtime records whose variable-length fields are stored in a flat data array.
 
-For a variable-length field such as ``mesh.z``, the mesh record stores values
-equivalent to:
+Object Collections
+^^^^^^^^^^^^^^^^^^
+
+Registered model objects are stored in collections on ``simulation``. The
+figure follows a cell, its boundary surfaces, and a surface-crossing tally.
+It demonstrates both forms of runtime collection.
+
+For a non-polymorphic category, an object's simulation-local ID directly
+indexes its collection. A particle's current cell and one of its boundary
+surfaces are therefore retrieved with:
+
+.. code-block:: python
+
+   cell = simulation["cells"][particle["cell_ID"]]
+   surface_ID = int(mcdc_get.cell.surface_IDs(0, cell, data))
+   surface = simulation["surfaces"][surface_ID]
+
+A polymorphic category has both a common base collection and a collection for
+each concrete representation. A surface stores the IDs of the surface-crossing
+tallies attached to it. Each ID first selects a base tally record, whose
+``sub_type`` and ``sub_ID`` identify the concrete surface-crossing record:
+
+.. code-block:: python
+
+   from mcdc.constant import TALLY_SURFACE_CROSSING
+
+
+   tally_ID = int(
+       mcdc_get.surface.surface_crossing_tally_IDs(0, surface, data)
+   )
+   tally = simulation["tallies"][tally_ID]
+
+   if tally["sub_type"] == TALLY_SURFACE_CROSSING:
+       surface_crossing_tally = simulation["surface_crossing_tallies"][
+           tally["sub_ID"]
+       ]
+
+The concrete tally record retains ``surface_filter_ID`` and ``cell_filter_ID``,
+connecting it back to the selected surface and cell. All IDs are assigned
+during model compilation and identify objects only within the current
+simulation snapshot. The hierarchy and ID assignment are described in
+:doc:`simulation_compilation`.
+
+Variable-Length Fields
+^^^^^^^^^^^^^^^^^^^^^^
+
+For a variable-length list such as a cell's boundary surfaces, the cell record
+stores values equivalent to:
 
 .. code-block:: text
 
-   z_offset = 120
-   z_length = 61
+   surface_IDs_offset = 120
+   N_surface = 2
 
-and the values occupy:
+and the two surface IDs occupy:
 
 .. code-block:: text
 
-   data[120:181]
+   data[120:122]
 
 For multidimensional arrays, annotated shape metadata supplies the strides used
 to reconstruct logical indexing. The payload itself is flattened when packed.
@@ -68,10 +118,6 @@ maps them to runtime fields:
 - Members named in a class's ``non_numba`` list are excluded from the packed
   representation or handled specially.
 
-Polymorphic base and subtype collections receive separate structured dtypes.
-The base ``ID``, ``sub_type``, ``sub_ID``, and child ``base_ID`` fields connect
-those collections without Python references.
-
 Packing is performed in two passes:
 
 #. Walk the compiled objects to build records and calculate the required
@@ -109,8 +155,8 @@ Conceptually, a generated element getter performs:
 
 .. code-block:: python
 
-   def z(index, mesh, data):
-       offset = mesh["z_offset"]
+   def surface_IDs(index, cell, data):
+       offset = cell["surface_IDs_offset"]
        return data[offset + index]
 
 Generated helpers also provide operations for complete arrays, final elements,
@@ -119,15 +165,16 @@ can therefore express logical access such as:
 
 .. code-block:: python
 
-   boundary = mcdc_get.structured_mesh.z(index, mesh, data)
+   surface_ID = int(mcdc_get.cell.surface_IDs(index, cell, data))
 
-without depending on where that mesh's z-grid happens to reside in ``data``.
+without depending on where that cell's surface IDs happen to reside in
+``data``.
 
 Transport Consumption
 ---------------------
 
-Modules under ``mcdc/transport`` consume only the runtime representation and
-primitive transport records. They use:
+Portable transport functions shared across the execution backends consume the
+runtime representation and primitive transport records. They use:
 
 - Direct structured-field access for fixed-size values and metadata.
 - Base and subtype IDs to navigate registered objects.
@@ -136,8 +183,10 @@ primitive transport records. They use:
 
 The layout is fixed for the duration of a prepared run. Transport may update
 allocated values, tally bins, particle banks, and runtime counters, but it
-cannot resize a field or introduce a new model object. Changing the model
-requires a new model compilation and runtime-preparation pass.
+cannot resize a field or introduce a new model object. A Python-only prototype
+may temporarily read or modify external Python state, but that state is not
+part of the portable runtime layout. Changing the prepared MC/DC model requires
+a new model compilation and runtime preparation pass.
 
 Execution Backends
 ------------------
diff --git a/docs/source/developer_guide/index.rst b/docs/source/developer_guide/index.rst
index 5b9b5ab0a..165d43c99 100644
--- a/docs/source/developer_guide/index.rst
+++ b/docs/source/developer_guide/index.rst
@@ -4,18 +4,12 @@
 Developer Guide
 ===============
 
-The Developer Guide explains how MC/DC works internally and how to extend or
-maintain its implementation.
+The Developer Guide explains how MC/DC works internally and how to extend or maintain its implementation.
 
-- Read :doc:`architecture/index` for MC/DC's Python-first design and to follow
-  the model through compilation, runtime preparation, CPU execution, and GPU
-  execution.
-- Read :doc:`extending/index` when adding model fields, registered objects,
-  polymorphic subtypes, or Numba-compatible transport behavior.
-- Read :doc:`documentation/index` when writing or reviewing project
-  documentation.
-- Use the :doc:`../contributing/index` for repository setup, development
-  workflow, testing, and pull-request requirements.
+- Read :doc:`architecture/index` to understand MC/DC's Python-first design and follow a transport model through simulation compilation, runtime preparation, shared transport algorithm, and the available execution modes.
+- Read :doc:`extending/index` when adding model fields, registered objects, polymorphic subtypes, or Numba-compatible transport behavior.
+- Read :doc:`documentation/index` when writing or reviewing project documentation.
+- Use :doc:`../contributing/index` for repository setup, development workflow, testing, and pull-request requirements.
 
 .. toctree::
    :maxdepth: 1

From 979f4a0c9b9fe65af6aa3d43f1b4e4bccaf80401 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 2 Aug 2026 20:36:52 +0700
Subject: [PATCH 081/202] reformat

---
 .../architecture/numba_gpu_execution.rst      |  38 +--
 .../python_first_numba_accelerated_design.rst | 257 ++++++-----------
 .../python_numba_cpu_execution.rst            |  86 ++----
 .../architecture/runtime_data_layout.rst      | 120 +++-----
 .../architecture/simulation_compilation.rst   | 272 +++++++-----------
 .../developer_guide/documentation/index.rst   |  14 +-
 .../documentation/philosophy.rst              |  57 ++--
 .../developer_guide/documentation/sphinx.rst  |  67 ++---
 .../extending/extending_the_object_model.rst  | 215 +++++---------
 .../developer_guide/extending/index.rst       |  17 +-
 ...riting_numba_compatible_transport_code.rst | 200 +++++--------
 11 files changed, 497 insertions(+), 846 deletions(-)

diff --git a/docs/source/developer_guide/architecture/numba_gpu_execution.rst b/docs/source/developer_guide/architecture/numba_gpu_execution.rst
index 1ea36eb12..27c879b4c 100644
--- a/docs/source/developer_guide/architecture/numba_gpu_execution.rst
+++ b/docs/source/developer_guide/architecture/numba_gpu_execution.rst
@@ -4,22 +4,18 @@
 Numba-GPU Execution
 ===================
 
-GPU execution is the final layer in MC/DC's execution model. MC/DC first
-compiles the Python model and creates the same logical runtime representation
-used on the CPU. It then adapts the transport functions for device execution,
-allocates or transfers runtime state, and uses Harmonize to schedule particle
-work.
+GPU execution is the final layer in MC/DC's execution model.
+MC/DC first compiles the Python model and creates the same logical runtime representation used on the CPU.
+It then adapts the transport functions for device execution, allocates or transfers runtime state, and uses Harmonize to schedule particle work.
 
-Read :doc:`simulation_compilation`, :doc:`runtime_data_layout`, and
-:doc:`python_numba_cpu_execution` first. This page focuses on the additional
-GPU-specific compilation and runtime machinery.
+Read :doc:`simulation_compilation`, :doc:`runtime_data_layout`, and :doc:`python_numba_cpu_execution` first.
+This page focuses on the additional GPU-specific compilation and runtime machinery.
 
 GPU Compilation
 ---------------
 
-When targeting GPUs, MC/DC functions are just-in-time (JIT) compiled with
-Numba and integrated with Harmonize. A GPU run selects Numba mode and the GPU
-target:
+When targeting GPUs, MC/DC functions are just-in-time (JIT) compiled with Numba and integrated with Harmonize.
+A GPU run selects Numba mode and the GPU target:
 
 .. code-block:: sh
 
@@ -45,10 +41,12 @@ Current versions of Numba come with CUDA operability natively, but this is set t
 
 .. image:: ../../images/developer_guide/architecture/numba_gpu_nvidia_flow.png
    :width: 800
-   :alt: Simple proxy example describing how to compile device functions in Numba-Python with external C++ code for targeting Nvidia GPUs. In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize.
+   :alt: Simple proxy example describing how to compile device functions in Numba-Python with external C++ code for targeting Nvidia GPUs.
+         In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize.
 
 
-Simple proxy example describing how to compile device functions in Numba-Python with external C++ code for targeting Nvidia GPUs. In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize
+Simple proxy example describing how to compile device functions in Numba-Python with external C++ code for targeting Nvidia GPUs.
+In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize
 
 We begin by
 
@@ -56,7 +54,7 @@ We begin by
 #. Compiling PTX to relocatable device code using ``nvcc -rdc=true -dc -arch=<arch> --cudart shared --compiler-options -fPIC add.ptx -o add.o`` where ``-dc`` asks the compiler for device code, ``-rdc`` asks to make that device code relocatable, ``--cudart shared`` asks for shared CUDA runtime libraries and ``-fPIC`` generates position-independent code;
 #. Compiling that relocatable byte code into a library of executable device functions is done with ``nvcc -dlink add.o -arch=<arch> --cudart shared -o device.o --compiler-options -fPIC`` where ``-dlink`` asks the compiler for relocatable device code; and finally
 #. Compiling the C-CUDA file containing the global function and linking with the library of device functions originating from Python with ``nvcc -shared add.o device.o -arch=<arch> --cudart shared``.
-    
+
 
 While the complexity of the functions both from MC/DC (Python) and Harmonize (C++) increases dramatically when moving toward implementation in MC/DC, this compilation strategy remains mostly the same.
 The exact compilation commands Harmonize calls when compiling MC/DC functions can be viewed by setting ``VERBOSE=True`` in ``harmonize/python/config.py``.
@@ -88,21 +86,23 @@ This process is done in LLVM-IR.
 
 .. image:: ../../images/developer_guide/architecture/numba_gpu_amd_flow.png
    :width: 800
-   :alt: Simple proxy example describing how to compile device functions in Numba-HIP with external C++ code to AMD GPU targets. In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize.
+   :alt: Simple proxy example describing how to compile device functions in Numba-HIP with external C++ code to AMD GPU targets.
+         In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize.
 
-Simple proxy example describing how to compile device functions in Numba-HIP with external C++ code to AMD GPU targets. In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize
+Simple proxy example describing how to compile device functions in Numba-HIP with external C++ code to AMD GPU targets.
+In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize
 
 Figure fig:codeclang shows the compilation structure.
 We begin compilation by
 
-#. Compiling C++ source in ``dep.cpp`` to LLVM-IR with host and device code bundled together with ``hipcc -c -fgpu-rdc -S -emit-llvm -o dep.ll -x hip dep.cpp -g`` where ``-fgpu-rdc`` asks the compiler for relocatable device code ``-emit-llvm`` requests the LLVM-IR, ``-c`` only runs preprocess, compile, and assemble steps, and ``-x hip`` specifies that ``dep.cpp`` is HIP code; 
+#. Compiling C++ source in ``dep.cpp`` to LLVM-IR with host and device code bundled together with ``hipcc -c -fgpu-rdc -S -emit-llvm -o dep.ll -x hip dep.cpp -g`` where ``-fgpu-rdc`` asks the compiler for relocatable device code ``-emit-llvm`` requests the LLVM-IR, ``-c`` only runs preprocess, compile, and assemble steps, and ``-x hip`` specifies that ``dep.cpp`` is HIP code;
 #. Unbundling the LLVM-IR:
-    
+
  a. first the device half ``clang-offload-bundler --type=ll --unbundle --input=dep.ll --output=dep_gpu.ll --targets=hip-amdgcn-amd-amdhsa--gfx90a`` where ``amdgcn-amd-amdhsa`` is the LLVM target-tipple and ``gfx90a`` is compiler designation for an MI250X
  b. then the host half ``clang-offload-bundler --type=ll --unbundle --input=dep.ll --output=dep_cpu.ll --targets=host-x86_64-unknown-linux-gnu``; then
 
 #. Compiling device functions from Python source with ``numba.hip.generate_llvmir()`` and place into ``add_one.ll``;
-#. Linking the now unbundled device code in ``dep_gpu.ll`` and the device code from Python in ``add_one.ll`` together with ``llvm-link dep_gpu.ll add_one.ll -S -o dep_gpu_linked.ll``; 
+#. Linking the now unbundled device code in ``dep_gpu.ll`` and the device code from Python in ``add_one.ll`` together with ``llvm-link dep_gpu.ll add_one.ll -S -o dep_gpu_linked.ll``;
 #. Rebundling the now combined Python/C++ device LLVM-IR back to the host LLVM-IR with ``clang-offload-bundler --type=ll --input=dep_gpu_linked.ll --input=dep_cpu.ll --output=dep_bundled.ll --targets=hip-amdgcn-amd-amdhsa--gfx90a, host-x86_64-unknown-linux-gnu``; and finally
 #. Compiling to an executable with ``hipcc -v -fgpu-rdc --hip-link dep_bundled.ll-o program`` where ``--hip-link`` links clang-offload-bundles for HIP
 
diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
index 518b61fc5..fe4731877 100644
--- a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -4,56 +4,40 @@
 Python-First, Numba-Accelerated Design
 ======================================
 
-MC/DC is a Python-based environment for developing Monte Carlo transport
-methods, but large calculations also require compiled performance.
-*Python-first* means that developers can build and validate a method through
-MC/DC's normal Python execution while using the full Python language and
-ecosystem. They can address the requirements of accelerated execution later.
-Numba provides the bridge between these goals—but what is Numba, and why is it
-a good fit for MC/DC?
+MC/DC is a Python-based environment for developing Monte Carlo transport methods, but large calculations also require compiled performance.
+*Python-first* means that developers can build and validate a method through MC/DC's normal Python execution while using the full Python language and ecosystem.
+They can address the requirements of accelerated execution later.
+Numba provides the bridge between these goals—but what is Numba, and why is it a good fit for MC/DC?
 
 What Is Numba?
 --------------
 
-`Numba <https://numba.readthedocs.io/en/stable/user/5minguide.html>`_ is a
-just-in-time (JIT) compiler for numerical Python. It translates compatible
-Python functions into machine code as a calculation runs, allowing MC/DC to
-accelerate Python transport algorithms without maintaining a second
-implementation in a lower-level language.
+`Numba <https://numba.readthedocs.io/en/stable/user/5minguide.html>`_ is a just-in-time (JIT) compiler for numerical Python.
+It translates compatible Python functions into machine code as a calculation runs, allowing MC/DC to accelerate Python transport algorithms without maintaining a second implementation in a lower-level language.
 
-Numba does not support every feature of Python. A prototype in MC/DC Python may
-use the full Python language and ecosystem, but an accelerated implementation
-must express the relevant data and behavior in forms that Numba can compile.
+Numba does not support every feature of Python.
+A prototype in MC/DC Python may use the full Python language and ecosystem, but an accelerated implementation must express the relevant data and behavior in forms that Numba can compile.
 
-MC/DC uses Numba as the bridge between Python development and accelerated
-transport. Its common transport path supports three *execution backends*, or
-environments that run the transport functions:
+MC/DC uses Numba as the bridge between Python development and accelerated transport.
+Its common transport path supports three *execution backends*, or environments that run the transport functions:
 
-- **Python** executes the functions through the interpreter with JIT
-  compilation disabled.
+- **Python** executes the functions through the interpreter with JIT compilation disabled.
 - **Numba-CPU** compiles the functions into machine code for the host CPU.
-- **Numba-GPU** compiles functions for an accelerator, with Harmonize providing
-  the supporting GPU runtime.
+- **Numba-GPU** compiles functions for an accelerator, with Harmonize providing the supporting GPU runtime.
 
 Why MC/DC Uses Numba
 --------------------
 
-Numba lets MC/DC keep its maintained transport algorithms in Python while
-specializing them for the model and hardware used by a calculation. This
-supports several project goals:
+Numba lets MC/DC keep its maintained transport algorithms in Python while specializing them for the model and hardware used by a calculation.
+This supports several project goals:
 
-- New transport methods can begin in the language and scientific ecosystem
-  already used to construct MC/DC models.
-- The Python backend supports unrestricted methods development and ordinary
-  Python debugging within MC/DC's normal model lifecycle.
-- Numba-CPU accelerates those functions without requiring a separate
-  implementation in C, C++, or Fortran.
-- Common transport interfaces provide a shared foundation for CPU and GPU
-  execution, with backend-specific adaptation where the hardware requires it.
+- New transport methods can begin in the language and scientific ecosystem already used to construct MC/DC models.
+- The Python backend supports unrestricted methods development and ordinary Python debugging within MC/DC's normal model lifecycle.
+- Numba-CPU accelerates those functions without requiring a separate implementation in C, C++, or Fortran.
+- Common transport interfaces provide a shared foundation for CPU and GPU execution, with backend-specific adaptation where the hardware requires it.
 
-The choice therefore preserves an expressive starting point while providing a
-path to compiled execution. It also introduces the constraints discussed in
-the remainder of this page.
+The choice therefore preserves an expressive starting point while providing a path to compiled execution.
+It also introduces the constraints discussed in the remainder of this page.
 
 Staged Methods Development
 --------------------------
@@ -61,78 +45,55 @@ Staged Methods Development
 MC/DC Python: Prototyping and Validation
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-A new method can be developed through MC/DC's Python backend. It still follows
-the normal MC/DC path: the user defines a valid model, MC/DC prepares the
-complete model and its numerical execution data, and transport runs through
-the Python interpreter with JIT compilation disabled. The preparation process
-is described in :doc:`simulation_compilation` and
-:doc:`runtime_data_layout`.
-
-Within those minimum requirements, prototype transport code may use arbitrary
-Python objects, module-level global state, manual imports, dynamic dispatch,
-callbacks, hard-coded assumptions, or direct edits to transport routines. It
-may call packages such as SciPy or Matplotlib during transport, perform file
-I/O, or visualize intermediate state. It may also reach beyond MC/DC's prepared
-transport data through ordinary Python mechanisms. These choices are
-acceptable because this stage prioritizes scientific expressiveness and rapid
-validation over performance, encapsulation, dependency discipline, and
-compiler compatibility.
-
-No special prototype framework or service is required. Researchers may use
-the most direct implementation within MC/DC Python that answers the question
-being studied. Prototype-only packages do not need to become MC/DC
-dependencies, and temporary implementation choices are not expected to remain
-in their original form.
-
-This freedom is permission, not a required style. A developer familiar with
-MC/DC and Numba may begin with an implementation already close to the compiled
-form, reducing later porting work without making compiler compatibility a
-requirement for initial exploration. Practical guidance is provided in
-:doc:`../extending/writing_numba_compatible_transport_code`.
+A new method can be developed through MC/DC's Python backend.
+It still follows the normal MC/DC path: the user defines a valid model, MC/DC prepares the complete model and its numerical execution data, and transport runs through the Python interpreter with JIT compilation disabled.
+The preparation process is described in :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
+
+Within those minimum requirements, prototype transport code may use arbitrary Python objects, module-level global state, manual imports, dynamic dispatch, callbacks, hard-coded assumptions, or direct edits to transport routines.
+It may call packages such as SciPy or Matplotlib during transport, perform file I/O, or visualize intermediate state.
+It may also reach beyond MC/DC's prepared transport data through ordinary Python mechanisms.
+These choices are acceptable because this stage prioritizes scientific expressiveness and rapid validation over performance, encapsulation, dependency discipline, and compiler compatibility.
+
+No special prototype framework or service is required.
+Researchers may use the most direct implementation within MC/DC Python that answers the question being studied.
+Prototype-only packages do not need to become MC/DC dependencies, and temporary implementation choices are not expected to remain in their original form.
+
+This freedom is permission, not a required style.
+A developer familiar with MC/DC and Numba may begin with an implementation already close to the compiled form, reducing later porting work without making compiler compatibility a requirement for initial exploration.
+Practical guidance is provided in :doc:`../extending/writing_numba_compatible_transport_code`.
 
 Numba-CPU Compilation
 ^^^^^^^^^^^^^^^^^^^^^
 
-Once the method is verified and larger calculations require more performance,
-it can be adapted for Numba-CPU. Unless the Python implementation was already
-written against the compatible subset, reaching this stage requires deliberate
-porting rather than simply changing an execution option. See
-:doc:`python_numba_cpu_execution` for the execution path and
-:doc:`../extending/writing_numba_compatible_transport_code` for the practical
-porting requirements.
+Once the method is verified and larger calculations require more performance, it can be adapted for Numba-CPU.
+Unless the Python implementation was already written against the compatible subset, reaching this stage requires deliberate porting rather than simply changing an execution option.
+See :doc:`python_numba_cpu_execution` for the execution path and :doc:`../extending/writing_numba_compatible_transport_code` for the practical porting requirements.
 
 Numba-GPU Compilation
 ^^^^^^^^^^^^^^^^^^^^^
 
-GPU execution is a further stage with additional hardware constraints. Some
-code that works with Numba-CPU therefore requires further adaptation before it
-can execute on a GPU. These additional layers are described in
-:doc:`numba_gpu_execution`.
+GPU execution is a further stage with additional hardware constraints.
+Some code that works with Numba-CPU therefore requires further adaptation before it can execute on a GPU.
+These additional layers are described in :doc:`numba_gpu_execution`.
 
 Valid Stopping Points
 ^^^^^^^^^^^^^^^^^^^^^
 
 Each stage can be a useful endpoint:
 
-- **MC/DC Python** is sufficient for prototyping, debugging, and small
-  calculations. Prototype code may use unrestricted Python where needed.
-- **Numba-CPU** is sufficient when compiled CPU performance meets the
-  calculation's needs.
-- **Numba-GPU** provides the final portability stage when accelerator
-  performance is required.
+- **MC/DC Python** is sufficient for prototyping, debugging, and small calculations.
+  Prototype code may use unrestricted Python where needed.
+- **Numba-CPU** is sufficient when compiled CPU performance meets the calculation's needs.
+- **Numba-GPU** provides the final portability stage when accelerator performance is required.
 
-This staged workflow allows researchers to stop when their immediate objective
-has been achieved. A general feature intended to be merged and maintained as
-part of MC/DC, however, must work in MC/DC Python, Numba-CPU, and Numba-GPU
-unless the maintainers explicitly accept and document a backend-specific
-limitation.
+This staged workflow allows researchers to stop when their immediate objective has been achieved.
+A general feature intended to be merged and maintained as part of MC/DC, however, must work in MC/DC Python, Numba-CPU, and Numba-GPU unless the maintainers explicitly accept and document a backend-specific limitation.
 
 The Standard Execution Path
 ---------------------------
 
-Every backend follows MC/DC's standard model and execution path. What changes
-between development stages is how transport runs and which Python features it
-may use:
+Every backend follows MC/DC's standard model and execution path.
+What changes between development stages is how transport runs and which Python features it may use:
 
 .. list-table::
    :header-rows: 1
@@ -157,106 +118,72 @@ may use:
      - HDF5 output and analysis objects
      - Python
 
-Model construction and preparation may use object-oriented interfaces,
-variable-length collections, validation, and other expressive Python features.
-Transport in the Python backend may also use ordinary Python facilities beyond
-the prepared execution data. The accelerated backends require predictable
-numerical data and explicit behavior. See
-:doc:`simulation_compilation` and :doc:`runtime_data_layout` for the two
-preparation stages, then :doc:`python_numba_cpu_execution` and
-:doc:`numba_gpu_execution` for backend execution.
+Model construction and preparation may use object-oriented interfaces, variable-length collections, validation, and other expressive Python features.
+Transport in the Python backend may also use ordinary Python facilities beyond the prepared execution data.
+The accelerated backends require predictable numerical data and explicit behavior.
+See :doc:`simulation_compilation` and :doc:`runtime_data_layout` for the two preparation stages, then :doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution` for backend execution.
 
 Architectural Consequences
 --------------------------
 
-Preparing a method for acceleration narrows the freedom available inside
-transport and has three broad architectural consequences.
+Preparing a method for acceleration narrows the freedom available inside transport and has three broad architectural consequences.
 
-**Flexible models become predictable execution data.** Python objects remain
-the natural way to describe a problem, but accelerated transport operates on a
-numerical representation prepared for one simulation. The transformation is
-covered in :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
+**Flexible models become predictable execution data.**
+Python objects remain the natural way to describe a problem, but accelerated transport operates on a numerical representation prepared for one simulation.
+The transformation is covered in :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
 
-**Transport behavior becomes explicit.** Dynamic Python techniques that are
-useful during prototyping must be expressed in forms the compiler can
-understand when the method is accelerated. Contributor guidance belongs in
-:doc:`../extending/writing_numba_compatible_transport_code` and
-:doc:`../extending/extending_the_object_model`.
+**Transport behavior becomes explicit.**
+Dynamic Python techniques that are useful during prototyping must be expressed in forms the compiler can understand when the method is accelerated.
+Contributor guidance belongs in :doc:`../extending/writing_numba_compatible_transport_code` and :doc:`../extending/extending_the_object_model`.
 
-**CPU and GPU share a portable core.** Common transport algorithms use behavior
-supported by both accelerated targets, while hardware-specific concerns remain
-isolated. The two execution paths are described in
-:doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`.
+**CPU and GPU share a portable core.**
+Common transport algorithms use behavior supported by both accelerated targets, while hardware-specific concerns remain isolated.
+The two execution paths are described in :doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`.
 
 Design Tradeoffs
 ----------------
 
-The staged approach does not eliminate development cost; it defers some of that
-cost until a method has demonstrated enough value to justify acceleration and
-long-term maintenance.
-
-Prototyping through MC/DC Python maximizes scientific expressiveness and
-minimizes the effort required to test an idea. The tradeoff is that parts of
-the Python implementation may need to be redesigned or rewritten for
-Numba-CPU. Beginning with simple numerical data and operations that Numba
-supports can reduce that porting effort, but introduces implementation
-constraints earlier in the research process.
-
-Portability also increases compiler, backend, and validation work. MC/DC
-accepts these costs so that maintained features can share transport logic
-across Python, CPU, and GPU execution rather than becoming separate
-implementations that may drift apart. Practical constraints are covered in
-:doc:`../extending/writing_numba_compatible_transport_code`; backend-specific
-costs are covered in :doc:`python_numba_cpu_execution` and
-:doc:`numba_gpu_execution`.
+The staged approach does not eliminate development cost; it defers some of that cost until a method has demonstrated enough value to justify acceleration and long-term maintenance.
+
+Prototyping through MC/DC Python maximizes scientific expressiveness and minimizes the effort required to test an idea.
+The tradeoff is that parts of the Python implementation may need to be redesigned or rewritten for Numba-CPU.
+Beginning with simple numerical data and operations that Numba supports can reduce that porting effort, but introduces implementation constraints earlier in the research process.
+
+Portability also increases compiler, backend, and validation work.
+MC/DC accepts these costs so that maintained features can share transport logic across Python, CPU, and GPU execution rather than becoming separate implementations that may drift apart.
+Practical constraints are covered in :doc:`../extending/writing_numba_compatible_transport_code`; backend-specific costs are covered in :doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`.
 
 Related Design Choices
 ----------------------
 
-Alternative designs place the boundary between expressiveness and portability
-elsewhere. Requiring Numba compatibility from the beginning would reduce later
-porting but constrain early exploration. Maintaining separate Python and
-optimized solvers would preserve unrestricted Python behavior but duplicate
-transport logic. Handwritten kernels would provide more low-level control but
-split methods development across languages.
-
-MC/DC instead uses staged convergence within its standard execution path. A
-method in MC/DC Python may range from an ad hoc implementation to one that is
-already nearly Numba-compatible. When the method needs compiled performance or
-becomes a maintained MC/DC capability, it converges on common numerical data
-and transport interfaces. This preserves a shared execution path without
-dictating how the Python implementation must begin. The data boundary is
-described in :doc:`runtime_data_layout`; contributor guidance is provided in
-:doc:`../extending/writing_numba_compatible_transport_code`.
+Alternative designs place the boundary between expressiveness and portability elsewhere.
+Requiring Numba compatibility from the beginning would reduce later porting but constrain early exploration.
+Maintaining separate Python and optimized solvers would preserve unrestricted Python behavior but duplicate transport logic.
+Handwritten kernels would provide more low-level control but split methods development across languages.
+
+MC/DC instead uses staged convergence within its standard execution path.
+A method in MC/DC Python may range from an ad hoc implementation to one that is already nearly Numba-compatible.
+When the method needs compiled performance or becomes a maintained MC/DC capability, it converges on common numerical data and transport interfaces.
+This preserves a shared execution path without dictating how the Python implementation must begin.
+The data boundary is described in :doc:`runtime_data_layout`; contributor guidance is provided in :doc:`../extending/writing_numba_compatible_transport_code`.
 
 Future Evolution
 ----------------
 
-The Python-first principle does not require the present implementation to
-remain fixed. Future work should make movement between stages easier without
-narrowing the freedom of prototyping in MC/DC Python.
+The Python-first principle does not require the present implementation to remain fixed.
+Future work should make movement between stages easier without narrowing the freedom of prototyping in MC/DC Python.
 
 Potential improvements fall into three areas:
 
-- **Python-mode flexibility** -- make the active Python model and arbitrary
-  development state easier to reach during Python execution without requiring
-  a formal prototype framework.
-- **Porting assistance** -- provide better tools for inspecting a Python
-  implementation and identifying code that an accelerated backend cannot run.
-- **Execution infrastructure** -- make the creation and ownership of prepared
-  data clearer, and keep hardware-specific behavior separated from the common
-  transport algorithms.
+- **Python-mode flexibility** -- make the active Python model and arbitrary development state easier to reach during Python execution without requiring a formal prototype framework.
+- **Porting assistance** -- provide better tools for inspecting a Python implementation and identifying code that an accelerated backend cannot run.
+- **Execution infrastructure** -- make the creation and ownership of prepared data clearer, and keep hardware-specific behavior separated from the common transport algorithms.
 
-Future changes should preserve the ability to stop at any development stage,
-keep the transition from an MC/DC-Python-only implementation to a portable
-maintained implementation explicit and reviewable, and retain equivalent
-physical behavior across the supported backends of a maintained feature.
+Future changes should preserve the ability to stop at any development stage, keep the transition from an MC/DC-Python-only implementation to a portable maintained implementation explicit and reviewable, and retain equivalent physical behavior across the supported backends of a maintained feature.
 
 Where to Go Next
 ----------------
 
-For model preparation, continue with :doc:`simulation_compilation` and
-:doc:`runtime_data_layout`. For execution, read
-:doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`. Contributors
-implementing a transport change should use
-:doc:`../extending/writing_numba_compatible_transport_code`.
+For model preparation, continue with :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
+For execution, read :doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`.
+Contributors implementing a transport change should use :doc:`../extending/writing_numba_compatible_transport_code`.
diff --git a/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst b/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
index 19326fbb3..a045a9cd9 100644
--- a/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
+++ b/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
@@ -4,15 +4,11 @@
 Python and Numba-CPU Execution
 ==============================
 
-MC/DC uses one transport implementation for both Python and Numba-CPU
-execution. The Python path is the conceptual baseline: it is the easiest mode
-to inspect and debug, and it establishes the behavior that the accelerated
-path preserves.
+MC/DC uses one transport implementation for both Python and Numba-CPU execution.
+The Python path is the conceptual baseline: it is the easiest mode to inspect and debug, and it establishes the behavior that the accelerated path preserves.
 
-Both modes operate on the same packed :doc:`runtime_data_layout` and call the
-same functions under ``mcdc/transport``. The difference is whether Numba
-executes functions decorated with ``@njit`` as ordinary Python functions or
-compiles them for the CPU.
+Both modes operate on the same packed :doc:`runtime_data_layout` and call the same functions under ``mcdc/transport``.
+The difference is whether Numba executes functions decorated with ``@njit`` as ordinary Python functions or compiles them for the CPU.
 
 Shared Preparation
 ------------------
@@ -20,17 +16,12 @@ Shared Preparation
 Before transport begins, both modes follow the same preparation path:
 
 #. :class:`mcdc.Simulation` compiles the reachable Python object graph.
-#. ``mcdc.main.prepare`` derives run-dependent values such as particle-bank
-   sizes and physics-mode selections.
-#. ``mcdc.code_factory`` builds the structured ``simulation`` state and flat
-   ``data`` array.
-#. Generated ``mcdc_get`` and ``mcdc_set`` helpers provide transport-safe
-   access to variable-length fields.
+#. ``mcdc.main.prepare`` derives run-dependent values such as particle-bank sizes and physics-mode selections.
+#. ``mcdc.code_factory`` builds the structured ``simulation`` state and flat ``data`` array.
+#. Generated ``mcdc_get`` and ``mcdc_set`` helpers provide transport-safe access to variable-length fields.
 #. The fixed-source or k-eigenvalue driver calls the transport kernels.
 
-This shared preparation is why Python mode can expose the same data-layout and
-transport behavior as Numba mode without maintaining a separate reference
-implementation.
+This shared preparation is why Python mode can expose the same data-layout and transport behavior as Numba mode without maintaining a separate reference implementation.
 
 .. image:: ../../images/developer_guide/architecture/execution_modes.svg
    :width: 100%
@@ -45,9 +36,8 @@ Python mode is the default:
 
    python input.py --mode=python
 
-In this mode, MC/DC sets ``numba.config.DISABLE_JIT``. Functions decorated with
-``@njit`` therefore execute through Python while retaining the same signatures
-and packed runtime inputs used by accelerated execution.
+In this mode, MC/DC sets ``numba.config.DISABLE_JIT``.
+Functions decorated with ``@njit`` therefore execute through Python while retaining the same signatures and packed runtime inputs used by accelerated execution.
 
 Python mode is best for:
 
@@ -56,36 +46,27 @@ Python mode is best for:
 - Obtaining ordinary Python tracebacks.
 - Running small smoke tests before enabling acceleration.
 
-Python mode does not bypass simulation compilation or runtime packing. It
-bypasses machine-code generation for the CPU transport functions.
+Python mode does not bypass simulation compilation or runtime packing.
+It bypasses machine-code generation for the CPU transport functions.
 
 Python Prototyping
 ^^^^^^^^^^^^^^^^^^
 
-The standard MC/DC Python execution path is also the environment for initial
-methods development. A prototype remains a complete MC/DC calculation and
-does not bypass model compilation, runtime preparation, or transport. Because
-JIT compilation is disabled, its transport code may temporarily access
-arbitrary Python objects or global state, import external packages, perform I/O
-or visualization, and use hard-coded or dynamic behavior.
+The standard MC/DC Python execution path is also the environment for initial methods development.
+A prototype remains a complete MC/DC calculation and does not bypass model compilation, runtime preparation, or transport.
+Because JIT compilation is disabled, its transport code may temporarily access arbitrary Python objects or global state, import external packages, perform I/O or visualization, and use hard-coded or dynamic behavior.
 
-These freedoms do not form a separate execution architecture. Advancing the
-method to Numba-CPU requires adapting the parts used by accelerated transport
-to the packed runtime representation and compiler-compatible interfaces.
+These freedoms do not form a separate execution architecture.
+Advancing the method to Numba-CPU requires adapting the parts used by accelerated transport to the packed runtime representation and compiler-compatible interfaces.
 
 Before Numba Acceleration
 -------------------------
 
-At the transition from an MC/DC-Python-only method to Numba acceleration,
-:doc:`python_first_numba_accelerated_design` is the main conceptual guide. It
-explains why MC/DC converts its flexible Python model into typed runtime data,
-which parts remain shared across execution backends, and which constraints
-follow from supporting Numba-CPU and Numba-GPU.
+At the transition from an MC/DC-Python-only method to Numba acceleration, :doc:`python_first_numba_accelerated_design` is the main conceptual guide.
+It explains why MC/DC converts its flexible Python model into typed runtime data, which parts remain shared across execution backends, and which constraints follow from supporting Numba-CPU and Numba-GPU.
 
-If you have not already read that design page as an overview, read it before
-continuing when developing MC/DC or studying its acceleration architecture.
-Readers who only need the mechanics of the Python and Numba-CPU modes may
-continue directly below.
+If you have not already read that design page as an overview, read it before continuing when developing MC/DC or studying its acceleration architecture.
+Readers who only need the mechanics of the Python and Numba-CPU modes may continue directly below.
 
 Numba-CPU Mode
 --------------
@@ -96,11 +77,9 @@ Numba-CPU mode enables just-in-time compilation:
 
    python input.py --mode=numba
 
-The target defaults to ``cpu``. Numba specializes the shared transport
-functions for the structured simulation dtype, flat data array, particle
-records, and other argument types encountered during execution. The initial
-run therefore includes compilation work; subsequent transport work uses the
-compiled functions.
+The target defaults to ``cpu``.
+Numba specializes the shared transport functions for the structured simulation dtype, flat data array, particle records, and other argument types encountered during execution.
+The initial run therefore includes compilation work; subsequent transport work uses the compiled functions.
 
 The runtime representation is unchanged:
 
@@ -127,23 +106,18 @@ The runtime representation is unchanged:
      - JIT disabled
      - Compiled for CPU
 
-Numba debug mode keeps JIT compilation enabled while adding bounds checking,
-fuller tracebacks, and compiler diagnostics:
+Numba debug mode keeps JIT compilation enabled while adding bounds checking, fuller tracebacks, and compiler diagnostics:
 
 .. code-block:: sh
 
    python input.py --mode=numba_debug
 
-Use the ordinary Python mode first to separate model or algorithm errors from
-Numba typing and compilation errors. For operational commands, MPI execution,
-and caching options, see :doc:`../../user_guide/execution/cpu`. For coding
-rules and a staged verification workflow, see
-:doc:`../extending/writing_numba_compatible_transport_code`.
+Use the ordinary Python mode first to separate model or algorithm errors from Numba typing and compilation errors.
+For operational commands, MPI execution, and caching options, see :doc:`../../user_guide/execution/cpu`.
+For coding rules and a staged verification workflow, see :doc:`../extending/writing_numba_compatible_transport_code`.
 
 From CPU to GPU
 ---------------
 
-Numba-GPU execution retains the same Python model-compilation and runtime-layout
-concepts, then replaces the CPU execution backend with device compilation and
-Harmonize scheduling. Continue with :doc:`numba_gpu_execution` after the
-Python and Numba-CPU paths are clear.
+Numba-GPU execution retains the same Python model-compilation and runtime-layout concepts, then replaces the CPU execution backend with device compilation and Harmonize scheduling.
+Continue with :doc:`numba_gpu_execution` after the Python and Numba-CPU paths are clear.
diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index c1375e616..d0dc939a6 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -4,33 +4,26 @@
 Runtime Data Layout
 ===================
 
-After model compilation has discovered and ordered the Python object graph,
-``mcdc.main.prepare`` creates the runtime representation used by transport.
+After model compilation has discovered and ordered the Python object graph, ``mcdc.main.prepare`` creates the runtime representation used by transport.
 The representation has two complementary parts:
 
 ``simulation``
-   A fixed-layout NumPy structured record containing scalar state, embedded
-   records, typed object collections, fixed-size arrays, and metadata.
+   A fixed-layout NumPy structured record containing scalar state, embedded records, typed object collections, fixed-size arrays, and metadata.
 
 ``data``
-   A contiguous one-dimensional NumPy array containing variable-length
-   numerical payloads and lists of object IDs.
-
-The same logical representation is supplied to Python, Numba-CPU, and
-Numba-GPU execution. It should therefore be understood as MC/DC's transport
-runtime model, not as a separate Numba-only model. During Python-only
-prototyping, transport code may also access arbitrary Python state alongside
-this representation. A method intended for portable, maintained execution must
-express the state required by transport through the prepared representation.
+   A contiguous one-dimensional NumPy array containing variable-length numerical payloads and lists of object IDs.
+
+The same logical representation is supplied to Python, Numba-CPU, and Numba-GPU execution.
+It should therefore be understood as MC/DC's transport runtime model, not as a separate Numba-only model.
+During Python-only prototyping, transport code may also access arbitrary Python state alongside this representation.
+A method intended for portable, maintained execution must express the state required by transport through the prepared representation.
 See :doc:`python_first_numba_accelerated_design` for this development model.
 
 Why Two Structures?
 -------------------
 
-Python model objects may contain arrays whose sizes depend on the problem:
-energy grids, cross sections, mesh boundaries, motion tables, tally filters,
-and many others. Nested Python references and arbitrary array shapes cannot be
-embedded directly in a stable structured dtype.
+Python model objects may contain arrays whose sizes depend on the problem: energy grids, cross sections, mesh boundaries, motion tables, tally filters, and many others.
+Nested Python references and arbitrary array shapes cannot be embedded directly in a stable structured dtype.
 
 MC/DC separates fixed-layout metadata from variable-length values:
 
@@ -41,13 +34,12 @@ MC/DC separates fixed-layout metadata from variable-length values:
 Object Collections
 ^^^^^^^^^^^^^^^^^^
 
-Registered model objects are stored in collections on ``simulation``. The
-figure follows a cell, its boundary surfaces, and a surface-crossing tally.
+Registered model objects are stored in collections on ``simulation``.
+The figure follows a cell, its boundary surfaces, and a surface-crossing tally.
 It demonstrates both forms of runtime collection.
 
-For a non-polymorphic category, an object's simulation-local ID directly
-indexes its collection. A particle's current cell and one of its boundary
-surfaces are therefore retrieved with:
+For a non-polymorphic category, an object's simulation-local ID directly indexes its collection.
+A particle's current cell and one of its boundary surfaces are therefore retrieved with:
 
 .. code-block:: python
 
@@ -55,10 +47,9 @@ surfaces are therefore retrieved with:
    surface_ID = int(mcdc_get.cell.surface_IDs(0, cell, data))
    surface = simulation["surfaces"][surface_ID]
 
-A polymorphic category has both a common base collection and a collection for
-each concrete representation. A surface stores the IDs of the surface-crossing
-tallies attached to it. Each ID first selects a base tally record, whose
-``sub_type`` and ``sub_ID`` identify the concrete surface-crossing record:
+A polymorphic category has both a common base collection and a collection for each concrete representation.
+A surface stores the IDs of the surface-crossing tallies attached to it.
+Each ID first selects a base tally record, whose ``sub_type`` and ``sub_ID`` identify the concrete surface-crossing record:
 
 .. code-block:: python
 
@@ -75,17 +66,14 @@ tallies attached to it. Each ID first selects a base tally record, whose
            tally["sub_ID"]
        ]
 
-The concrete tally record retains ``surface_filter_ID`` and ``cell_filter_ID``,
-connecting it back to the selected surface and cell. All IDs are assigned
-during model compilation and identify objects only within the current
-simulation snapshot. The hierarchy and ID assignment are described in
-:doc:`simulation_compilation`.
+The concrete tally record retains ``surface_filter_ID`` and ``cell_filter_ID``, connecting it back to the selected surface and cell.
+All IDs are assigned during model compilation and identify objects only within the current simulation snapshot.
+The hierarchy and ID assignment are described in :doc:`simulation_compilation`.
 
 Variable-Length Fields
 ^^^^^^^^^^^^^^^^^^^^^^
 
-For a variable-length list such as a cell's boundary surfaces, the cell record
-stores values equivalent to:
+For a variable-length list such as a cell's boundary surfaces, the cell record stores values equivalent to:
 
 .. code-block:: text
 
@@ -98,35 +86,28 @@ and the two surface IDs occupy:
 
    data[120:122]
 
-For multidimensional arrays, annotated shape metadata supplies the strides used
-to reconstruct logical indexing. The payload itself is flattened when packed.
+For multidimensional arrays, annotated shape metadata supplies the strides used to reconstruct logical indexing.
+The payload itself is flattened when packed.
 
 Deriving the Layout
 -------------------
 
-Classes in ``mcdc/object_`` declare their runtime-visible fields with Python
-type annotations. ``generate_numba_layers`` collects those annotations and
-maps them to runtime fields:
+Classes in ``mcdc/object_`` declare their runtime-visible fields with Python type annotations.
+``generate_numba_layers`` collects those annotations and maps them to runtime fields:
 
 - Scalars become scalar structured fields.
 - Fixed-shape annotated arrays are embedded in structured records.
-- Variable-length arrays become ``<field>_offset`` and ``<field>_length``
-  metadata plus values in ``data``.
+- Variable-length arrays become ``<field>_offset`` and ``<field>_length`` metadata plus values in ``data``.
 - Object references become ``<field>_ID`` fields.
-- Lists of object references become ``N_<object>`` and
-  ``<object>_IDs_offset`` metadata plus IDs in ``data``.
-- Members named in a class's ``non_numba`` list are excluded from the packed
-  representation or handled specially.
+- Lists of object references become ``N_<object>`` and ``<object>_IDs_offset`` metadata plus IDs in ``data``.
+- Members named in a class's ``non_numba`` list are excluded from the packed representation or handled specially.
 
 Packing is performed in two passes:
 
-#. Walk the compiled objects to build records and calculate the required
-   ``data`` size.
-#. Allocate ``data`` and walk the objects again to copy flattened payloads into
-   their assigned regions.
+#. Walk the compiled objects to build records and calculate the required ``data`` size.
+#. Allocate ``data`` and walk the objects again to copy flattened payloads into their assigned regions.
 
-The structured ``simulation`` dtype can then be finalized because collection
-sizes, particle-bank sizes, and nested record types are known.
+The structured ``simulation`` dtype can then be finalized because collection sizes, particle-bank sizes, and nested record types are known.
 
 The One-element Container
 -------------------------
@@ -138,18 +119,14 @@ The generated simulation record is stored in a one-element NumPy array:
    simulation_container, data = prepare(simulation_python)
    simulation = simulation_container[0]
 
-The container gives Python, Numba, MPI, and GPU paths a consistent mutable
-reference to the structured state. Transport drivers receive the container and
-``data``; individual kernels generally operate on the record or its nested
-objects.
+The container gives Python, Numba, MPI, and GPU paths a consistent mutable reference to the structured state.
+Transport drivers receive the container and ``data``; individual kernels generally operate on the record or its nested objects.
 
 Generated Access Helpers
 ------------------------
 
-``mcdc.code_factory`` generates modules under ``mcdc/mcdc_get`` and
-``mcdc/mcdc_set`` for variable-length fields. These helpers hide offset and
-stride arithmetic from transport code and remain callable from both Python and
-Numba-compiled functions.
+``mcdc.code_factory`` generates modules under ``mcdc/mcdc_get`` and ``mcdc/mcdc_set`` for variable-length fields.
+These helpers hide offset and stride arithmetic from transport code and remain callable from both Python and Numba-compiled functions.
 
 Conceptually, a generated element getter performs:
 
@@ -159,38 +136,33 @@ Conceptually, a generated element getter performs:
        offset = cell["surface_IDs_offset"]
        return data[offset + index]
 
-Generated helpers also provide operations for complete arrays, final elements,
-chunks, vectors, and multidimensional elements as appropriate. Transport code
-can therefore express logical access such as:
+Generated helpers also provide operations for complete arrays, final elements, chunks, vectors, and multidimensional elements as appropriate.
+Transport code can therefore express logical access such as:
 
 .. code-block:: python
 
    surface_ID = int(mcdc_get.cell.surface_IDs(index, cell, data))
 
-without depending on where that cell's surface IDs happen to reside in
-``data``.
+without depending on where that cell's surface IDs happen to reside in ``data``.
 
 Transport Consumption
 ---------------------
 
-Portable transport functions shared across the execution backends consume the
-runtime representation and primitive transport records. They use:
+Portable transport functions shared across the execution backends consume the runtime representation and primitive transport records.
+They use:
 
 - Direct structured-field access for fixed-size values and metadata.
 - Base and subtype IDs to navigate registered objects.
 - ``mcdc_get`` and ``mcdc_set`` for variable-length values.
 - The same function signatures in Python and Numba-CPU modes.
 
-The layout is fixed for the duration of a prepared run. Transport may update
-allocated values, tally bins, particle banks, and runtime counters, but it
-cannot resize a field or introduce a new model object. A Python-only prototype
-may temporarily read or modify external Python state, but that state is not
-part of the portable runtime layout. Changing the prepared MC/DC model requires
-a new model compilation and runtime preparation pass.
+The layout is fixed for the duration of a prepared run.
+Transport may update allocated values, tally bins, particle banks, and runtime counters, but it cannot resize a field or introduce a new model object.
+A Python-only prototype may temporarily read or modify external Python state, but that state is not part of the portable runtime layout.
+Changing the prepared MC/DC model requires a new model compilation and runtime preparation pass.
 
 Execution Backends
 ------------------
 
-Continue with :doc:`python_numba_cpu_execution` to see how Python mode and
-Numba-CPU mode consume this shared layout. GPU allocation and Harmonize
-integration are described in :doc:`numba_gpu_execution`.
+Continue with :doc:`python_numba_cpu_execution` to see how Python mode and Numba-CPU mode consume this shared layout.
+GPU allocation and Harmonize integration are described in :doc:`numba_gpu_execution`.
diff --git a/docs/source/developer_guide/architecture/simulation_compilation.rst b/docs/source/developer_guide/architecture/simulation_compilation.rst
index 26408d1fd..5752a62e1 100644
--- a/docs/source/developer_guide/architecture/simulation_compilation.rst
+++ b/docs/source/developer_guide/architecture/simulation_compilation.rst
@@ -4,43 +4,29 @@
 Simulation Compilation
 ======================
 
-MC/DC begins with normal Python objects. Materials, surfaces, cells, sources,
-tallies, settings, and techniques can contain nested references and
-arbitrary-sized arrays. A :class:`mcdc.Simulation` owns the roots of one model
-and turns that connected object graph into a deterministic, simulation-local
-snapshot.
+MC/DC begins with normal Python objects.
+Materials, surfaces, cells, sources, tallies, settings, and techniques can contain nested references and arbitrary-sized arrays.
+A :class:`mcdc.Simulation` owns the roots of one model and turns that connected object graph into a deterministic, simulation-local snapshot.
 
-This first compilation stage is entirely a Python operation. It establishes
-the model that later runtime preparation will pack for Python, Numba-CPU, or
-Numba-GPU execution.
+This first compilation stage is entirely a Python operation.
+It establishes the model that later runtime preparation will pack for Python, Numba-CPU, or Numba-GPU execution.
 
 Why a Simulation Context Is Needed
 ----------------------------------
 
-A Monte Carlo transport model is a connected system rather than a collection
-of independent definitions. A cell is not complete without its bounding
-surfaces and fill; a material may depend on nuclides, elements, reactions, and
-their data; and sources and tallies may refer to distributions, meshes, or
-geometry objects. The same object may also be shared by several parts of the
-model.
-
-These relationships are assembled incrementally with ordinary Python
-references. While the model is being built, an individual object cannot know
-its final position among all objects of the same kind, whether another branch
-of the model will refer to it, or which subtype-specific collection will
-contain it. Finalizing each object when it is created would therefore make
-model construction depend on definition order and require process-wide
-registration.
-
-:class:`mcdc.Simulation` provides the owning context for this delayed
-finalization. After the model cells, sources, tallies, settings, and techniques
-have been configured, compilation can inspect the complete reachable object
-graph at once. It registers shared objects only once, resolves relationships
-into simulation-local identifiers, and produces a consistent snapshot for
-runtime preparation.
-
-Here, *context* means the explicit model scope owned by a ``Simulation``
-instance, not a Python ``with`` context manager.
+A Monte Carlo transport model is a connected system rather than a collection of independent definitions.
+A cell is not complete without its bounding surfaces and fill; a material may depend on nuclides, elements, reactions, and their data; and sources and tallies may refer to distributions, meshes, or geometry objects.
+The same object may also be shared by several parts of the model.
+
+These relationships are assembled incrementally with ordinary Python references.
+While the model is being built, an individual object cannot know its final position among all objects of the same kind, whether another branch of the model will refer to it, or which subtype-specific collection will contain it.
+Finalizing each object when it is created would therefore make model construction depend on definition order and require process-wide registration.
+
+:class:`mcdc.Simulation` provides the owning context for this delayed finalization.
+After the model cells, sources, tallies, settings, and techniques have been configured, compilation can inspect the complete reachable object graph at once.
+It registers shared objects only once, resolves relationships into simulation-local identifiers, and produces a consistent snapshot for runtime preparation.
+
+Here, *context* means the explicit model scope owned by a ``Simulation`` instance, not a Python ``with`` context manager.
 
 Terminology
 -----------
@@ -56,18 +42,15 @@ MC/DC uses several related forms of compilation:
      - Primary implementation
    * - Model compilation
      - Discover objects, register them once, and assign local IDs.
-     - ``Simulation.compile`` and
-       ``mcdc/code_factory/python_objects_compiler.py``
+     - ``Simulation.compile`` and ``mcdc/code_factory/python_objects_compiler.py``
    * - Runtime preparation
      - Derive run state and pack the model into ``simulation`` and ``data``.
-     - ``mcdc.main.prepare`` and
-       ``mcdc/code_factory/numba_layers_generator.py``
+     - ``mcdc.main.prepare`` and ``mcdc/code_factory/numba_layers_generator.py``
    * - Backend compilation
      - Compile shared transport functions for a CPU or GPU target.
      - Numba and, for GPUs, Harmonize
 
-Unless otherwise qualified, this page uses *compilation* to mean model
-compilation.
+Unless otherwise qualified, this page uses *compilation* to mean model compilation.
 
 Ownership and Roots
 -------------------
@@ -86,40 +69,31 @@ The setter calls identify the roots of the user model:
 - ``set_model`` places cells in the simulation's root universe.
 - ``set_sources`` retains the sources sampled by transport.
 - ``set_tallies`` retains the requested scoring definitions.
-- Settings and transport techniques are embedded objects already owned by the
-  simulation.
+- Settings and transport techniques are embedded objects already owned by the simulation.
 
-There is no process-wide model singleton. Multiple ``Simulation`` instances can
-be constructed and configured in the same Python process, provided each owns a
-distinct object graph. Model objects are included only when they are reachable
-from a simulation's roots or embedded configuration.
+There is no process-wide model singleton.
+Multiple ``Simulation`` instances can be constructed and configured in the same Python process, provided each owns a distinct object graph.
+Model objects are included only when they are reachable from a simulation's roots or embedded configuration.
 
 Ownership Boundary and Process Model
 ------------------------------------
 
-MC/DC intentionally uses a serial-in-process execution model: one
-``Simulation`` is compiled, prepared, or executed at a time within a Python
-process. A model-object instance belongs to one simulation context.
+MC/DC intentionally uses a serial-in-process execution model: one ``Simulation`` is compiled, prepared, or executed at a time within a Python process.
+A model-object instance belongs to one simulation context.
 
-References may be shared freely within that context. For example, several
-cells may use the same material, and compilation will register that material
-once. The same material instance must not be attached to a second
-``Simulation``. Compilation metadata such as ``compile_ID``, ``ID``, and
-``sub_ID`` is stored on the Python object and describes only its owning
-simulation's current snapshot.
+References may be shared freely within that context.
+For example, several cells may use the same material, and compilation will register that material once.
+The same material instance must not be attached to a second ``Simulation``.
+Compilation metadata such as ``compile_ID``, ``ID``, and ``sub_ID`` is stored on the Python object and describes only its owning simulation's current snapshot.
 
-This ownership rule keeps ordinary model construction and recursive
-compilation lightweight. Applications that need concurrent calculations should
-create an independent model graph in each process and manage those processes
-from an outer Python driver, workflow system, or batch scheduler. Process-level
-orchestration is the supported parallelism boundary for multiple independent
-simulations.
+This ownership rule keeps ordinary model construction and recursive compilation lightweight.
+Applications that need concurrent calculations should create an independent model graph in each process and manage those processes from an outer Python driver, workflow system, or batch scheduler.
+Process-level orchestration is the supported parallelism boundary for multiple independent simulations.
 
 The MC/DC Object Hierarchy
 --------------------------
 
-The classes in ``mcdc/object_/base.py`` give every part of the model a common
-compilation lifecycle:
+The classes in ``mcdc/object_/base.py`` give every part of the model a common compilation lifecycle:
 
 .. code-block:: text
 
@@ -127,153 +101,116 @@ compilation lifecycle:
    └── MCDCObject
        └── MCDCPolymorphic
 
-The distinction between these classes is about identity in a compiled
-simulation. All three can contribute fields to the packed runtime layout, but
-only ``MCDCObject`` and ``MCDCPolymorphic`` instances are registered as
-independently addressable model entities.
+The distinction between these classes is about identity in a compiled simulation.
+All three can contribute fields to the packed runtime layout, but only ``MCDCObject`` and ``MCDCPolymorphic`` instances are registered as independently addressable model entities.
 
 ``MCDCBase``: Embedded State and Traversal
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 ``MCDCBase`` is the foundation for Python-side model and runtime definitions.
-Each subclass declares a ``label`` and type-annotated fields. The annotations
-serve two related purposes:
+Each subclass declares a ``label`` and type-annotated fields.
+The annotations serve two related purposes:
 
 - Assignment validation catches incompatible model values during construction.
-- The Numba-layer generator uses the annotations to derive structured fields,
-  object references, and variable-length data access.
-
-An ``MCDCBase`` instance participates in recursive compilation and carries a
-``compile_ID``, but it does not receive an object ``ID`` or occupy a
-simulation-level registry. This behavior is appropriate for state that belongs
-to a parent rather than representing a separately addressable model entity.
-Examples include ``Simulation``, ``Settings``, transport-technique
-configuration, particle-bank metadata, and GPU metadata.
-``Simulation`` is the special root of this hierarchy: it starts compilation
-and owns the resulting registries instead of being registered in one.
-
-The default compilation method visits object-valued members and lists of
-members recursively. Fields named in ``non_numba`` are excluded from this
-default traversal and packed representation; the owning class handles them
-explicitly when special processing is required.
+- The Numba-layer generator uses the annotations to derive structured fields, object references, and variable-length data access.
+
+An ``MCDCBase`` instance participates in recursive compilation and carries a ``compile_ID``, but it does not receive an object ``ID`` or occupy a simulation-level registry.
+This behavior is appropriate for state that belongs to a parent rather than representing a separately addressable model entity.
+Examples include ``Simulation``, ``Settings``, transport-technique configuration, particle-bank metadata, and GPU metadata.
+``Simulation`` is the special root of this hierarchy: it starts compilation and owns the resulting registries instead of being registered in one.
+
+The default compilation method visits object-valued members and lists of members recursively.
+Fields named in ``non_numba`` are excluded from this default traversal and packed representation; the owning class handles them explicitly when special processing is required.
 
 ``MCDCObject``: Registered Model Entities
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-``MCDCObject`` extends ``MCDCBase`` for entities that must be collected and
-referenced by transport. Examples include cells, surfaces, universes, lattices,
-sources, nuclides, and elements.
+``MCDCObject`` extends ``MCDCBase`` for entities that must be collected and referenced by transport.
+Examples include cells, surfaces, universes, lattices, sources, nuclides, and elements.
 
-When compilation reaches an ``MCDCObject``, ``register_object`` places it in
-the corresponding collection owned by the current ``Simulation`` and assigns
-its simulation-local ``ID``. Registration happens before the object's members
-are traversed. Consequently, another reference to the same Python instance can
-recognize that it is already registered, which both preserves sharing and
-terminates cycles.
+When compilation reaches an ``MCDCObject``, ``register_object`` places it in the corresponding collection owned by the current ``Simulation`` and assigns its simulation-local ``ID``.
+Registration happens before the object's members are traversed.
+Consequently, another reference to the same Python instance can recognize that it is already registered, which both preserves sharing and terminates cycles.
 
-An ``ID`` identifies object position within one compiled simulation; it is not
-a permanent identity belonging to the Python object. Recompiling its owning
-simulation may assign a different ``ID``. Attaching the same object instance to
-another simulation is outside the ownership model.
+An ``ID`` identifies object position within one compiled simulation; it is not a permanent identity belonging to the Python object.
+Recompiling its owning simulation may assign a different ``ID``.
+Attaching the same object instance to another simulation is outside the ownership model.
 
 ``MCDCPolymorphic``: Base and Concrete Representations
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-``MCDCPolymorphic`` extends ``MCDCObject`` for categories with multiple
-runtime representations. Meshes, distributions, tallies, and neutron and
-electron reactions use this pattern. For example, ``Tally`` defines the shared
-tally category, while ``TallySurfaceCrossing``, ``TallyCollision``, and
-``TallyTracklength`` provide estimator-specific representations.
+``MCDCPolymorphic`` extends ``MCDCObject`` for categories with multiple runtime representations.
+Meshes, distributions, tallies, and neutron and electron reactions use this pattern.
+For example, ``Tally`` defines the shared tally category, while ``TallySurfaceCrossing``, ``TallyCollision``, and ``TallyTracklength`` provide estimator-specific representations.
 
-Each concrete polymorphic class declares a ``sub_type`` code. During
-registration, an instance receives two positions:
+Each concrete polymorphic class declares a ``sub_type`` code.
+During registration, an instance receives two positions:
 
 - ``ID`` locates its base record in the heterogeneous category collection.
-- ``sub_ID`` locates its concrete record among objects with the same
-  ``sub_type``.
+- ``sub_ID`` locates its concrete record among objects with the same ``sub_type``.
 
-By convention, the shared category class uses ``sub_type = -1`` and concrete
-subclasses use named integer constants. Their distinct ``label`` values also
-name the corresponding structured layouts and generated accessor modules.
+By convention, the shared category class uses ``sub_type = -1`` and concrete subclasses use named integer constants.
+Their distinct ``label`` values also name the corresponding structured layouts and generated accessor modules.
 
-The packed base record stores ``sub_type`` and ``sub_ID``; the concrete record
-stores ``base_ID``. Transport can therefore move between the common category
-view and the subtype-specific data without retaining Python references or
-depending on Python dynamic dispatch.
+The packed base record stores ``sub_type`` and ``sub_ID``; the concrete record stores ``base_ID``.
+Transport can therefore move between the common category view and the subtype-specific data without retaining Python references or depending on Python dynamic dispatch.
 
-For the implementation steps required to add a field, registered category, or
-polymorphic subtype, see
-:doc:`../extending/extending_the_object_model`.
+For the implementation steps required to add a field, registered category, or polymorphic subtype, see :doc:`../extending/extending_the_object_model`.
 
 Recursive Discovery
 -------------------
 
-``Simulation.compile`` assigns a new ``compile_ID``, clears the previous
-registries, and walks the object graph:
+``Simulation.compile`` assigns a new ``compile_ID``, clears the previous registries, and walks the object graph:
 
 #. Reserved ``None`` representations are registered.
-#. The root universe recursively reaches cells, regions, surfaces, fills,
-   universes, lattices, materials, nuclear data, and distributions.
+#. The root universe recursively reaches cells, regions, surfaces, fills, universes, lattices, materials, nuclear data, and distributions.
 #. Sources and tallies are traversed from their explicit root lists.
 #. Settings, techniques, and their members are traversed from the simulation.
 
-The common lifecycle defined by the object hierarchy makes this traversal
-uniform: embedded ``MCDCBase`` members are visited in place, while
-``MCDCObject`` members are registered before their descendants are explored.
+The common lifecycle defined by the object hierarchy makes this traversal uniform: embedded ``MCDCBase`` members are visited in place, while ``MCDCObject`` members are registered before their descendants are explored.
 
-Discovery follows actual Python references. For example, a root cell reaches
-its region, the region reaches its surfaces, and the cell's fill reaches its
-material or child universe. Users therefore attach root cells rather than
-manually registering every referenced object.
+Discovery follows actual Python references.
+For example, a root cell reaches its region, the region reaches its surfaces, and the cell's fill reaches its material or child universe.
+Users therefore attach root cells rather than manually registering every referenced object.
 
 Deduplication and Cycles
 ------------------------
 
-An object's ``compile_ID`` records the compilation snapshot in which it most
-recently participated. When the traversal reaches the same object again during
-that snapshot, registration stops for that branch.
+An object's ``compile_ID`` records the compilation snapshot in which it most recently participated.
+When the traversal reaches the same object again during that snapshot, registration stops for that branch.
 
 This behavior has two purposes:
 
-- A material, surface, mesh, or other object shared in several places is
-  registered once.
-- Cycles among embedded configuration objects do not cause infinite
-  recursion.
+- A material, surface, mesh, or other object shared in several places is registered once.
+- Cycles among embedded configuration objects do not cause infinite recursion.
 
-Deduplication is based on Python object identity within one compilation, not on
-equal field values. Two separately constructed materials with identical cross
-sections remain two objects unless a class performs its own canonicalization.
+Deduplication is based on Python object identity within one compilation, not on equal field values.
+Two separately constructed materials with identical cross sections remain two objects unless a class performs its own canonicalization.
 
 Simulation-local IDs
 --------------------
 
-Registered objects receive identifiers that are meaningful only within the
-current compiled simulation:
+Registered objects receive identifiers that are meaningful only within the current compiled simulation:
 
 ``ID``
-   Position in the corresponding simulation collection, such as all surfaces
-   or all materials.
+   Position in the corresponding simulation collection, such as all surfaces or all materials.
 
 ``sub_type``
-   Integer code identifying the concrete representation of a polymorphic
-   object, such as a surface-crossing, collision, or track-length tally.
+   Integer code identifying the concrete representation of a polymorphic object, such as a surface-crossing, collision, or track-length tally.
 
 ``sub_ID``
    Position in the collection for that concrete subtype.
 
-The packed child record also carries ``base_ID`` so transport can move between
-the subtype-specific and base representations.
+The packed child record also carries ``base_ID`` so transport can move between the subtype-specific and base representations.
 
-For example, transport can inspect a tally base record's ``sub_type`` and
-``sub_ID`` and then select its estimator-specific record. These IDs replace
-Python object references in the runtime layer.
+For example, transport can inspect a tally base record's ``sub_type`` and ``sub_ID`` and then select its estimator-specific record.
+These IDs replace Python object references in the runtime layer.
 
 Snapshot Lifecycle
 ------------------
 
-``set_model``, ``set_sources``, and ``set_tallies`` invalidate the compiled
-state. ``run`` and ``visualize_model`` call ``compile`` automatically when the
-simulation is not compiled, so most user inputs do not need an explicit call.
+``set_model``, ``set_sources``, and ``set_tallies`` invalidate the compiled state.
+``run`` and ``visualize_model`` call ``compile`` automatically when the simulation is not compiled, so most user inputs do not need an explicit call.
 
 An explicit call is useful for inspecting discovered objects and assigned IDs:
 
@@ -285,21 +222,18 @@ An explicit call is useful for inspecting discovered objects and assigned IDs:
    print(source_cell.ID)
    print(source_region_material.ID)
 
-IDs can change whenever the simulation is compiled again. They must not be
-stored as durable identifiers outside the current snapshot.
+IDs can change whenever the simulation is compiled again.
+They must not be stored as durable identifiers outside the current snapshot.
 
-Directly mutating an already attached object does not notify its owning
-simulation. After such a change to an explicitly compiled or visualized model,
-call ``simulation.compile()`` again before inspecting or visualizing the new
-snapshot. ``simulation.run()`` marks the snapshot uncompiled after execution,
-so a subsequent run recompiles it.
+Directly mutating an already attached object does not notify its owning simulation.
+After such a change to an explicitly compiled or visualized model, call ``simulation.compile()`` again before inspecting or visualizing the new snapshot.
+``simulation.run()`` marks the snapshot uncompiled after execution, so a subsequent run recompiles it.
 
 Iterative Partial Updates
 ^^^^^^^^^^^^^^^^^^^^^^^^^
 
-An iterative study can keep one simulation and change only part of its owned
-model between runs. For example, two sources can be reweighted while the
-geometry, materials, and tallies remain unchanged:
+An iterative study can keep one simulation and change only part of its owned model between runs.
+For example, two sources can be reweighted while the geometry, materials, and tallies remain unchanged:
 
 .. code-block:: python
 
@@ -313,19 +247,15 @@ geometry, materials, and tallies remain unchanged:
        simulation.compile()
        simulation.run()
 
-Each call to ``compile`` assigns a new ``compile_ID`` and rebuilds a complete,
-consistent snapshot even though only the source probabilities changed. The
-objects remain owned by the same ``Simulation`` throughout the study.
-See :ref:`example_iterative_source_reweighting` for a complete executable
-example and comparison script.
+Each call to ``compile`` assigns a new ``compile_ID`` and rebuilds a complete, consistent snapshot even though only the source probabilities changed.
+The objects remain owned by the same ``Simulation`` throughout the study.
+See :ref:`example_iterative_source_reweighting` for a complete executable example and comparison script.
 
 From Objects to Runtime Data
 ----------------------------
 
-Model compilation leaves the original Python objects intact and populates the
-simulation's ordered registries. Runtime preparation then reads those objects,
-derives structured dtypes from their annotations, and packs their values.
+Model compilation leaves the original Python objects intact and populates the simulation's ordered registries.
+Runtime preparation then reads those objects, derives structured dtypes from their annotations, and packs their values.
 
-Continue with :doc:`runtime_data_layout` for that conversion. For the
-user-facing construct-to-output workflow, see
-:doc:`../../user_guide/simulation_lifecycle`.
+Continue with :doc:`runtime_data_layout` for that conversion.
+For the user-facing construct-to-output workflow, see :doc:`../../user_guide/simulation_lifecycle`.
diff --git a/docs/source/developer_guide/documentation/index.rst b/docs/source/developer_guide/documentation/index.rst
index 9dfd789e0..cfb758bf9 100644
--- a/docs/source/developer_guide/documentation/index.rst
+++ b/docs/source/developer_guide/documentation/index.rst
@@ -3,17 +3,13 @@
 Documentation
 =============
 
-High-quality documentation is an essential part of MC/DC. Clear documentation
-helps users perform simulations, enables method developers to understand and
-extend computational methods, and assists framework developers in maintaining
-and evolving the software.
+High-quality documentation is an essential part of MC/DC.
+Clear documentation helps users perform simulations, enables method developers to understand and extend computational methods, and assists framework developers in maintaining and evolving the software.
 
-This section explains both the philosophy behind MC/DC's documentation and the
-tools used to build it.
+This section explains both the philosophy behind MC/DC's documentation and the tools used to build it.
 
-Read :doc:`philosophy` when deciding what information belongs in a page and how
-to layer it for different audiences. Read :doc:`sphinx` for source layout,
-reStructuredText, API generation, and local build instructions.
+Read :doc:`philosophy` when deciding what information belongs in a page and how to layer it for different audiences.
+Read :doc:`sphinx` for source layout, reStructuredText, API generation, and local build instructions.
 
 .. toctree::
    :maxdepth: 1
diff --git a/docs/source/developer_guide/documentation/philosophy.rst b/docs/source/developer_guide/documentation/philosophy.rst
index 52ebecdd1..c3a8834b8 100644
--- a/docs/source/developer_guide/documentation/philosophy.rst
+++ b/docs/source/developer_guide/documentation/philosophy.rst
@@ -7,31 +7,24 @@ Documentation Philosophy
 Vision
 ------
 
-The MC/DC documentation should serve the diverse community that develops and
-uses the project. As MC/DC continues to grow, its documentation should be as
-scalable and maintainable as its software architecture.
+The MC/DC documentation should serve the diverse community that develops and uses the project.
+As MC/DC continues to grow, its documentation should be as scalable and maintainable as its software architecture.
 
-MC/DC adopts a layered documentation philosophy that balances usability,
-technical depth, and long-term maintainability across the entire project.
+MC/DC adopts a layered documentation philosophy that balances usability, technical depth, and long-term maintainability across the entire project.
 
-This philosophy applies to all forms of MC/DC documentation, including Getting
-Started, the User Guide, Examples, Theory and Methods, Reference, the Developer
-Guide, Contributing, the README, and API docstrings.
+This philosophy applies to all forms of MC/DC documentation, including Getting Started, the User Guide, Examples, Theory and Methods, Reference, the Developer Guide, Contributing, the README, and API docstrings.
 
 The Layered Documentation Philosophy
 ------------------------------------
 
-MC/DC documentation is written for three complementary audiences. Rather than
-maintaining separate documentation for each audience, individual documents
-should progressively layer information from high-level usage to mathematical
-concepts and implementation details. Readers can naturally stop at the level of
-detail appropriate for their needs.
+MC/DC documentation is written for three complementary audiences.
+Rather than maintaining separate documentation for each audience, individual documents should progressively layer information from high-level usage to mathematical concepts and implementation details.
+Readers can naturally stop at the level of detail appropriate for their needs.
 
 Users
 ^^^^^
 
-Users build geometry, define materials and sources, configure simulations,
-execute transport calculations, and analyze results.
+Users build geometry, define materials and sources, configure simulations, execute transport calculations, and analyze results.
 
 Documentation for users should emphasize:
 
@@ -43,8 +36,7 @@ Documentation for users should emphasize:
 Method Developers
 ^^^^^^^^^^^^^^^^^
 
-Method Developers use MC/DC as a platform for developing and evaluating new
-transport methods and computational algorithms.
+Method Developers use MC/DC as a platform for developing and evaluating new transport methods and computational algorithms.
 
 Documentation for Method Developers should explain:
 
@@ -74,8 +66,7 @@ Documentation for Framework Developers should describe:
 Guiding Principles
 ------------------
 
-Documentation should naturally progress from high-level concepts toward
-implementation details.
+Documentation should naturally progress from high-level concepts toward implementation details.
 
 A typical progression is:
 
@@ -85,27 +76,21 @@ A typical progression is:
 #. Mathematical concepts
 #. Implementation notes
 
-Not every document requires every section. However, documentation should
-generally present information in this order so that each audience can stop
-reading once they have reached the level of detail they need.
+Not every document requires every section.
+However, documentation should generally present information in this order so that each audience can stop reading once they have reached the level of detail they need.
 
-Public behavior should be described before mathematical representation, and
-mathematical representation should be described before implementation details.
+Public behavior should be described before mathematical representation, and mathematical representation should be described before implementation details.
 
 API Docstrings
 --------------
 
-API docstrings should follow the same layered philosophy. In general:
+API docstrings should follow the same layered philosophy.
+In general:
 
-- The opening description should explain the public purpose of the object,
-  function, or module.
-- Parameters, return values, attributes, and examples should focus on the
-  public interface.
-- Mathematical representations, algorithms, and design rationale should be
-  documented in the ``Notes`` section when they help Method Developers.
-- Framework-specific implementation details should be documented separately as
-  implementation notes when appropriate.
+- The opening description should explain the public purpose of the object, function, or module.
+- Parameters, return values, attributes, and examples should focus on the public interface.
+- Mathematical representations, algorithms, and design rationale should be documented in the ``Notes`` section when they help Method Developers.
+- Framework-specific implementation details should be documented separately as implementation notes when appropriate.
 
-Not every API requires all of these sections. The goal is to provide each
-audience with the information it needs while keeping the documentation clear,
-progressive, and easy to navigate.
+Not every API requires all of these sections.
+The goal is to provide each audience with the information it needs while keeping the documentation clear, progressive, and easy to navigate.
diff --git a/docs/source/developer_guide/documentation/sphinx.rst b/docs/source/developer_guide/documentation/sphinx.rst
index 2750a8a3d..b56d02c61 100644
--- a/docs/source/developer_guide/documentation/sphinx.rst
+++ b/docs/source/developer_guide/documentation/sphinx.rst
@@ -5,13 +5,9 @@
 Sphinx and Read the Docs
 ========================
 
-MC/DC uses `Sphinx <https://www.sphinx-doc.org/>`_ to generate its
-documentation and `Read the Docs <https://about.readthedocs.com/>`_ to build
-and host the documentation website.
+MC/DC uses `Sphinx <https://www.sphinx-doc.org/>`_ to generate its documentation and `Read the Docs <https://about.readthedocs.com/>`_ to build and host the documentation website.
 
-This page introduces the subset of Sphinx needed to contribute to MC/DC's
-documentation, including reStructuredText, document organization, automatic API
-generation, and local documentation builds.
+This page introduces the subset of Sphinx needed to contribute to MC/DC's documentation, including reStructuredText, document organization, automatic API generation, and local documentation builds.
 
 
 reStructuredText and Sphinx
@@ -19,18 +15,17 @@ reStructuredText and Sphinx
 
 We write files for Sphinx using a plaintext markup language called reStructuredText (rst).
 `Click here for a rst Primer <https://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html>`_.
-Sphinx builds an html file for every rst file in the documentation root directory and its subdirectories our documentation root directory is ``mcdc/docs/source/``. 
-The root document, ``index.rst``, serves as the welcome page. 
-The root directory also contains task-oriented sections, each with an
-``index.rst`` landing page and related topic pages.
+Sphinx builds an html file for every rst file in the documentation root directory and its subdirectories our documentation root directory is ``mcdc/docs/source/``.
+The root document, ``index.rst``, serves as the welcome page.
+The root directory also contains task-oriented sections, each with an ``index.rst`` landing page and related topic pages.
 It's useful to compare our rst files to their associated webpages to get a feel for how they translate.
 
 
 Like any plaintext markup language, rst uses "explicit markup" for constructs that need special handling, such as including a code-block or cross-referencing other pages.
- 
+
 A block of explicit markup text starts with ".. " and is terminated by the next paragraph at the same level of indentation.
 
-Sphinx creates webpage elements using explicit markup blocks called directives. 
+Sphinx creates webpage elements using explicit markup blocks called directives.
 
 .. tip::
    For example, this block was created using the `tip` directive!
@@ -40,18 +35,17 @@ Sphinx creates webpage elements using explicit markup blocks called directives.
   .. tip::
      For example, this block was created using the `tip` directive!
 
-An explicit markup block without a directive is taken as a comment that will not appear on the webpage:
-::
+An explicit markup block without a directive is taken as a comment that will not appear on the webpage: ::
 
   .. For example, this is a comment.
 
-In addition to directives for blocks of explicit markup, Sphinx handles in-line explicit markup with roles. 
+In addition to directives for blocks of explicit markup, Sphinx handles in-line explicit markup with roles.
 For example, this equation :math:`a^2 + b^2 = c^2` was created using the `math` role.
 ::
 
   For example, this equation :math:`a^2 + b^2 = c^2` was created using the `math` role.
 
-`Click here for a list of Sphinx directives <https://www.sphinx-doc.org/en/master/usage/restructuredtext/directives.html>`_ and `click here for a list of Sphinx roles <https://www.sphinx-doc.org/en/master/usage/restructuredtext/roles.html>`_. 
+`Click here for a list of Sphinx directives <https://www.sphinx-doc.org/en/master/usage/restructuredtext/directives.html>`_ and `click here for a list of Sphinx roles <https://www.sphinx-doc.org/en/master/usage/restructuredtext/roles.html>`_.
 
 
 The toctree
@@ -59,9 +53,7 @@ The toctree
 
 Sphinx's main directive is the `toctree` directive, which generates a table of contents tree (toctree) with links to other webpages in the build.
 The listed documents should be named relative to the current document and excluding the .rst extension.
-For example, the following on ``index.rst`` creates a table of contents on the
-main page with links to the main user-facing sections:
-::
+For example, the following on ``index.rst`` creates a table of contents on the main page with links to the main user-facing sections: ::
 
   .. toctree::
      user_guide/index
@@ -79,56 +71,47 @@ Within MC/DC's source code, we document functions and classes using docstrings.
 `We use two Sphinx extensions <https://romanvm.pythonanywhere.com/post/autodocumenting-your-python-code-sphinx-part-ii-6/>`_ -- ``autodoc`` and ``autosummary`` -- to generate rst files for Sphinx using the existing docstrings in our source code.
 For ``autodoc`` and ``autosummary`` to work, the docstrings within MC/DC's source code must be written in correct rst.
 
-The ``autodoc`` extension includes a set of directives to document different chunks of code (e.g., modules, functions, classes). 
-For example, below is the entire rst file that generates the
-:doc:`../../reference/python_api/generated/mcdc.MaterialMG` page:
+The ``autodoc`` extension includes a set of directives to document different chunks of code (e.g., modules, functions, classes).
+For example, below is the entire rst file that generates the :doc:`../../reference/python_api/generated/mcdc.MaterialMG` page:
 
 .. code-block::
-   
+
    mcdc.MaterialMG
    ===============
-   
+
    .. currentmodule:: mcdc
-   
+
    .. autoclass:: MaterialMG
 
-(That in-line reference was created using
-:code:`:doc:\`../../reference/python_api/generated/mcdc.MaterialMG\``, by the
-way).
+(That in-line reference was created using :code:`:doc:\`../../reference/python_api/generated/mcdc.MaterialMG\``, by the way).
 
 A rst file with an ``autodoc`` directive is required for each module or function that we would like to document.
 Rather than create all of these rst files by hand, we use the ``autosummary`` extension to do it for us.
 
-For example, consider the first ``autosummary`` directive in
-``source/reference/python_api/index.rst``, the file that governs the
-:doc:`../../reference/python_api/index` page:
+For example, consider the first ``autosummary`` directive in ``source/reference/python_api/index.rst``, the file that governs the :doc:`../../reference/python_api/index` page:
 
 .. code-block::
 
    .. autosummary::
-      
+
       mcdc.Material
       mcdc.MaterialMG
 
 This directive:
-  #. Generates two files in ``reference/python_api/generated/``:
-     ``mcdc.Material.rst`` and ``mcdc.MaterialMG.rst``.
+  #. Generates two files in ``reference/python_api/generated/``: ``mcdc.Material.rst`` and ``mcdc.MaterialMG.rst``.
   #. Populates each file with the proper autoclass directive.
-  #. Creates a table on :doc:`../../reference/python_api/index` with entries
-     mcdc.Material and mcdc.MaterialMG that link to the respective generated
-     pages.
+  #. Creates a table on :doc:`../../reference/python_api/index` with entries mcdc.Material and mcdc.MaterialMG that link to the respective generated pages.
 
 
 Building Locally
 ----------------
 
-We can check our work with a local build. 
+We can check our work with a local build.
 Make sure you're in ``mcdc/docs/``:
 
 #. Both Sphinx and the PyData Sphinx Theme should have been installed with MC/DC.
    To check, type ``sphinx-build --version`` on the commandline.
-   If they are not installed, run ``pip install -e ".[docs]"`` from the
-   repository root.
+   If they are not installed, run ``pip install -e ".[docs]"`` from the repository root.
 #. With Sphinx installed, run ``make html``.
    This builds local html files in ``mcdc/docs/build/``.
 #. To launch your local html from the commandline, ``open build/html/index.html``.
@@ -143,8 +126,8 @@ Make sure you're in ``mcdc/docs/``:
    However, this *WILL* cause issues with our documentation website host, readthedocs.
    Like you just did, readthedocs will checkout our repo and use Sphinx to build html files from our rst files, attempting to import all of MC/DC's packages along the way.
    There are some python packages, like ``mpi4py``, that readthedocs is unable to import, causing the documentation build to fail.
-   
-   **If you've added any new package imports to MC/DC's source code, add them to the** ``MOCK_MODULES`` **list in** ``mcdc/docs/source/conf.py``. 
+
+   **If you've added any new package imports to MC/DC's source code, add them to the** ``MOCK_MODULES`` **list in** ``mcdc/docs/source/conf.py``.
 
    This will allow readthedocs to get past the imports without issue.
 
diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index 4768f2187..bda8967d8 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -4,19 +4,13 @@
 Extending the Object Model
 ==========================
 
-MC/DC extensions normally begin as ordinary Python model objects, but an
-extension is complete only when its state and behavior are available in every
-required execution mode. This page describes how to extend the object model
-without breaking simulation-local compilation or the generated runtime layout.
+MC/DC extensions normally begin as ordinary Python model objects, but an extension is complete only when its state and behavior are available in every required execution mode.
+This page describes how to extend the object model without breaking simulation-local compilation or the generated runtime layout.
 
-Read :doc:`../architecture/simulation_compilation` first for the
-``MCDCBase``--``MCDCObject``--``MCDCPolymorphic`` hierarchy. Read
-:doc:`../architecture/runtime_data_layout` for the structured ``simulation``
-record, flat ``data`` array, and generated accessors.
+Read :doc:`../architecture/simulation_compilation` first for the ``MCDCBase``--``MCDCObject``--``MCDCPolymorphic`` hierarchy.
+Read :doc:`../architecture/runtime_data_layout` for the structured ``simulation`` record, flat ``data`` array, and generated accessors.
 
-When the new state is consumed during particle transport, continue with
-:doc:`writing_numba_compatible_transport_code` for type, dispatch, allocation,
-CPU/GPU compatibility, and verification guidance.
+When the new state is consumed during particle transport, continue with :doc:`writing_numba_compatible_transport_code` for type, dispatch, allocation, CPU/GPU compatibility, and verification guidance.
 
 Choose the Extension Type
 -------------------------
@@ -32,64 +26,48 @@ Choose the narrowest extension that represents the new concept:
      - Use when
    * - Add a field
      - Existing class
-     - The concept already belongs to an existing model or configuration
-       object.
+     - The concept already belongs to an existing model or configuration object.
    * - Add embedded state
      - ``MCDCBase``
-     - The state belongs to one parent and does not need an independently
-       addressable entry in a simulation registry.
+     - The state belongs to one parent and does not need an independently addressable entry in a simulation registry.
    * - Add a registered category
      - ``MCDCObject``
-     - Transport must refer to independently registered instances by
-       simulation-local ``ID``.
+     - Transport must refer to independently registered instances by simulation-local ``ID``.
    * - Add a representation to an existing category
      - ``MCDCPolymorphic``
-     - The extension shares a category interface but needs a distinct packed
-       layout and dispatch code.
+     - The extension shares a category interface but needs a distinct packed layout and dispatch code.
 
-Prefer adding a subtype to an existing polymorphic family over creating a new
-registered category when the new object has the same conceptual role. A new
-tally estimator, for example, belongs under ``Tally``; it does not need an
-unrelated top-level registry.
+Prefer adding a subtype to an existing polymorphic family over creating a new registered category when the new object has the same conceptual role.
+A new tally estimator, for example, belongs under ``Tally``; it does not need an unrelated top-level registry.
 
 The Common Class Contract
 -------------------------
 
-Every MC/DC model class must follow the conventions used by the compiler and
-Numba-layer generator.
+Every MC/DC model class must follow the conventions used by the compiler and Numba-layer generator.
 
 ``label``
-   Provide a unique, stable, lower-case label such as ``structured_mesh``. The
-   label names generated structured layouts and the corresponding modules
-   under ``mcdc_get`` and ``mcdc_set``.
+   Provide a unique, stable, lower-case label such as ``structured_mesh``.
+   The label names generated structured layouts and the corresponding modules under ``mcdc_get`` and ``mcdc_set``.
 
 Type annotations
-   Annotate every field that must be represented at runtime. Annotations define
-   scalar fields, embedded structures, object-ID references, and
-   variable-length payloads.
+   Annotate every field that must be represented at runtime.
+   Annotations define scalar fields, embedded structures, object-ID references, and variable-length payloads.
 
 Initialization
-   Assign every runtime-visible field a valid initial value. Subclasses of
-   ``MCDCObject`` must call ``super().__init__()`` so ``ID`` is initialized;
-   subclasses of ``MCDCPolymorphic`` must do the same so both ``ID`` and
-   ``sub_ID`` are initialized.
+   Assign every runtime-visible field a valid initial value.
+   Subclasses of ``MCDCObject`` must call ``super().__init__()`` so ``ID`` is initialized; subclasses of ``MCDCPolymorphic`` must do the same so both ``ID`` and ``sub_ID`` are initialized.
 
 ``non_numba``
-   List Python-only fields that should not be traversed or packed
-   automatically. The class must explicitly convert any required information
-   from those fields into annotated runtime-visible fields before packing.
+   List Python-only fields that should not be traversed or packed automatically.
+   The class must explicitly convert any required information from those fields into annotated runtime-visible fields before packing.
 
 Compilation hook
-   Use the inherited ``_compile_into_simulation`` implementation unless the
-   class must canonicalize objects, compile excluded references, or derive
-   fields from assigned object IDs.
+   Use the inherited ``_compile_into_simulation`` implementation unless the class must canonicalize objects, compile excluded references, or derive fields from assigned object IDs.
 
 Ownership boundary
-   Design each model-object instance for one ``Simulation`` context. Reuse the
-   instance within that model when sharing is intentional, but construct a new
-   object graph for another simulation or process. Extension code must not keep
-   process-wide singleton model objects that can be attached to several
-   simulations.
+   Design each model-object instance for one ``Simulation`` context.
+   Reuse the instance within that model when sharing is intentional, but construct a new object graph for another simulation or process.
+   Extension code must not keep process-wide singleton model objects that can be attached to several simulations.
 
 Represent Fields Deliberately
 -----------------------------
@@ -122,34 +100,28 @@ The layer generator interprets annotations according to the field's role:
      - Count and offset to IDs stored in ``data``
      - Generated ID accessor
 
-Use an integer-only shape when an array is always the same size. Use symbolic
-dimensions when a shape depends on the model. Do not store a Python reference
-in transport-visible state; annotate it as an ``MCDCObject`` or polymorphic
-base so the packed layer records an ID.
+Use an integer-only shape when an array is always the same size.
+Use symbolic dimensions when a shape depends on the model.
+Do not store a Python reference in transport-visible state; annotate it as an ``MCDCObject`` or polymorphic base so the packed layer records an ID.
 
 Adding a Field to an Existing Class
 -----------------------------------
 
 #. Add the annotation to the class that owns the concept.
 #. Initialize the field for every construction path.
-#. Decide whether it is fixed-size, variable-length, an embedded
-   ``MCDCBase``, or an ``MCDCObject`` reference.
-#. Update any compile hook that derives the field or converts a Python-only
-   input into its runtime representation.
-#. Consume the field through direct structured access or its generated
-   ``mcdc_get`` and ``mcdc_set`` helpers.
-#. Update the public docstring and API documentation when users can configure
-   the field.
-
-Avoid adding parallel state in several classes. If a value belongs to the
-simulation as a whole, place it in ``Simulation`` or one of its embedded
-configuration objects and pass or access that representation consistently.
+#. Decide whether it is fixed-size, variable-length, an embedded ``MCDCBase``, or an ``MCDCObject`` reference.
+#. Update any compile hook that derives the field or converts a Python-only input into its runtime representation.
+#. Consume the field through direct structured access or its generated ``mcdc_get`` and ``mcdc_set`` helpers.
+#. Update the public docstring and API documentation when users can configure the field.
+
+Avoid adding parallel state in several classes.
+If a value belongs to the simulation as a whole, place it in ``Simulation`` or one of its embedded configuration objects and pass or access that representation consistently.
 
 Adding Embedded ``MCDCBase`` State
 ----------------------------------
 
-Use ``MCDCBase`` for configuration or runtime state that is owned by one
-parent. A minimal class has a label, annotated fields, and initialized values:
+Use ``MCDCBase`` for configuration or runtime state that is owned by one parent.
+A minimal class has a label, annotated fields, and initialized values:
 
 .. code-block:: python
 
@@ -164,58 +136,41 @@ parent. A minimal class has a label, annotated fields, and initialized values:
            self.active = False
            self.strength = 1.0
 
-Add an annotated field for the object to its owner and instantiate it with the
-owner. For simulation-wide configuration, this normally means adding the field
-to ``Simulation`` and constructing it in ``Simulation.__init__``. The embedded
-object participates in recursive compilation but does not require a registry
-branch or object ID.
+Add an annotated field for the object to its owner and instantiate it with the owner.
+For simulation-wide configuration, this normally means adding the field to ``Simulation`` and constructing it in ``Simulation.__init__``.
+The embedded object participates in recursive compilation but does not require a registry branch or object ID.
 
 If the embedded object refers to an ``MCDCObject``, annotate that reference.
-The default traversal will register the referenced object when compilation
-reaches the embedded configuration.
+The default traversal will register the referenced object when compilation reaches the embedded configuration.
 
 Adding a New ``MCDCObject`` Category
 ------------------------------------
 
 A genuinely new registered category requires coordinated changes:
 
-#. Define the class with a unique ``label``, annotations, initialized fields,
-   and a call to ``super().__init__()``.
-#. Add the category collection to ``Simulation`` annotations and initialize or
-   reset it in ``Simulation._reset_model``.
-#. Import the category in
-   ``mcdc/code_factory/python_objects_compiler.py`` and add an
-   ``isinstance`` branch in ``register_object`` that selects its simulation
-   collection.
-#. Ensure the object is reachable from an existing simulation root or add an
-   explicit root and compilation step.
-#. Ensure the class's module is imported before
-   ``numba_layers_generator.py`` discovers the classes. A public class is
-   normally imported through ``mcdc/__init__.py``; an internal class must be
-   imported by another module in the compilation path.
+#. Define the class with a unique ``label``, annotations, initialized fields, and a call to ``super().__init__()``.
+#. Add the category collection to ``Simulation`` annotations and initialize or reset it in ``Simulation._reset_model``.
+#. Import the category in ``mcdc/code_factory/python_objects_compiler.py`` and add an ``isinstance`` branch in ``register_object`` that selects its simulation collection.
+#. Ensure the object is reachable from an existing simulation root or add an explicit root and compilation step.
+#. Ensure the class's module is imported before ``numba_layers_generator.py`` discovers the classes.
+   A public class is normally imported through ``mcdc/__init__.py``; an internal class must be imported by another module in the compilation path.
 #. Add the collection and lookup behavior required by transport.
 
-Do not add a fallback registration branch that silently accepts unknown
-objects. An explicit category branch keeps registry ownership and runtime
-layout reviewable.
+Do not add a fallback registration branch that silently accepts unknown objects.
+An explicit category branch keeps registry ownership and runtime layout reviewable.
 
 Adding a Polymorphic Subtype
 ----------------------------
 
-Adding a concrete subtype to an existing family is more localized than adding
-a category:
+Adding a concrete subtype to an existing family is more localized than adding a category:
 
 #. Add a unique integer constant for the subtype.
-#. Inherit from the existing polymorphic base, such as ``MeshBase`` or
-   ``Tally``.
+#. Inherit from the existing polymorphic base, such as ``MeshBase`` or ``Tally``.
 #. Set a unique concrete ``label`` and the new ``sub_type`` constant.
-#. Call the base initializer so shared fields, ``ID``, and ``sub_ID`` are
-   initialized.
+#. Call the base initializer so shared fields, ``ID``, and ``sub_ID`` are initialized.
 #. Annotate and initialize subtype-specific fields.
-#. Import the subtype before layer generation and expose it from
-   ``mcdc/__init__.py`` when it is public.
-#. Add transport dispatch for the new ``sub_type`` and implement the
-   subtype-specific behavior.
+#. Import the subtype before layer generation and expose it from ``mcdc/__init__.py`` when it is public.
+#. Add transport dispatch for the new ``sub_type`` and implement the subtype-specific behavior.
 
 For example, the structural part of a mesh subtype follows this pattern:
 
@@ -231,16 +186,14 @@ For example, the structural part of a mesh subtype follows this pattern:
            super().__init__(name)
            self.boundaries = np.asarray(boundaries, dtype=float64)
 
-No new ``register_object`` branch is needed for a subtype of an already
-registered family. The existing ``isinstance(..., MeshBase)`` or corresponding
-category check places it in the base collection, while ``sub_type`` and
-``sub_ID`` connect it to its concrete packed collection.
+No new ``register_object`` branch is needed for a subtype of an already registered family.
+The existing ``isinstance(..., MeshBase)`` or corresponding category check places it in the base collection, while ``sub_type`` and ``sub_ID`` connect it to its concrete packed collection.
 
 Custom Compilation Hooks
 ------------------------
 
-Override ``_compile_into_simulation`` only when the default recursive traversal
-is insufficient. The common post-registration pattern is:
+Override ``_compile_into_simulation`` only when the default recursive traversal is insufficient.
+The common post-registration pattern is:
 
 .. code-block:: python
 
@@ -252,13 +205,11 @@ is insufficient. The common post-registration pattern is:
        self.runtime_field = self.python_reference.ID
        return True
 
-Calling ``super`` first registers an ``MCDCObject`` and recursively compiles its
-ordinary members. The Boolean return prevents repeated work when the same
-object is reached again.
+Calling ``super`` first registers an ``MCDCObject`` and recursively compiles its ordinary members.
+The Boolean return prevents repeated work when the same object is reached again.
 
 Some classes must canonicalize or replace members before the default traversal.
-In that case, check ``compile_ID`` before doing the work, update the
-runtime-visible members, and then call ``super`` exactly once:
+In that case, check ``compile_ID`` before doing the work, update the runtime-visible members, and then call ``super`` exactly once:
 
 .. code-block:: python
 
@@ -274,26 +225,24 @@ runtime-visible members, and then call ``super`` exactly once:
        self._derive_post_registration_fields()
        return True
 
-Do not assign ``compile_ID``, ``ID``, or ``sub_ID`` manually. The shared
-compiler owns those values.
+Do not assign ``compile_ID``, ``ID``, or ``sub_ID`` manually.
+The shared compiler owns those values.
 
 Generated Runtime Layers and Accessors
 --------------------------------------
 
-``numba_layers_generator.py`` derives the structured dtypes, flat-data
-metadata, and accessor targets from the completed model classes. It writes:
+``numba_layers_generator.py`` derives the structured dtypes, flat-data metadata, and accessor targets from the completed model classes.
+It writes:
 
 - ``mcdc/numba_types.py`` for structured dtype definitions.
 - ``mcdc/mcdc_get/<label>.py`` for generated reads.
 - ``mcdc/mcdc_set/<label>.py`` for generated writes.
-- ``mcdc_get/__init__.py`` and ``mcdc_set/__init__.py`` for generated module
-  imports.
+- ``mcdc_get/__init__.py`` and ``mcdc_set/__init__.py`` for generated module imports.
 
-Do not implement a generated accessor by hand. Express the field correctly in
-the class annotation, prepare a representative simulation, and allow the layer
-generator to regenerate the modules. Then use the generated helper from
-transport code. Fixed-size fields do not need helpers and can be accessed
-directly from the structured record.
+Do not implement a generated accessor by hand.
+Express the field correctly in the class annotation, prepare a representative simulation, and allow the layer generator to regenerate the modules.
+Then use the generated helper from transport code.
+Fixed-size fields do not need helpers and can be accessed directly from the structured record.
 
 Public API and Documentation
 ----------------------------
@@ -301,16 +250,12 @@ Public API and Documentation
 For a user-facing class or constructor:
 
 #. Export the class from ``mcdc/__init__.py``.
-#. Add it to the appropriate autosummary group in
-   ``docs/source/reference/python_api/index.rst``.
-#. Document parameters, units, defaults, constraints, and at least one usable
-   example in the class docstring.
-#. Update the User Guide when the extension changes how users construct or run
-   a model.
+#. Add it to the appropriate autosummary group in ``docs/source/reference/python_api/index.rst``.
+#. Document parameters, units, defaults, constraints, and at least one usable example in the class docstring.
+#. Update the User Guide when the extension changes how users construct or run a model.
 
-Internal helper classes should remain under ``mcdc.object_`` and should not be
-exported merely to make discovery work. Import them explicitly in the
-compilation path instead.
+Internal helper classes should remain under ``mcdc.object_`` and should not be exported merely to make discovery work.
+Import them explicitly in the compilation path instead.
 
 Verification Checklist
 ----------------------
@@ -319,17 +264,13 @@ An object-model extension should verify all affected layers:
 
 - Construction accepts valid input and rejects invalid shapes or types.
 - Compilation discovers the object from the intended root.
-- Shared references register once, and recompilation produces a valid new
-  snapshot.
+- Shared references register once, and recompilation produces a valid new snapshot.
 - Separate simulations use independently constructed model-object instances.
-- Packed fields, object IDs, offsets, and generated accessors contain the
-  expected values.
+- Packed fields, object IDs, offsets, and generated accessors contain the expected values.
 - Python and Numba-CPU modes produce equivalent behavior.
 - GPU execution is covered when the changed transport path supports GPUs.
 - Public examples compile under the example validator when the API changes.
 - API and developer documentation build without warnings.
 
-Add focused unit tests near ``test/unit/test_object_compilation.py`` for
-compilation behavior and near the relevant transport tests for runtime
-behavior. Use :doc:`../../contributing/example_validation` when an extension
-changes public examples.
+Add focused unit tests near ``test/unit/test_object_compilation.py`` for compilation behavior and near the relevant transport tests for runtime behavior.
+Use :doc:`../../contributing/example_validation` when an extension changes public examples.
diff --git a/docs/source/developer_guide/extending/index.rst b/docs/source/developer_guide/extending/index.rst
index 4e62e60d3..96e175715 100644
--- a/docs/source/developer_guide/extending/index.rst
+++ b/docs/source/developer_guide/extending/index.rst
@@ -4,20 +4,13 @@
 Extending MC/DC
 ===============
 
-This section provides implementation-oriented guidance for adding new model
-concepts and transport capabilities to MC/DC. It complements the
-:doc:`../architecture/index`, which explains the existing design, by describing
-the changes an extension must make across the Python model, compilation,
-generated runtime layers, transport implementation, public API, and tests.
+This section provides implementation-oriented guidance for adding new model concepts and transport capabilities to MC/DC.
+It complements the :doc:`../architecture/index`, which explains the existing design, by describing the changes an extension must make across the Python model, compilation, generated runtime layers, transport implementation, public API, and tests.
 
-Start with :doc:`extending_the_object_model` when adding a field to an existing
-model class, introducing simulation-owned configuration, creating a registered
-model-object category, or implementing a new polymorphic subtype. Continue with
-:doc:`writing_numba_compatible_transport_code` when the extension adds or
-changes code executed during particle transport.
+Start with :doc:`extending_the_object_model` when adding a field to an existing model class, introducing simulation-owned configuration, creating a registered model-object category, or implementing a new polymorphic subtype.
+Continue with :doc:`writing_numba_compatible_transport_code` when the extension adds or changes code executed during particle transport.
 
-Use the :doc:`../../contributing/index` for repository setup, test commands,
-continuous-integration coverage, and pull-request requirements.
+Use the :doc:`../../contributing/index` for repository setup, test commands, continuous-integration coverage, and pull-request requirements.
 
 .. toctree::
    :maxdepth: 1
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index 3c3127f8a..b6d7af2d4 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -4,19 +4,14 @@
 Writing Numba-Compatible Transport Code
 =======================================
 
-Maintained transport code in MC/DC is written in Python but may execute as
-Python, Numba-compiled CPU code, or Numba-compiled GPU device code. A method may
-be prototyped within the MC/DC Python backend before it is adapted for the two
-accelerated backends.
+Maintained transport code in MC/DC is written in Python but may execute as Python, Numba-compiled CPU code, or Numba-compiled GPU device code.
+A method may be prototyped within the MC/DC Python backend before it is adapted for the two accelerated backends.
 
-Read :doc:`../architecture/python_first_numba_accelerated_design` first for the
-reason behind this development model. If the change introduces new model
-state, also read :doc:`extending_the_object_model` and
-:doc:`../architecture/runtime_data_layout`.
+Read :doc:`../architecture/python_first_numba_accelerated_design` first for the reason behind this development model.
+If the change introduces new model state, also read :doc:`extending_the_object_model` and :doc:`../architecture/runtime_data_layout`.
 
-The rules below apply when an MC/DC Python prototype is being made portable and
-maintained as part of MC/DC. They are not restrictions on temporary
-Python-only behavior during initial exploration.
+The rules below apply when an MC/DC Python prototype is being made portable and maintained as part of MC/DC.
+They are not restrictions on temporary Python-only behavior during initial exploration.
 
 Choose the Host or Transport Layer
 ----------------------------------
@@ -36,40 +31,29 @@ Place work in transport when it must be performed during particle execution:
 - Sample distributions and update the random-number state.
 - Score tallies or update preallocated banks and counters.
 
-Do as much irregular work as practical before transport. A small amount of
-host-side preparation can turn a dynamic operation into simple indexed access
-inside a frequently called kernel.
+Do as much irregular work as practical before transport.
+A small amount of host-side preparation can turn a dynamic operation into simple indexed access inside a frequently called kernel.
 
 Work Python First
 -----------------
 
-An exploratory method may begin in MC/DC Python, using whichever Python data
-structures make the algorithm easiest to understand and verify. It still runs
-through MC/DC's normal model preparation and transport path. This Python-only
-implementation is a valid stopping point for a small study that does not need
-compiled performance.
-
-At this stage, use module-level global state, arbitrary Python objects, ad hoc
-imports, dynamic behavior, file I/O, callbacks, visualization, hard-coded
-assumptions, or direct transport edits whenever they help answer the research
-question. Calls to packages such as SciPy and Matplotlib are acceptable even
-during transport. A formal prototype service or abstraction is not required.
-
-Keep prototype-only dependencies local to the experiment rather than adding
-them to MC/DC's required dependencies. The prototype is allowed to be
-disposable and is not expected to compile unchanged.
-
-Unrestricted prototyping is optional. A developer already familiar with MC/DC
-and Numba may begin with packed runtime inputs, stable types, and supported
-operations, producing an implementation that is nearly Numba-compatible from
-the start. This can minimize the deliberate porting work while preserving the
-freedom to use ordinary Python whenever it helps establish the method.
-
-Porting for accelerated execution begins by adapting the verified method so
-that the required information and behavior use the packed runtime inputs
-available to transport. Decorate the maintained function with ``@njit`` like
-the surrounding transport functions; in Python mode, MC/DC disables JIT
-compilation and calls the same function as Python.
+An exploratory method may begin in MC/DC Python, using whichever Python data structures make the algorithm easiest to understand and verify.
+It still runs through MC/DC's normal model preparation and transport path.
+This Python-only implementation is a valid stopping point for a small study that does not need compiled performance.
+
+At this stage, use module-level global state, arbitrary Python objects, ad hoc imports, dynamic behavior, file I/O, callbacks, visualization, hard-coded assumptions, or direct transport edits whenever they help answer the research question.
+Calls to packages such as SciPy and Matplotlib are acceptable even during transport.
+A formal prototype service or abstraction is not required.
+
+Keep prototype-only dependencies local to the experiment rather than adding them to MC/DC's required dependencies.
+The prototype is allowed to be disposable and is not expected to compile unchanged.
+
+Unrestricted prototyping is optional.
+A developer already familiar with MC/DC and Numba may begin with packed runtime inputs, stable types, and supported operations, producing an implementation that is nearly Numba-compatible from the start.
+This can minimize the deliberate porting work while preserving the freedom to use ordinary Python whenever it helps establish the method.
+
+Porting for accelerated execution begins by adapting the verified method so that the required information and behavior use the packed runtime inputs available to transport.
+Decorate the maintained function with ``@njit`` like the surrounding transport functions; in Python mode, MC/DC disables JIT compilation and calls the same function as Python.
 
 .. code-block:: python
 
@@ -81,79 +65,67 @@ compilation and calls the same function as Python.
        particle = particle_container[0]
        particle["w"] *= factor
 
-Keep the function small enough that its inputs, outputs, and mutations are
-clear. First exercise it in Python mode to verify the algorithm and obtain an
-ordinary traceback. Then run it in Numba-CPU mode to verify type inference.
-Finally, adapt and validate it for Numba-GPU. Each stage may reveal constraints
-that were irrelevant to the preceding implementation.
+Keep the function small enough that its inputs, outputs, and mutations are clear.
+First exercise it in Python mode to verify the algorithm and obtain an ordinary traceback.
+Then run it in Numba-CPU mode to verify type inference.
+Finally, adapt and validate it for Numba-GPU.
+Each stage may reveal constraints that were irrelevant to the preceding implementation.
 
 Use Runtime Data, Not Model Objects
 -----------------------------------
 
-An integrated transport function should accept scalars, NumPy arrays,
-structured records, one-element record containers, and the packed
-``simulation`` and ``data`` state. It should not accept an ``MCDCObject``
-instance or follow Python object references.
+An integrated transport function should accept scalars, NumPy arrays, structured records, one-element record containers, and the packed ``simulation`` and ``data`` state.
+It should not accept an ``MCDCObject`` instance or follow Python object references.
 
 Use the representation appropriate to each field:
 
 - Read fixed-size values directly from a structured record.
 - Follow registered relationships with their integer IDs.
 - Use ``sub_type`` and ``sub_ID`` for polymorphic dispatch.
-- Use generated ``mcdc_get`` and ``mcdc_set`` helpers for variable-length
-  fields in ``data``.
+- Use generated ``mcdc_get`` and ``mcdc_set`` helpers for variable-length fields in ``data``.
 - Mutate only state allocated during runtime preparation.
 
-If the required value is unavailable in this form, extend the object model and
-generated runtime layer before writing the transport behavior. Do not create a
-parallel Python-only lookup inside the kernel.
+If the required value is unavailable in this form, extend the object model and generated runtime layer before writing the transport behavior.
+Do not create a parallel Python-only lookup inside the kernel.
 
 Keep Types Stable
 -----------------
 
-Numba determines a compiled function's types from its arguments and control
-flow. Make those types unambiguous:
+Numba determines a compiled function's types from its arguments and control flow.
+Make those types unambiguous:
 
 - Initialize local variables on every path before use.
 - Return the same number and compatible types of values from every branch.
-- Avoid changing a variable from a scalar to an array or from an integer to an
-  unrelated object.
-- Use explicit integer and floating-point constants when their width or
-  signedness affects an operation.
-- Keep structured-record field names fixed; do not compute field names at run
-  time.
-- Avoid heterogeneous Python lists, dictionaries, sets, generators, and
-  dynamically created classes in transport.
+- Avoid changing a variable from a scalar to an array or from an integer to an unrelated object.
+- Use explicit integer and floating-point constants when their width or signedness affects an operation.
+- Keep structured-record field names fixed; do not compute field names at run time.
+- Avoid heterogeneous Python lists, dictionaries, sets, generators, and dynamically created classes in transport.
 
 Numba may accept a construct on the CPU without making it available on the GPU.
-When a function is shared, compatibility with the stricter target is the
-relevant standard.
+When a function is shared, compatibility with the stricter target is the relevant standard.
 
 Represent Variable-Length Data Explicitly
 -----------------------------------------
 
-Do not recover variable-length model data by allocating a new Python
-container. Read it from ``data`` using the metadata in its owning record.
+Do not recover variable-length model data by allocating a new Python container.
+Read it from ``data`` using the metadata in its owning record.
 Prefer the generated accessor because it preserves the layout convention:
 
 .. code-block:: python
 
    value = mcdc_get.tally.energy(index, tally, data)
 
-An ``*_all`` or ``*_chunk`` helper may expose a view when an algorithm needs a
-range. Element access is preferable when the kernel only needs one value. Do
-not resize the returned view or retain it beyond the prepared run.
+An ``*_all`` or ``*_chunk`` helper may expose a view when an algorithm needs a range.
+Element access is preferable when the kernel only needs one value.
+Do not resize the returned view or retain it beyond the prepared run.
 
-For a new variable-length field, declare the field on the Python model class
-and regenerate its accessors as described in
-:doc:`extending_the_object_model`. Do not hand-maintain offset arithmetic in
-several transport modules.
+For a new variable-length field, declare the field on the Python model class and regenerate its accessors as described in :doc:`extending_the_object_model`.
+Do not hand-maintain offset arithmetic in several transport modules.
 
 Use Explicit Dispatch
 ---------------------
 
-Dispatch on integer constants through a small interface function rather than
-using Python ``isinstance`` checks or methods on runtime records:
+Dispatch on integer constants through a small interface function rather than using Python ``isinstance`` checks or methods on runtime records:
 
 .. code-block:: python
 
@@ -168,26 +140,19 @@ using Python ``isinstance`` checks or methods on runtime records:
            return concrete["x0"] + index * concrete["dx"]
        return 0.0
 
-Use the actual category interface and constants already defined for that
-family. When adding a subtype, update every exhaustive dispatch site and test
-an unsupported value deliberately if the interface defines fallback behavior.
+Use the actual category interface and constants already defined for that family.
+When adding a subtype, update every exhaustive dispatch site and test an unsupported value deliberately if the interface defines fallback behavior.
 
 Control Allocation and Mutation
 -------------------------------
 
-Particle histories repeatedly execute transport functions, so temporary
-allocation can be both expensive and difficult to support consistently across
-targets.
+Particle histories repeatedly execute transport functions, so temporary allocation can be both expensive and difficult to support consistently across targets.
 
-- Reuse particle containers, banks, tally arrays, and scratch state allocated
-  during preparation.
-- Update structured fields or ``data`` through explicit assignments and
-  generated setters.
-- Prefer scalar calculations or bounded loops over constructing intermediate
-  Python collections.
+- Reuse particle containers, banks, tally arrays, and scratch state allocated during preparation.
+- Update structured fields or ``data`` through explicit assignments and generated setters.
+- Prefer scalar calculations or bounded loops over constructing intermediate Python collections.
 - Do not append a new model entity or change a field's shape during transport.
-- Preserve the one-element container convention when a mutable record must be
-  shared across function boundaries.
+- Preserve the one-element container convention when a mutable record must be shared across function boundaries.
 
 The owner of each mutation should be evident from the function signature.
 Avoid hidden module-level mutable state.
@@ -197,39 +162,29 @@ Stay Within the CPU/GPU Common Subset
 
 For code intended to run on both targets:
 
-- Use numerical control flow and operations already established in nearby
-  shared transport modules.
+- Use numerical control flow and operations already established in nearby shared transport modules.
 - Avoid Python exceptions as ordinary control flow.
-- Keep file access, printing, timing, MPI orchestration, and other host
-  services outside device functions.
+- Keep file access, printing, timing, MPI orchestration, and other host services outside device functions.
 - Do not use Numba ``objmode`` in a path that must execute on the GPU.
-- Avoid relying on a CPU-only Numba feature merely because Numba-CPU compiles
-  it.
-- Keep target-specific atomics, memory operations, and scheduling behind the
-  existing GPU adaptation layer.
+- Avoid relying on a CPU-only Numba feature merely because Numba-CPU compiles it.
+- Keep target-specific atomics, memory operations, and scheduling behind the existing GPU adaptation layer.
 
 Backend-specific code is appropriate when the execution model truly differs.
-Keep the shared numerical operation in ``mcdc/transport`` when possible, and
-put only the required adaptation under ``mcdc/code_factory/gpu``. Document why
-the paths differ and test their physical equivalence.
+Keep the shared numerical operation in ``mcdc/transport`` when possible, and put only the required adaptation under ``mcdc/code_factory/gpu``.
+Document why the paths differ and test their physical equivalence.
 
 Debug in Layers
 ---------------
 
 When a change fails, isolate the layer:
 
-#. **Python construction** -- confirm that the model compiles and the expected
-   objects, IDs, offsets, and data are present.
-#. **Python transport** -- verify the algorithm and state mutation with JIT
-   disabled.
-#. **Numba-CPU** -- resolve typing, unsupported-operation, and compiled-runtime
-   failures.
-#. **Numba-GPU** -- resolve device compilation, memory, atomic, and scheduling
-   failures.
+#. **Python construction** -- confirm that the model compiles and the expected objects, IDs, offsets, and data are present.
+#. **Python transport** -- verify the algorithm and state mutation with JIT disabled.
+#. **Numba-CPU** -- resolve typing, unsupported-operation, and compiled-runtime failures.
+#. **Numba-GPU** -- resolve device compilation, memory, atomic, and scheduling failures.
 
-Do not begin by diagnosing a GPU compiler error if the same calculation is
-already incorrect in Python. Conversely, a passing Python test does not prove
-that the function is type-stable or device compatible.
+Do not begin by diagnosing a GPU compiler error if the same calculation is already incorrect in Python.
+Conversely, a passing Python test does not prove that the function is type-stable or device compatible.
 
 Verification Checklist
 ----------------------
@@ -241,17 +196,12 @@ Before considering a transport extension complete:
 - The same tests or representative regression case pass in Numba-CPU mode.
 - Python and Numba-CPU results agree within the test's numerical tolerance.
 - A supported GPU environment exercises the path.
-- GPU results preserve the same physical behavior within appropriate
-  numerical and statistical tolerances.
-- Existing examples still construct successfully when the public API or model
-  compilation changed.
+- GPU results preserve the same physical behavior within appropriate numerical and statistical tolerances.
+- Existing examples still construct successfully when the public API or model compilation changed.
 - User and developer documentation describe any new behavior or limitation.
 
-A general feature merged and maintained as part of MC/DC must complete all
-three execution stages unless the maintainers explicitly accept and document a
-backend-specific limitation. Experimental or study-specific work may stop at
-Python or Numba-CPU when that stage already satisfies its purpose.
+A general feature merged and maintained as part of MC/DC must complete all three execution stages unless the maintainers explicitly accept and document a backend-specific limitation.
+Experimental or study-specific work may stop at Python or Numba-CPU when that stage already satisfies its purpose.
 
-Repository commands, continuous-integration coverage, and regression-test
-options belong in the :doc:`../../contributing/index`. For changes affecting
-public inputs, follow :doc:`../../contributing/example_validation`.
+Repository commands, continuous-integration coverage, and regression-test options belong in the :doc:`../../contributing/index`.
+For changes affecting public inputs, follow :doc:`../../contributing/example_validation`.

From f6d3f237a66c4b8b2557695258d4a77c7f3d46fd Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 2 Aug 2026 20:42:03 +0700
Subject: [PATCH 082/202] update docs

---
 .../architecture/python_first_numba_accelerated_design.rst       | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
index fe4731877..0d7c2a94a 100644
--- a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -130,6 +130,7 @@ Preparing a method for acceleration narrows the freedom available inside transpo
 
 **Flexible models become predictable execution data.**
 Python objects remain the natural way to describe a problem, but accelerated transport operates on a numerical representation prepared for one simulation.
+Mutable runtime records are passed in one-element array containers, providing stable shared storage across Python, Numba-CPU, and Numba-GPU execution.
 The transformation is covered in :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
 
 **Transport behavior becomes explicit.**

From 4fa4673c1f147428580767d809c61b29dcb4fcac Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 2 Aug 2026 21:07:20 +0700
Subject: [PATCH 083/202] update docs

---
 .../python_first_numba_accelerated_design.rst |  1 +
 .../architecture/runtime_data_layout.rst      | 28 +++++++++++++++++++
 2 files changed, 29 insertions(+)

diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
index 0d7c2a94a..fe759c675 100644
--- a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -130,6 +130,7 @@ Preparing a method for acceleration narrows the freedom available inside transpo
 
 **Flexible models become predictable execution data.**
 Python objects remain the natural way to describe a problem, but accelerated transport operates on a numerical representation prepared for one simulation.
+MC/DC therefore replaces Python's implicit object machinery with a purpose-built runtime object model based on structured records, simulation-local IDs, offsets, and generated accessors.
 Mutable runtime records are passed in one-element array containers, providing stable shared storage across Python, Numba-CPU, and Numba-GPU execution.
 The transformation is covered in :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
 
diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index d0dc939a6..ee84cb325 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -31,6 +31,34 @@ MC/DC separates fixed-layout metadata from variable-length values:
    :width: 100%
    :alt: A cell, its boundary surfaces, and a surface-crossing tally become connected runtime records whose variable-length fields are stored in a flat data array.
 
+An Explicit Runtime Object Model
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+At a high level, MC/DC's prepared representation recreates machinery that an object system normally provides behind a class interface.
+A conventional object runtime stores fixed fields with the object while references point to separately allocated objects and variable-length values.
+Accessing an attribute follows those references without requiring application code to know where the referenced memory resides.
+
+MC/DC makes comparable operations explicit.
+Fixed fields become structured-record fields, Python object references become simulation-local IDs, variable-length fields become offsets into ``data``, and generated accessors perform the corresponding lookup or offset calculation.
+The combination of ``simulation`` and ``data`` can therefore be understood as a purpose-built runtime object model backed by explicit records and a flat data arena.
+
+Seen narrowly, this design reinvents facilities already supplied by Python and other language runtimes.
+MC/DC derives schemas, assigns object identities, packs values, represents relationships, dispatches among concrete representations, and generates field accessors.
+Maintaining this machinery adds implementation complexity and requires MC/DC to define rules that an ordinary class system would otherwise manage automatically.
+
+The duplication is necessary because the Python object model does not satisfy MC/DC's execution requirements.
+Python objects may contain interpreter-managed references, dynamic types, arbitrary inheritance behavior, and separately allocated containers that Numba cannot generally compile or transfer to an accelerator.
+Host pointers also cannot serve as portable references to state allocated in a GPU address space.
+MC/DC instead needs a complete representation with predictable types, explicit ownership, stable relationships, and equivalent access patterns across Python, Numba-CPU, and Numba-GPU execution.
+
+The current single ``float64`` data arena is a simplifying choice within this design rather than an inherent requirement of an explicit runtime object model.
+It gives MC/DC one variable-length allocation, one offset space, and consistent function signatures across execution modes.
+Integer values stored in the arena, including lists of object IDs, are exactly representable for practical MC/DC model sizes but must be cast back to integers when accessed.
+Separate typed arenas could preserve integer types and avoid those conversions, but would introduce additional allocations, offsets, generated accessors, function arguments, and GPU memory management.
+
+MC/DC's implementation should therefore be viewed neither as an ordinary Python class layout nor as a general-purpose replacement for one.
+It is a specialized, arena-backed object model that exchanges language-level generality for the predictable representation required by portable particle-transport execution.
+
 Object Collections
 ^^^^^^^^^^^^^^^^^^
 

From 7a4725c8d6918746b779fad8f5e48067f349e812 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 11:19:57 +0700
Subject: [PATCH 084/202] use png not svg

---
 .../developer_guide/architecture/index.rst    |   2 +-
 .../architecture/runtime_data_layout.rst      |   2 +-
 .../architecture/architecture_flow.png        | Bin 0 -> 434866 bytes
 .../architecture/architecture_flow.svg        |   1 -
 .../architecture/runtime_data_layout.png      | Bin 0 -> 824180 bytes
 .../architecture/runtime_data_layout.svg      | 103 ------------------
 6 files changed, 2 insertions(+), 106 deletions(-)
 create mode 100644 docs/source/images/developer_guide/architecture/architecture_flow.png
 delete mode 100644 docs/source/images/developer_guide/architecture/architecture_flow.svg
 create mode 100644 docs/source/images/developer_guide/architecture/runtime_data_layout.png
 delete mode 100644 docs/source/images/developer_guide/architecture/runtime_data_layout.svg

diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index 1dfc17ec7..954463ae0 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -6,7 +6,7 @@ Architecture
 
 Architecture documentation explains how MC/DC translates flexible Python model definitions into particle-transport execution:
 
-.. image:: ../../images/developer_guide/architecture/architecture_flow.svg
+.. image:: ../../images/developer_guide/architecture/architecture_flow.png
    :width: 100%
    :class: architecture-flow-figure
    :alt: MC/DC's architecture flow from model definition through simulation compilation and runtime preparation to shared transport, which runs with Python, Numba-CPU, or Numba-GPU execution modes.
diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index ee84cb325..b93ca5b2a 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -27,7 +27,7 @@ Nested Python references and arbitrary array shapes cannot be embedded directly
 
 MC/DC separates fixed-layout metadata from variable-length values:
 
-.. image:: ../../images/developer_guide/architecture/runtime_data_layout.svg
+.. image:: ../../images/developer_guide/architecture/runtime_data_layout.png
    :width: 100%
    :alt: A cell, its boundary surfaces, and a surface-crossing tally become connected runtime records whose variable-length fields are stored in a flat data array.
 
diff --git a/docs/source/images/developer_guide/architecture/architecture_flow.png b/docs/source/images/developer_guide/architecture/architecture_flow.png
new file mode 100644
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diff --git a/docs/source/images/developer_guide/architecture/runtime_data_layout.svg b/docs/source/images/developer_guide/architecture/runtime_data_layout.svg
deleted file mode 100644
index 4eacbd26c..000000000
--- a/docs/source/images/developer_guide/architecture/runtime_data_layout.svg
+++ /dev/null
@@ -1,103 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="720" viewBox="0 0 1200 720" role="img" aria-labelledby="title desc">
-  <title id="title">MC/DC runtime data layout</title>
-  <desc id="desc">A cell refers to its boundary surfaces, and a surface refers to an attached surface-crossing tally. The cell and surfaces are stored directly. The tally has a common base record and a concrete surface-crossing record. Their variable-length ID lists and tally values are flattened into a shared data array.</desc>
-  <defs>
-    <style>
-      .title { font-family: system-ui, sans-serif; font-size: 23px; font-weight: 700; fill: #17202a; }
-      .label { font-family: system-ui, sans-serif; font-size: 17px; font-weight: 650; fill: #17202a; }
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-      .box { stroke: #34495e; stroke-width: 2; rx: 10; }
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-  </defs>
-
-  <text x="600" y="35" text-anchor="middle" class="title">Connected model objects become fixed-layout records and flat data</text>
-
-  <rect x="35" y="75" width="300" height="470" class="box" fill="#eaf2f8"/>
-  <text x="185" y="108" text-anchor="middle" class="label">Python model objects</text>
-
-  <line x1="185" y1="230" x2="185" y2="270" stroke="#566573" stroke-width="2.5"/>
-  <text x="200" y="255" class="small">bounded by</text>
-  <line x1="185" y1="375" x2="185" y2="415" stroke="#566573" stroke-width="2.5"/>
-  <text x="200" y="400" class="small">filters</text>
-
-  <rect x="65" y="130" width="240" height="100" class="box" fill="#ffffff"/>
-  <text x="85" y="160" class="mono">Cell</text>
-  <text x="85" y="188" class="mono">region = +lower &amp; -upper</text>
-  <text x="85" y="216" class="body">directly stored object</text>
-
-  <rect x="65" y="270" width="240" height="105" class="box" fill="#ffffff"/>
-  <text x="85" y="300" class="mono">lower = PlaneZ(z=0)</text>
-  <text x="85" y="328" class="mono">upper = PlaneZ(z=2)</text>
-  <text x="85" y="356" class="body">directly stored surfaces</text>
-
-  <rect x="65" y="415" width="240" height="110" class="box" fill="#ffffff"/>
-  <text x="85" y="445" class="mono">Tally</text>
-  <text x="85" y="473" class="mono">surface = upper</text>
-  <text x="85" y="501" class="mono">cell = cell</text>
-  <text x="85" y="518" class="body">surface-crossing tally</text>
-
-  <rect x="400" y="75" width="420" height="470" class="box" fill="#fef9e7"/>
-  <text x="610" y="108" text-anchor="middle" class="label">structured simulation</text>
-
-  <line x1="610" y1="210" x2="610" y2="235" stroke="#566573" stroke-width="2.5"/>
-  <text x="625" y="228" class="small">surface IDs</text>
-  <line x1="610" y1="335" x2="610" y2="360" stroke="#566573" stroke-width="2.5"/>
-  <text x="625" y="353" class="small">tally ID</text>
-  <line x1="610" y1="440" x2="610" y2="455" stroke="#566573" stroke-width="2.5"/>
-  <text x="625" y="452" class="small">sub_ID</text>
-
-  <rect x="425" y="125" width="370" height="85" class="box" fill="#ffffff"/>
-  <text x="445" y="154" class="mono">cells[0]</text>
-  <text x="445" y="180" class="mono">N_surface = 2</text>
-  <text x="445" y="203" class="mono">surface_IDs_offset = 0</text>
-
-  <rect x="425" y="235" width="370" height="100" class="box" fill="#ffffff"/>
-  <text x="445" y="264" class="mono">surfaces[0], surfaces[1]</text>
-  <text x="445" y="290" class="mono">type = SURFACE_PLANE_Z</text>
-  <text x="445" y="313" class="mono">surfaces[1].N_surface_crossing_tally = 1</text>
-  <text x="445" y="330" class="small">surface_crossing_tally_IDs_offset = 2</text>
-
-  <rect x="425" y="360" width="370" height="80" class="box" fill="#ffffff"/>
-  <text x="445" y="389" class="mono">tallies[0]</text>
-  <text x="445" y="413" class="mono">sub_type = TALLY_SURFACE_CROSSING</text>
-  <text x="445" y="434" class="mono">sub_ID = 0</text>
-
-  <rect x="425" y="455" width="370" height="80" class="box" fill="#ffffff"/>
-  <text x="445" y="482" class="mono">surface_crossing_tallies[0]</text>
-  <text x="445" y="505" class="mono">surface_filter_ID = 1</text>
-  <text x="445" y="528" class="mono">cell_filter_ID = 0</text>
-
-  <line x1="335" y1="180" x2="400" y2="168" stroke="#566573" stroke-width="2.5"/>
-  <line x1="335" y1="322" x2="400" y2="285" stroke="#566573" stroke-width="2.5"/>
-  <line x1="335" y1="470" x2="400" y2="398" stroke="#566573" stroke-width="2.5"/>
-
-  <rect x="875" y="75" width="290" height="470" class="box" fill="#e8f8f5"/>
-  <text x="1020" y="108" text-anchor="middle" class="label">flat data array</text>
-
-  <rect x="905" y="145" width="230" height="55" class="box" fill="#d5f5e3"/>
-  <text x="1020" y="169" text-anchor="middle" class="mono">0 · 1</text>
-  <text x="1020" y="191" text-anchor="middle" class="body">cell.surface_IDs</text>
-
-  <rect x="905" y="260" width="230" height="55" class="box" fill="#d6eaf8"/>
-  <text x="1020" y="284" text-anchor="middle" class="mono">0</text>
-  <text x="1020" y="306" text-anchor="middle" class="body">surface-crossing tally IDs</text>
-
-  <rect x="905" y="385" width="230" height="55" class="box" fill="#f5eef8"/>
-  <text x="1020" y="409" text-anchor="middle" class="mono">… scores and bins …</text>
-  <text x="1020" y="431" text-anchor="middle" class="body">tally variable fields</text>
-
-  <text x="1020" y="505" text-anchor="middle" class="mono">data[0:N]</text>
-  <line x1="820" y1="168" x2="875" y2="172" stroke="#566573" stroke-width="2.5"/>
-  <line x1="820" y1="285" x2="875" y2="287" stroke="#566573" stroke-width="2.5"/>
-  <line x1="820" y1="398" x2="875" y2="412" stroke="#566573" stroke-width="2.5"/>
-
-  <rect x="180" y="590" width="840" height="95" class="box" fill="#f4ecf7"/>
-  <text x="600" y="620" text-anchor="middle" class="label">generated mcdc_get / mcdc_set helpers</text>
-  <text x="600" y="647" text-anchor="middle" class="mono">mcdc_get.cell.surface_IDs(i, cell, data)</text>
-  <text x="600" y="670" text-anchor="middle" class="mono">mcdc_get.surface.surface_crossing_tally_IDs(i, surface, data)</text>
-
-  <line x1="610" y1="545" x2="610" y2="590" stroke="#566573" stroke-width="2.5"/>
-  <line x1="1020" y1="545" x2="845" y2="590" stroke="#566573" stroke-width="2.5"/>
-</svg>

From 974842f7b0297bf7fde15ecdcc2341274e056616 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 11:53:24 +0700
Subject: [PATCH 085/202] minor edit docs

---
 .../architecture/runtime_data_layout.rst      | 45 ++++++++++---------
 1 file changed, 25 insertions(+), 20 deletions(-)

diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index b93ca5b2a..f87e518bf 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -4,7 +4,7 @@
 Runtime Data Layout
 ===================
 
-After model compilation has discovered and ordered the Python object graph, ``mcdc.main.prepare`` creates the runtime representation used by transport.
+After model compilation has discovered and ordered the Python object graph, ``mcdc.main.prepare`` calls ``generate_numba_layers`` in ``mcdc.code_factory`` to create the runtime representation used by transport.
 The representation has two complementary parts:
 
 ``simulation``
@@ -14,7 +14,6 @@ The representation has two complementary parts:
    A contiguous one-dimensional NumPy array containing variable-length numerical payloads and lists of object IDs.
 
 The same logical representation is supplied to Python, Numba-CPU, and Numba-GPU execution.
-It should therefore be understood as MC/DC's transport runtime model, not as a separate Numba-only model.
 During Python-only prototyping, transport code may also access arbitrary Python state alongside this representation.
 A method intended for portable, maintained execution must express the state required by transport through the prepared representation.
 See :doc:`python_first_numba_accelerated_design` for this development model.
@@ -23,18 +22,24 @@ Why Two Structures?
 -------------------
 
 Python model objects may contain arrays whose sizes depend on the problem: energy grids, cross sections, mesh boundaries, motion tables, tally filters, and many others.
-Nested Python references and arbitrary array shapes cannot be embedded directly in a stable structured dtype.
+Nested Python object references and variable-sized arrays cannot be embedded directly in the stable NumPy structured dtype required by the Numba execution modes.
 
 MC/DC separates fixed-layout metadata from variable-length values:
 
 .. image:: ../../images/developer_guide/architecture/runtime_data_layout.png
    :width: 100%
-   :alt: A cell, its boundary surfaces, and a surface-crossing tally become connected runtime records whose variable-length fields are stored in a flat data array.
+   :alt: Runtime preparation turns a cell, its three boundary surfaces, and a surface-crossing tally into structured records whose metadata points into a flat data array through generated accessors.
+
+The figure follows one connected example from Python model objects into the two runtime layers.
+The cell record locates its three surface IDs in ``data``, the selected surface record locates an attached tally ID, and the base tally record identifies its concrete surface-crossing record.
+Tally scores, bins, and other variable-length payloads share the same flat arena.
+Generated ``mcdc_get`` and ``mcdc_set`` accessors translate logical field access into the required offset calculation.
+The IDs and offsets shown in the figure are illustrative; their values depend on the compiled model and its packed layout.
 
 An Explicit Runtime Object Model
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-At a high level, MC/DC's prepared representation recreates machinery that an object system normally provides behind a class interface.
+Together, the structured records, flat data arena, and generated accessors form an explicit runtime object model.
 A conventional object runtime stores fixed fields with the object while references point to separately allocated objects and variable-length values.
 Accessing an attribute follows those references without requiring application code to know where the referenced memory resides.
 
@@ -46,7 +51,7 @@ Seen narrowly, this design reinvents facilities already supplied by Python and o
 MC/DC derives schemas, assigns object identities, packs values, represents relationships, dispatches among concrete representations, and generates field accessors.
 Maintaining this machinery adds implementation complexity and requires MC/DC to define rules that an ordinary class system would otherwise manage automatically.
 
-The duplication is necessary because the Python object model does not satisfy MC/DC's execution requirements.
+The duplication is necessary because the Python object model does not satisfy Numba execution requirements.
 Python objects may contain interpreter-managed references, dynamic types, arbitrary inheritance behavior, and separately allocated containers that Numba cannot generally compile or transfer to an accelerator.
 Host pointers also cannot serve as portable references to state allocated in a GPU address space.
 MC/DC instead needs a complete representation with predictable types, explicit ownership, stable relationships, and equivalent access patterns across Python, Numba-CPU, and Numba-GPU execution.
@@ -63,8 +68,7 @@ Object Collections
 ^^^^^^^^^^^^^^^^^^
 
 Registered model objects are stored in collections on ``simulation``.
-The figure follows a cell, its boundary surfaces, and a surface-crossing tally.
-It demonstrates both forms of runtime collection.
+The figure demonstrates both forms of runtime collection: direct indexing for non-polymorphic objects and base-to-concrete dispatch for polymorphic objects.
 
 For a non-polymorphic category, an object's simulation-local ID directly indexes its collection.
 A particle's current cell and one of its boundary surfaces are therefore retrieved with:
@@ -84,15 +88,12 @@ Each ID first selects a base tally record, whose ``sub_type`` and ``sub_ID`` ide
    from mcdc.constant import TALLY_SURFACE_CROSSING
 
 
-   tally_ID = int(
-       mcdc_get.surface.surface_crossing_tally_IDs(0, surface, data)
-   )
+   tally_ID = int(mcdc_get.surface.surface_crossing_tally_IDs(0, surface, data))
    tally = simulation["tallies"][tally_ID]
 
-   if tally["sub_type"] == TALLY_SURFACE_CROSSING:
-       surface_crossing_tally = simulation["surface_crossing_tallies"][
-           tally["sub_ID"]
-       ]
+   tally["sub_type"] == TALLY_SURFACE_CROSSING  # True
+
+   surface_crossing_tally = simulation["surface_crossing_tallies"][tally["sub_ID"]]
 
 The concrete tally record retains ``surface_filter_ID`` and ``cell_filter_ID``, connecting it back to the selected surface and cell.
 All IDs are assigned during model compilation and identify objects only within the current simulation snapshot.
@@ -101,18 +102,22 @@ The hierarchy and ID assignment are described in :doc:`simulation_compilation`.
 Variable-Length Fields
 ^^^^^^^^^^^^^^^^^^^^^^
 
-For a variable-length list such as a cell's boundary surfaces, the cell record stores values equivalent to:
+Using the illustrative values in the figure, the cell and selected surface records store metadata equivalent to:
 
 .. code-block:: text
 
-   surface_IDs_offset = 120
-   N_surface = 2
+   cell.surface_IDs_offset = 0
+   cell.N_surface = 3
+
+   surface.surface_crossing_tally_IDs_offset = 3
+   surface.N_surface_crossing_tally = 1
 
-and the two surface IDs occupy:
+The corresponding ID lists occupy adjacent regions of ``data`` in the simplified layout:
 
 .. code-block:: text
 
-   data[120:122]
+   data[0:3] = [0, 1, 2]  # Cell's surface IDs
+   data[3:4] = [0]        # Surface's tally ID
 
 For multidimensional arrays, annotated shape metadata supplies the strides used to reconstruct logical indexing.
 The payload itself is flattened when packed.

From 02eb600e9df595eda3998f4d2c7da274dcd2f116 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 12:33:22 +0700
Subject: [PATCH 086/202] update docs

---
 .../architecture/runtime_data_layout.rst      | 85 +++++++++++++------
 1 file changed, 60 insertions(+), 25 deletions(-)

diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index f87e518bf..5ef01cc74 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -119,8 +119,66 @@ The corresponding ID lists occupy adjacent regions of ``data`` in the simplified
    data[0:3] = [0, 1, 2]  # Cell's surface IDs
    data[3:4] = [0]        # Surface's tally ID
 
-For multidimensional arrays, annotated shape metadata supplies the strides used to reconstruct logical indexing.
-The payload itself is flattened when packed.
+Array Shapes and Generated Access
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Array shape annotations determine whether an array is embedded in a structured record or stored in ``data``.
+For example, ``Cell.translation`` has a completely fixed shape:
+
+.. code-block:: python
+
+   translation: Annotated[NDArray[float64], (3,)]
+
+Because every dimension is an integer literal, the three-component array is embedded directly in the cell record and accessed through ``cell["translation"]``.
+
+``Surface.move_velocities`` combines a model-dependent dimension with a fixed trailing dimension:
+
+.. code-block:: python
+
+   move_velocities: Annotated[NDArray[float64], ("N_move", 3)]
+
+The symbolic dimension ``N_move`` names the surface record field that supplies its size at runtime.
+Because that dimension depends on the model, the array is flattened into ``data``, and the surface record stores its offset and total length.
+Fully symbolic multidimensional arrays use the same mechanism.
+For example, ``mgxs_nu_d`` is shaped ``("G", "J")`` and uses the named energy-group and delayed-neutron-group dimensions to reconstruct indexing into its flattened payload.
+Generated accessors for arrays stored in ``data`` currently support array ranks from one through four dimensions.
+
+``mcdc.code_factory`` generates modules under ``mcdc/mcdc_get`` and ``mcdc/mcdc_set`` for fields stored in ``data``.
+These helpers hide offset and stride arithmetic from transport code and remain callable from both Python and Numba-compiled functions.
+
+Conceptually, a generated element getter for the cell's surface IDs performs:
+
+.. code-block:: python
+
+   def surface_IDs(index, cell, data):
+       offset = cell["surface_IDs_offset"]
+       return data[offset + index]
+
+Transport code can therefore express logical access without depending on where the values reside in ``data``:
+
+.. code-block:: python
+
+   surface_ID = int(mcdc_get.cell.surface_IDs(index, cell, data))
+
+For ``move_velocities``, the generated accessor uses the fixed trailing dimension as the row stride and reconstructs logical two-dimensional indexing:
+
+.. code-block:: python
+
+   velocity = mcdc_get.surface.move_velocities(
+       move_index, component_index, surface, data
+   )
+
+For ``mgxs_nu_d``, the generated element getter reads the named trailing dimension ``J`` from the material record and uses it as the runtime row stride:
+
+.. code-block:: python
+
+   def mgxs_nu_d(group, delayed_group, material, data):
+       offset = material["mgxs_nu_d_offset"]
+       stride = material["J"]
+       return data[offset + group * stride + delayed_group]
+
+In the row-major flattened layout, ``J`` determines the stride between energy groups, while ``G`` determines the number of rows.
+Generated helpers also provide operations for complete arrays, final elements, chunks, vectors, and multidimensional elements as appropriate.
 
 Deriving the Layout
 -------------------
@@ -155,29 +213,6 @@ The generated simulation record is stored in a one-element NumPy array:
 The container gives Python, Numba, MPI, and GPU paths a consistent mutable reference to the structured state.
 Transport drivers receive the container and ``data``; individual kernels generally operate on the record or its nested objects.
 
-Generated Access Helpers
-------------------------
-
-``mcdc.code_factory`` generates modules under ``mcdc/mcdc_get`` and ``mcdc/mcdc_set`` for variable-length fields.
-These helpers hide offset and stride arithmetic from transport code and remain callable from both Python and Numba-compiled functions.
-
-Conceptually, a generated element getter performs:
-
-.. code-block:: python
-
-   def surface_IDs(index, cell, data):
-       offset = cell["surface_IDs_offset"]
-       return data[offset + index]
-
-Generated helpers also provide operations for complete arrays, final elements, chunks, vectors, and multidimensional elements as appropriate.
-Transport code can therefore express logical access such as:
-
-.. code-block:: python
-
-   surface_ID = int(mcdc_get.cell.surface_IDs(index, cell, data))
-
-without depending on where that cell's surface IDs happen to reside in ``data``.
-
 Transport Consumption
 ---------------------
 

From 8f6310b827f0b0885c5629b33ec0aee94db2363b Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 15:39:32 +0700
Subject: [PATCH 087/202] add integer casting to mcdc_get

---
 .../architecture/runtime_data_layout.rst      |  15 +-
 mcdc/code_factory/numba_layers_generator.py   | 186 ++++++++++++++----
 mcdc/mcdc_get/cell.py                         |  17 +-
 mcdc/mcdc_get/electron_ionization_reaction.py |   9 +-
 mcdc/mcdc_get/element.py                      |  17 +-
 mcdc/mcdc_get/kalbach_mann_distribution.py    |   5 +-
 mcdc/mcdc_get/lattice.py                      |   3 +-
 mcdc/mcdc_get/multi_table_distribution.py     |   5 +-
 mcdc/mcdc_get/native_material.py              |   9 +-
 .../neutron_inelastic_scattering_reaction.py  |   5 +-
 mcdc/mcdc_get/nuclide.py                      |  21 +-
 mcdc/mcdc_get/surface.py                      |   5 +-
 mcdc/mcdc_get/table_data.py                   |   9 +-
 .../tabulated_energy_angle_distribution.py    |   9 +-
 mcdc/mcdc_get/tally.py                        |   9 +-
 mcdc/mcdc_get/universe.py                     |   5 +-
 mcdc/transport/distribution.py                |  44 ++---
 mcdc/transport/geometry/interface.py          |  14 +-
 mcdc/transport/physics/electron/native.py     |  36 ++--
 mcdc/transport/physics/neutron/native.py      |  56 +++---
 mcdc/transport/simulation.py                  |   6 +-
 test/unit/test_numba_layers_generator.py      | 100 ++++++++++
 22 files changed, 396 insertions(+), 189 deletions(-)
 create mode 100644 test/unit/test_numba_layers_generator.py

diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index 5ef01cc74..3c9f8e7d6 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -58,7 +58,7 @@ MC/DC instead needs a complete representation with predictable types, explicit o
 
 The current single ``float64`` data arena is a simplifying choice within this design rather than an inherent requirement of an explicit runtime object model.
 It gives MC/DC one variable-length allocation, one offset space, and consistent function signatures across execution modes.
-Integer values stored in the arena, including lists of object IDs, are exactly representable for practical MC/DC model sizes but must be cast back to integers when accessed.
+Integer values stored in the arena, including lists of object IDs, are exactly representable for practical MC/DC model sizes, and generated scalar getters cast them back to integers when accessed.
 Separate typed arenas could preserve integer types and avoid those conversions, but would introduce additional allocations, offsets, generated accessors, function arguments, and GPU memory management.
 
 MC/DC's implementation should therefore be viewed neither as an ordinary Python class layout nor as a general-purpose replacement for one.
@@ -76,7 +76,7 @@ A particle's current cell and one of its boundary surfaces are therefore retriev
 .. code-block:: python
 
    cell = simulation["cells"][particle["cell_ID"]]
-   surface_ID = int(mcdc_get.cell.surface_IDs(0, cell, data))
+   surface_ID = mcdc_get.cell.surface_IDs(0, cell, data)
    surface = simulation["surfaces"][surface_ID]
 
 A polymorphic category has both a common base collection and a collection for each concrete representation.
@@ -88,7 +88,7 @@ Each ID first selects a base tally record, whose ``sub_type`` and ``sub_ID`` ide
    from mcdc.constant import TALLY_SURFACE_CROSSING
 
 
-   tally_ID = int(mcdc_get.surface.surface_crossing_tally_IDs(0, surface, data))
+   tally_ID = mcdc_get.surface.surface_crossing_tally_IDs(0, surface, data)
    tally = simulation["tallies"][tally_ID]
 
    tally["sub_type"] == TALLY_SURFACE_CROSSING  # True
@@ -150,15 +150,18 @@ Conceptually, a generated element getter for the cell's surface IDs performs:
 
 .. code-block:: python
 
+   from numpy import int64
+
+
    def surface_IDs(index, cell, data):
        offset = cell["surface_IDs_offset"]
-       return data[offset + index]
+       return int64(data[offset + index])
 
 Transport code can therefore express logical access without depending on where the values reside in ``data``:
 
 .. code-block:: python
 
-   surface_ID = int(mcdc_get.cell.surface_IDs(index, cell, data))
+   surface_ID = mcdc_get.cell.surface_IDs(index, cell, data)
 
 For ``move_velocities``, the generated accessor uses the fixed trailing dimension as the row stride and reconstructs logical two-dimensional indexing:
 
@@ -179,6 +182,8 @@ For ``mgxs_nu_d``, the generated element getter reads the named trailing dimensi
 
 In the row-major flattened layout, ``J`` determines the stride between energy groups, while ``G`` determines the number of rows.
 Generated helpers also provide operations for complete arrays, final elements, chunks, vectors, and multidimensional elements as appropriate.
+Scalar getters restore the integer type declared by an annotation or implied by an object-ID list.
+Bulk getters continue to return zero-copy ``float64`` views into ``data`` and therefore require explicit conversion when an integer array is needed outside transport.
 
 Deriving the Layout
 -------------------
diff --git a/mcdc/code_factory/numba_layers_generator.py b/mcdc/code_factory/numba_layers_generator.py
index e7ac5a739..afe5cc54a 100644
--- a/mcdc/code_factory/numba_layers_generator.py
+++ b/mcdc/code_factory/numba_layers_generator.py
@@ -499,6 +499,10 @@ def set_structure(label, structures, accessor_targets, annotations):
                     fixed_size_array = False
                     break
 
+        # Get the element dtype from an NDArray without shape metadata
+        if hint_origin is np.ndarray and hint_inner_dtype is None:
+            hint_inner_dtype = get_ndarray_dtype(hint)
+
         # Skip simulation object structure
         if label == "simulation":
             if hint in all_classes:
@@ -547,10 +551,16 @@ def polymorphic_base(x):
         elif simple_list or numpy_array:
             structure.append((f"{field}_offset", type_map[int]))
             structure.append((f"{field}_length", type_map[int]))
+            logical_type = hint_args[0] if simple_list else hint_inner_dtype
+            cast_to_int = is_integer_type(logical_type)
             if hint_origin_shape is not None:
-                accessor_target.append((f"{field}", hint_origin_shape))
+                accessor_target.append(
+                    AccessorTarget(f"{field}", hint_origin_shape, cast_to_int)
+                )
             else:
-                accessor_target.append((f"{field}", (f"{field}_length",)))
+                accessor_target.append(
+                    AccessorTarget(f"{field}", (f"{field}_length",), cast_to_int)
+                )
 
         # MC/DC classes
         elif non_polymorphic(hint) or polymorphic_base(hint):
@@ -562,9 +572,13 @@ def polymorphic_base(x):
             structure.append((f"N_{singular}", type_map[int]))
             structure.append((f"{singular}_IDs_offset", type_map[int]))
             if hint_origin_shape is not None:
-                accessor_target.append((f"{singular}_IDs", hint_origin_shape))
+                accessor_target.append(
+                    AccessorTarget(f"{singular}_IDs", hint_origin_shape, True)
+                )
             else:
-                accessor_target.append((f"{singular}_IDs", (f"N_{singular}",)))
+                accessor_target.append(
+                    AccessorTarget(f"{singular}_IDs", (f"N_{singular}",), True)
+                )
 
         # Unknown type
         else:
@@ -865,11 +879,26 @@ def into_dtype(field_list):
 # Type parser
 # ======================================================================================
 
-from typing import Annotated, Any, ForwardRef, Optional, Union, get_args, get_origin
+from typing import (
+    Annotated,
+    Any,
+    ForwardRef,
+    NamedTuple,
+    Optional,
+    Union,
+    get_args,
+    get_origin,
+)
 import numpy as np
 from numpy.typing import NDArray
 
 
+class AccessorTarget(NamedTuple):
+    name: str
+    shape: tuple[int | str, ...]
+    cast_to_int: bool
+
+
 # --- Safe locals for eval + ForwardRef fallback ---
 class _FwdRefDict(dict):
     """If a symbol isn't in the whitelist, treat it as a ForwardRef('Symbol')."""
@@ -940,12 +969,44 @@ def decode_annotated_ndarray(hint):
     }
 
 
+def get_ndarray_dtype(hint):
+    hint_args = get_args(hint)
+    if len(hint_args) < 2:
+        return None
+    dtype_args = get_args(hint_args[1])
+    if len(dtype_args) == 0:
+        return None
+    return dtype_args[0]
+
+
+def is_integer_type(type_):
+    if type_ is None:
+        return False
+    try:
+        return np.issubdtype(np.dtype(type_), np.integer)
+    except TypeError:
+        return False
+
+
 # ======================================================================================
 # Helpers for mcdc_get generators
 # ======================================================================================
 
 
+def validate_accessor_targets(targets):
+    for object_name, attributes in targets.items():
+        for attribute in attributes:
+            rank = len(attribute.shape)
+            if not 1 <= rank <= 4:
+                raise ValueError(
+                    f"Generated accessors support one through four dimensions, "
+                    f"but {object_name}.{attribute.name} has rank {rank}."
+                )
+
+
 def generate_mcdc_access(targets):
+    validate_accessor_targets(targets)
+
     for object_name in targets.keys():
         path = f"{Path(mcdc.__file__).parent}"
         file_getter = open(f"{path}/mcdc_get/{object_name}.py", "w")
@@ -958,17 +1019,27 @@ def generate_mcdc_access(targets):
             "# The following is automatically generated by code_factory.py\n\n"
         )
 
+        if any(attribute.cast_to_int for attribute in targets[object_name]):
+            text_getter += "from numpy import int64\n"
         text_getter += "from numba import njit\n\n\n"
         text_setter += "from numba import njit\n\n\n"
 
         for attribute in targets[object_name]:
-            attribute_name = attribute[0]
-            shape = attribute[1]
+            attribute_name = attribute.name
+            shape = attribute.shape
+            cast_to_int = attribute.cast_to_int
 
             if len(shape) == 1:
-                text_getter += _accessor_1d_element(object_name, attribute_name)
+                text_getter += _accessor_1d_element(
+                    object_name, attribute_name, cast_to_int=cast_to_int
+                )
                 text_getter += _accessor_1d_all(object_name, attribute_name, shape[0])
-                text_getter += _accessor_1d_last(object_name, attribute_name, shape[0])
+                text_getter += _accessor_1d_last(
+                    object_name,
+                    attribute_name,
+                    shape[0],
+                    cast_to_int=cast_to_int,
+                )
 
                 text_setter += _accessor_1d_element(object_name, attribute_name, True)
                 text_setter += _accessor_1d_all(
@@ -983,7 +1054,10 @@ def generate_mcdc_access(targets):
                     object_name, attribute_name, shape[1]
                 )
                 text_getter += _accessor_2d_element(
-                    object_name, attribute_name, shape[1]
+                    object_name,
+                    attribute_name,
+                    shape[1],
+                    cast_to_int=cast_to_int,
                 )
 
                 text_setter += _accessor_2d_vector(
@@ -995,7 +1069,11 @@ def generate_mcdc_access(targets):
 
             elif len(shape) == 3:
                 text_getter += _accessor_3d_element(
-                    object_name, attribute_name, shape[1], shape[2]
+                    object_name,
+                    attribute_name,
+                    shape[1],
+                    shape[2],
+                    cast_to_int=cast_to_int,
                 )
 
                 text_setter += _accessor_3d_element(
@@ -1004,7 +1082,12 @@ def generate_mcdc_access(targets):
 
             elif len(shape) == 4:
                 text_getter += _accessor_4d_element(
-                    object_name, attribute_name, shape[1], shape[2], shape[3]
+                    object_name,
+                    attribute_name,
+                    shape[1],
+                    shape[2],
+                    shape[3],
+                    cast_to_int=cast_to_int,
                 )
 
                 text_setter += _accessor_4d_element(
@@ -1029,7 +1112,21 @@ def generate_mcdc_access(targets):
             f.write(text)
 
 
-def _accessor_1d_element(object_name, attribute_name, setter=False):
+def accessor_return(expression, cast_to_int):
+    if cast_to_int:
+        # Use an explicit NumPy scalar type so Python and Numba return the same
+        # logical integer width from the float64 data arena.
+        expression = f"int64({expression})"
+    return f"    return {expression}\n\n\n"
+
+
+def accessor_dimension(variable_name, dimension, object_name):
+    if isinstance(dimension, str):
+        return f'    {variable_name} = {object_name}["{dimension}"]\n'
+    return f"    {variable_name} = {dimension}\n"
+
+
+def _accessor_1d_element(object_name, attribute_name, setter=False, cast_to_int=False):
     text = f"@njit\n"
     if setter:
         text += f"def {attribute_name}(index, {object_name}, data, value):\n"
@@ -1039,7 +1136,7 @@ def _accessor_1d_element(object_name, attribute_name, setter=False):
     if setter:
         text += f"    data[offset + index] = value\n\n\n"
     else:
-        text += f"    return data[offset + index]\n\n\n"
+        text += accessor_return("data[offset + index]", cast_to_int)
     return text
 
 
@@ -1062,7 +1159,9 @@ def _accessor_1d_all(object_name, attribute_name, size, setter=False):
     return text
 
 
-def _accessor_1d_last(object_name, attribute_name, size, setter=False):
+def _accessor_1d_last(
+    object_name, attribute_name, size, setter=False, cast_to_int=False
+):
     text = f"@njit\n"
     if setter:
         text += f"def {attribute_name}_last({object_name}, data, value):\n"
@@ -1077,7 +1176,7 @@ def _accessor_1d_last(object_name, attribute_name, size, setter=False):
     if setter:
         text += f"    data[end - 1] = value\n\n\n"
     else:
-        text += f"    return data[end - 1]\n\n\n"
+        text += accessor_return("data[end - 1]", cast_to_int)
     return text
 
 
@@ -1098,21 +1197,22 @@ def _accessor_chunk(object_name, attribute_name, setter=False):
     return text
 
 
-def _accessor_2d_element(object_name, attribute_name, stride, setter=False):
+def _accessor_2d_element(
+    object_name, attribute_name, stride, setter=False, cast_to_int=False
+):
     text = f"@njit\n"
     if setter:
         text += f"def {attribute_name}(index_1, index_2, {object_name}, data, value):\n"
     else:
         text += f"def {attribute_name}(index_1, index_2, {object_name}, data):\n"
     text += f'    offset = {object_name}["{attribute_name}_offset"]\n'
-    if isinstance(stride, str):
-        text += f'    stride = {object_name}["{stride}"]\n'
-    else:
-        text += f"    stride = {stride}\n"
+    text += accessor_dimension("stride", stride, object_name)
     if setter:
         text += f"    data[offset + index_1 * stride + index_2] = value\n\n\n"
     else:
-        text += f"    return data[offset + index_1 * stride + index_2]\n\n\n"
+        text += accessor_return(
+            "data[offset + index_1 * stride + index_2]", cast_to_int
+        )
     return text
 
 
@@ -1123,10 +1223,7 @@ def _accessor_2d_vector(object_name, attribute_name, stride, setter=False):
     else:
         text += f"def {attribute_name}_vector(index_1, {object_name}, data):\n"
     text += f'    offset = {object_name}["{attribute_name}_offset"]\n'
-    if isinstance(stride, str):
-        text += f'    stride = {object_name}["{stride}"]\n'
-    else:
-        text += f"    stride = {stride}\n"
+    text += accessor_dimension("stride", stride, object_name)
     text += f"    start = offset + index_1 * stride\n"
     text += f"    end = start + stride\n"
     if setter:
@@ -1136,7 +1233,14 @@ def _accessor_2d_vector(object_name, attribute_name, stride, setter=False):
     return text
 
 
-def _accessor_3d_element(object_name, attribute_name, stride_2, stride_3, setter=False):
+def _accessor_3d_element(
+    object_name,
+    attribute_name,
+    stride_2,
+    stride_3,
+    setter=False,
+    cast_to_int=False,
+):
     text = f"@njit\n"
     if setter:
         text += f"def {attribute_name}(index_1, index_2, index_3, {object_name}, data, value):\n"
@@ -1145,17 +1249,26 @@ def _accessor_3d_element(object_name, attribute_name, stride_2, stride_3, setter
             f"def {attribute_name}(index_1, index_2, index_3, {object_name}, data):\n"
         )
     text += f'    offset = {object_name}["{attribute_name}_offset"]\n'
-    text += f'    stride_2 = {object_name}["{stride_2}"]\n'
-    text += f'    stride_3 = {object_name}["{stride_3}"]\n'
+    text += accessor_dimension("stride_2", stride_2, object_name)
+    text += accessor_dimension("stride_3", stride_3, object_name)
     if setter:
         text += f"    data[offset + index_1 * stride_2 * stride_3 + index_2 * stride_3 + index_3] = value\n\n\n"
     else:
-        text += f"    return data[offset + index_1 * stride_2 * stride_3 + index_2 * stride_3 + index_3]\n\n\n"
+        text += accessor_return(
+            "data[offset + index_1 * stride_2 * stride_3 + index_2 * stride_3 + index_3]",
+            cast_to_int,
+        )
     return text
 
 
 def _accessor_4d_element(
-    object_name, attribute_name, stride_2, stride_3, stride_4, setter=False
+    object_name,
+    attribute_name,
+    stride_2,
+    stride_3,
+    stride_4,
+    setter=False,
+    cast_to_int=False,
 ):
     text = f"@njit\n"
     if setter:
@@ -1163,13 +1276,16 @@ def _accessor_4d_element(
     else:
         text += f"def {attribute_name}(index_1, index_2, index_3, index_4, {object_name}, data):\n"
     text += f'    offset = {object_name}["{attribute_name}_offset"]\n'
-    text += f'    stride_2 = {object_name}["{stride_2}"]\n'
-    text += f'    stride_3 = {object_name}["{stride_3}"]\n'
-    text += f'    stride_4 = {object_name}["{stride_4}"]\n'
+    text += accessor_dimension("stride_2", stride_2, object_name)
+    text += accessor_dimension("stride_3", stride_3, object_name)
+    text += accessor_dimension("stride_4", stride_4, object_name)
     if setter:
         text += f"    data[offset + index_1 * stride_2 * stride_3 * stride_4 + index_2 * stride_3 * stride_4 + index_3 * stride_4 + index_4] = value\n\n\n"
     else:
-        text += f"    return data[offset + index_1 * stride_2 * stride_3 * stride_4 + index_2 * stride_3 * stride_4 + index_3 * stride_4 + index_4]\n\n\n"
+        text += accessor_return(
+            "data[offset + index_1 * stride_2 * stride_3 * stride_4 + index_2 * stride_3 * stride_4 + index_3 * stride_4 + index_4]",
+            cast_to_int,
+        )
     return text
 
 
diff --git a/mcdc/mcdc_get/cell.py b/mcdc/mcdc_get/cell.py
index 17ee8a8e4..8dbe96150 100644
--- a/mcdc/mcdc_get/cell.py
+++ b/mcdc/mcdc_get/cell.py
@@ -1,12 +1,13 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
 @njit
 def region_RPN_tokens(index, cell, data):
     offset = cell["region_RPN_tokens_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -22,7 +23,7 @@ def region_RPN_tokens_last(cell, data):
     start = cell["region_RPN_tokens_offset"]
     size = cell["region_RPN_tokens_length"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -35,7 +36,7 @@ def region_RPN_tokens_chunk(start, length, cell, data):
 @njit
 def surface_IDs(index, cell, data):
     offset = cell["surface_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -51,7 +52,7 @@ def surface_IDs_last(cell, data):
     start = cell["surface_IDs_offset"]
     size = cell["N_surface"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -64,7 +65,7 @@ def surface_IDs_chunk(start, length, cell, data):
 @njit
 def collision_tally_IDs(index, cell, data):
     offset = cell["collision_tally_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -80,7 +81,7 @@ def collision_tally_IDs_last(cell, data):
     start = cell["collision_tally_IDs_offset"]
     size = cell["N_collision_tally"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -93,7 +94,7 @@ def collision_tally_IDs_chunk(start, length, cell, data):
 @njit
 def tracklength_tally_IDs(index, cell, data):
     offset = cell["tracklength_tally_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -109,7 +110,7 @@ def tracklength_tally_IDs_last(cell, data):
     start = cell["tracklength_tally_IDs_offset"]
     size = cell["N_tracklength_tally"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/electron_ionization_reaction.py b/mcdc/mcdc_get/electron_ionization_reaction.py
index 22775182f..e485ff58d 100644
--- a/mcdc/mcdc_get/electron_ionization_reaction.py
+++ b/mcdc/mcdc_get/electron_ionization_reaction.py
@@ -1,12 +1,13 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
 @njit
 def subshell_x_IDs(index, electron_ionization_reaction, data):
     offset = electron_ionization_reaction["subshell_x_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -22,7 +23,7 @@ def subshell_x_IDs_last(electron_ionization_reaction, data):
     start = electron_ionization_reaction["subshell_x_IDs_offset"]
     size = electron_ionization_reaction["N_subshell_x"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -35,7 +36,7 @@ def subshell_x_IDs_chunk(start, length, electron_ionization_reaction, data):
 @njit
 def subshell_product_IDs(index, electron_ionization_reaction, data):
     offset = electron_ionization_reaction["subshell_product_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -51,7 +52,7 @@ def subshell_product_IDs_last(electron_ionization_reaction, data):
     start = electron_ionization_reaction["subshell_product_IDs_offset"]
     size = electron_ionization_reaction["N_subshell_product"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/element.py b/mcdc/mcdc_get/element.py
index 6d5873a2c..a2fec6bd9 100644
--- a/mcdc/mcdc_get/element.py
+++ b/mcdc/mcdc_get/element.py
@@ -1,5 +1,6 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
@@ -180,7 +181,7 @@ def electron_bremsstrahlung_xs_chunk(start, length, element, data):
 @njit
 def electron_ionization_reaction_IDs(index, element, data):
     offset = element["electron_ionization_reaction_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -196,7 +197,7 @@ def electron_ionization_reaction_IDs_last(element, data):
     start = element["electron_ionization_reaction_IDs_offset"]
     size = element["N_electron_ionization_reaction"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -209,7 +210,7 @@ def electron_ionization_reaction_IDs_chunk(start, length, element, data):
 @njit
 def electron_elastic_scattering_reaction_IDs(index, element, data):
     offset = element["electron_elastic_scattering_reaction_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -225,7 +226,7 @@ def electron_elastic_scattering_reaction_IDs_last(element, data):
     start = element["electron_elastic_scattering_reaction_IDs_offset"]
     size = element["N_electron_elastic_scattering_reaction"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -238,7 +239,7 @@ def electron_elastic_scattering_reaction_IDs_chunk(start, length, element, data)
 @njit
 def electron_excitation_reaction_IDs(index, element, data):
     offset = element["electron_excitation_reaction_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -254,7 +255,7 @@ def electron_excitation_reaction_IDs_last(element, data):
     start = element["electron_excitation_reaction_IDs_offset"]
     size = element["N_electron_excitation_reaction"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -267,7 +268,7 @@ def electron_excitation_reaction_IDs_chunk(start, length, element, data):
 @njit
 def electron_bremsstrahlung_reaction_IDs(index, element, data):
     offset = element["electron_bremsstrahlung_reaction_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -283,7 +284,7 @@ def electron_bremsstrahlung_reaction_IDs_last(element, data):
     start = element["electron_bremsstrahlung_reaction_IDs_offset"]
     size = element["N_electron_bremsstrahlung_reaction"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/kalbach_mann_distribution.py b/mcdc/mcdc_get/kalbach_mann_distribution.py
index 456942a01..2916d0893 100644
--- a/mcdc/mcdc_get/kalbach_mann_distribution.py
+++ b/mcdc/mcdc_get/kalbach_mann_distribution.py
@@ -1,5 +1,6 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
@@ -35,7 +36,7 @@ def energy_chunk(start, length, kalbach_mann_distribution, data):
 @njit
 def offset(index, kalbach_mann_distribution, data):
     offset = kalbach_mann_distribution["offset_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -51,7 +52,7 @@ def offset_last(kalbach_mann_distribution, data):
     start = kalbach_mann_distribution["offset_offset"]
     size = kalbach_mann_distribution["offset_length"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/lattice.py b/mcdc/mcdc_get/lattice.py
index 437f5be40..4daad9d4b 100644
--- a/mcdc/mcdc_get/lattice.py
+++ b/mcdc/mcdc_get/lattice.py
@@ -1,5 +1,6 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
@@ -8,7 +9,7 @@ def universe_IDs(index_1, index_2, index_3, lattice, data):
     offset = lattice["universe_IDs_offset"]
     stride_2 = lattice["Ny"]
     stride_3 = lattice["Nz"]
-    return data[offset + index_1 * stride_2 * stride_3 + index_2 * stride_3 + index_3]
+    return int64(data[offset + index_1 * stride_2 * stride_3 + index_2 * stride_3 + index_3])
 
 
 @njit
diff --git a/mcdc/mcdc_get/multi_table_distribution.py b/mcdc/mcdc_get/multi_table_distribution.py
index aad2a755d..de411b77b 100644
--- a/mcdc/mcdc_get/multi_table_distribution.py
+++ b/mcdc/mcdc_get/multi_table_distribution.py
@@ -1,5 +1,6 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
@@ -35,7 +36,7 @@ def grid_chunk(start, length, multi_table_distribution, data):
 @njit
 def table_IDs(index, multi_table_distribution, data):
     offset = multi_table_distribution["table_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -51,7 +52,7 @@ def table_IDs_last(multi_table_distribution, data):
     start = multi_table_distribution["table_IDs_offset"]
     size = multi_table_distribution["N_table"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/native_material.py b/mcdc/mcdc_get/native_material.py
index 361294585..f07966d30 100644
--- a/mcdc/mcdc_get/native_material.py
+++ b/mcdc/mcdc_get/native_material.py
@@ -1,12 +1,13 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
 @njit
 def nuclide_IDs(index, native_material, data):
     offset = native_material["nuclide_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -22,7 +23,7 @@ def nuclide_IDs_last(native_material, data):
     start = native_material["nuclide_IDs_offset"]
     size = native_material["N_nuclide"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -35,7 +36,7 @@ def nuclide_IDs_chunk(start, length, native_material, data):
 @njit
 def element_IDs(index, native_material, data):
     offset = native_material["element_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -51,7 +52,7 @@ def element_IDs_last(native_material, data):
     start = native_material["element_IDs_offset"]
     size = native_material["N_element"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/neutron_inelastic_scattering_reaction.py b/mcdc/mcdc_get/neutron_inelastic_scattering_reaction.py
index 5cf2f0dd4..de62aafda 100644
--- a/mcdc/mcdc_get/neutron_inelastic_scattering_reaction.py
+++ b/mcdc/mcdc_get/neutron_inelastic_scattering_reaction.py
@@ -1,5 +1,6 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
@@ -58,7 +59,7 @@ def spectrum_probability_chunk(start, length, neutron_inelastic_scattering_react
 @njit
 def energy_spectrum_IDs(index, neutron_inelastic_scattering_reaction, data):
     offset = neutron_inelastic_scattering_reaction["energy_spectrum_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -74,7 +75,7 @@ def energy_spectrum_IDs_last(neutron_inelastic_scattering_reaction, data):
     start = neutron_inelastic_scattering_reaction["energy_spectrum_IDs_offset"]
     size = neutron_inelastic_scattering_reaction["N_energy_spectrum"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/nuclide.py b/mcdc/mcdc_get/nuclide.py
index af9593f10..63496f6da 100644
--- a/mcdc/mcdc_get/nuclide.py
+++ b/mcdc/mcdc_get/nuclide.py
@@ -1,5 +1,6 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
@@ -180,7 +181,7 @@ def neutron_fission_xs_chunk(start, length, nuclide, data):
 @njit
 def neutron_elastic_scattering_reaction_IDs(index, nuclide, data):
     offset = nuclide["neutron_elastic_scattering_reaction_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -196,7 +197,7 @@ def neutron_elastic_scattering_reaction_IDs_last(nuclide, data):
     start = nuclide["neutron_elastic_scattering_reaction_IDs_offset"]
     size = nuclide["N_neutron_elastic_scattering_reaction"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -209,7 +210,7 @@ def neutron_elastic_scattering_reaction_IDs_chunk(start, length, nuclide, data):
 @njit
 def neutron_capture_reaction_IDs(index, nuclide, data):
     offset = nuclide["neutron_capture_reaction_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -225,7 +226,7 @@ def neutron_capture_reaction_IDs_last(nuclide, data):
     start = nuclide["neutron_capture_reaction_IDs_offset"]
     size = nuclide["N_neutron_capture_reaction"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -238,7 +239,7 @@ def neutron_capture_reaction_IDs_chunk(start, length, nuclide, data):
 @njit
 def neutron_inelastic_scattering_reaction_IDs(index, nuclide, data):
     offset = nuclide["neutron_inelastic_scattering_reaction_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -254,7 +255,7 @@ def neutron_inelastic_scattering_reaction_IDs_last(nuclide, data):
     start = nuclide["neutron_inelastic_scattering_reaction_IDs_offset"]
     size = nuclide["N_neutron_inelastic_scattering_reaction"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -267,7 +268,7 @@ def neutron_inelastic_scattering_reaction_IDs_chunk(start, length, nuclide, data
 @njit
 def neutron_fission_reaction_IDs(index, nuclide, data):
     offset = nuclide["neutron_fission_reaction_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -283,7 +284,7 @@ def neutron_fission_reaction_IDs_last(nuclide, data):
     start = nuclide["neutron_fission_reaction_IDs_offset"]
     size = nuclide["N_neutron_fission_reaction"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -354,7 +355,7 @@ def neutron_fission_delayed_decay_rates_chunk(start, length, nuclide, data):
 @njit
 def neutron_fission_delayed_spectrum_IDs(index, nuclide, data):
     offset = nuclide["neutron_fission_delayed_spectrum_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -370,7 +371,7 @@ def neutron_fission_delayed_spectrum_IDs_last(nuclide, data):
     start = nuclide["neutron_fission_delayed_spectrum_IDs_offset"]
     size = nuclide["N_neutron_fission_delayed_spectrum"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/surface.py b/mcdc/mcdc_get/surface.py
index 68cb8e2a5..4e6c1c65e 100644
--- a/mcdc/mcdc_get/surface.py
+++ b/mcdc/mcdc_get/surface.py
@@ -1,5 +1,6 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
@@ -110,7 +111,7 @@ def move_translations_chunk(start, length, surface, data):
 @njit
 def surface_crossing_tally_IDs(index, surface, data):
     offset = surface["surface_crossing_tally_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -126,7 +127,7 @@ def surface_crossing_tally_IDs_last(surface, data):
     start = surface["surface_crossing_tally_IDs_offset"]
     size = surface["N_surface_crossing_tally"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/table_data.py b/mcdc/mcdc_get/table_data.py
index db53747eb..8b3d1b54a 100644
--- a/mcdc/mcdc_get/table_data.py
+++ b/mcdc/mcdc_get/table_data.py
@@ -1,5 +1,6 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
@@ -64,7 +65,7 @@ def y_chunk(start, length, table_data, data):
 @njit
 def interpolations(index, table_data, data):
     offset = table_data["interpolations_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -80,7 +81,7 @@ def interpolations_last(table_data, data):
     start = table_data["interpolations_offset"]
     size = table_data["interpolations_length"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -93,7 +94,7 @@ def interpolations_chunk(start, length, table_data, data):
 @njit
 def interpolation_boundaries(index, table_data, data):
     offset = table_data["interpolation_boundaries_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -109,7 +110,7 @@ def interpolation_boundaries_last(table_data, data):
     start = table_data["interpolation_boundaries_offset"]
     size = table_data["interpolation_boundaries_length"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/tabulated_energy_angle_distribution.py b/mcdc/mcdc_get/tabulated_energy_angle_distribution.py
index aeb1fe914..9aff254b5 100644
--- a/mcdc/mcdc_get/tabulated_energy_angle_distribution.py
+++ b/mcdc/mcdc_get/tabulated_energy_angle_distribution.py
@@ -1,5 +1,6 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
@@ -35,7 +36,7 @@ def energy_chunk(start, length, tabulated_energy_angle_distribution, data):
 @njit
 def offset(index, tabulated_energy_angle_distribution, data):
     offset = tabulated_energy_angle_distribution["offset_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -51,7 +52,7 @@ def offset_last(tabulated_energy_angle_distribution, data):
     start = tabulated_energy_angle_distribution["offset_offset"]
     size = tabulated_energy_angle_distribution["offset_length"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -151,7 +152,7 @@ def cdf_chunk(start, length, tabulated_energy_angle_distribution, data):
 @njit
 def cosine_offset_(index, tabulated_energy_angle_distribution, data):
     offset = tabulated_energy_angle_distribution["cosine_offset__offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -167,7 +168,7 @@ def cosine_offset__last(tabulated_energy_angle_distribution, data):
     start = tabulated_energy_angle_distribution["cosine_offset__offset"]
     size = tabulated_energy_angle_distribution["cosine_offset__length"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/tally.py b/mcdc/mcdc_get/tally.py
index dbf02745f..5556883c1 100644
--- a/mcdc/mcdc_get/tally.py
+++ b/mcdc/mcdc_get/tally.py
@@ -1,12 +1,13 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
 @njit
 def scores(index, tally, data):
     offset = tally["scores_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -22,7 +23,7 @@ def scores_last(tally, data):
     start = tally["scores_offset"]
     size = tally["scores_length"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
@@ -238,7 +239,7 @@ def bin_sum_square_chunk(start, length, tally, data):
 @njit
 def bin_shape(index, tally, data):
     offset = tally["bin_shape_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -254,7 +255,7 @@ def bin_shape_last(tally, data):
     start = tally["bin_shape_offset"]
     size = tally["bin_shape_length"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/mcdc_get/universe.py b/mcdc/mcdc_get/universe.py
index 5bfcf612d..f7822ed22 100644
--- a/mcdc/mcdc_get/universe.py
+++ b/mcdc/mcdc_get/universe.py
@@ -1,12 +1,13 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
 
 
 @njit
 def cell_IDs(index, universe, data):
     offset = universe["cell_IDs_offset"]
-    return data[offset + index]
+    return int64(data[offset + index])
 
 
 @njit
@@ -22,7 +23,7 @@ def cell_IDs_last(universe, data):
     start = universe["cell_IDs_offset"]
     size = universe["N_cell"]
     end = start + size
-    return data[end - 1]
+    return int64(data[end - 1])
 
 
 @njit
diff --git a/mcdc/transport/distribution.py b/mcdc/transport/distribution.py
index a91579f80..190f3ae04 100644
--- a/mcdc/transport/distribution.py
+++ b/mcdc/transport/distribution.py
@@ -332,7 +332,7 @@ def _sample_multi_table(E, rng_state, multi_table, simulation, data, scale):
             use_next_table = True  # For scaling later if needed
 
     # Sample from the selected table
-    ID = int(mcdc_get.multi_table_distribution.table_IDs(idx, multi_table, data))
+    ID = mcdc_get.multi_table_distribution.table_IDs(idx, multi_table, data)
     sub_ID = simulation["distributions"][ID]["sub_ID"]
     table_distribution = simulation["tabulated_distributions"][sub_ID]
     sample = sample_tabulated(table_distribution, rng_state, simulation, data)
@@ -346,8 +346,8 @@ def _sample_multi_table(E, rng_state, multi_table, simulation, data, scale):
         idx -= 1
 
     # PDF tables
-    ID0 = int(mcdc_get.multi_table_distribution.table_IDs(idx, multi_table, data))
-    ID1 = int(mcdc_get.multi_table_distribution.table_IDs(idx + 1, multi_table, data))
+    ID0 = mcdc_get.multi_table_distribution.table_IDs(idx, multi_table, data)
+    ID1 = mcdc_get.multi_table_distribution.table_IDs(idx + 1, multi_table, data)
     #
     sub_ID0 = simulation["distributions"][ID0]["sub_ID"]
     sub_ID1 = simulation["distributions"][ID1]["sub_ID"]
@@ -462,8 +462,8 @@ def sample_kalbach_mann(E, rng_state, kalbach_mann, data):
     # ==================================================================================
 
     # First table
-    start = int(mcdc_get.kalbach_mann_distribution.offset(idx, kalbach_mann, data))
-    end = int(mcdc_get.kalbach_mann_distribution.offset(idx + 1, kalbach_mann, data))
+    start = mcdc_get.kalbach_mann_distribution.offset(idx, kalbach_mann, data)
+    end = mcdc_get.kalbach_mann_distribution.offset(idx + 1, kalbach_mann, data)
     E0_min = mcdc_get.kalbach_mann_distribution.energy_out(start, kalbach_mann, data)
     E0_max = mcdc_get.kalbach_mann_distribution.energy_out(end - 1, kalbach_mann, data)
 
@@ -472,9 +472,7 @@ def sample_kalbach_mann(E, rng_state, kalbach_mann, data):
     if idx + 2 == len(grid):
         end = kalbach_mann["energy_length"]
     else:
-        end = int(
-            mcdc_get.kalbach_mann_distribution.offset(idx + 2, kalbach_mann, data)
-        )
+        end = mcdc_get.kalbach_mann_distribution.offset(idx + 2, kalbach_mann, data)
     E1_min = mcdc_get.kalbach_mann_distribution.energy_out(start, kalbach_mann, data)
     E1_max = mcdc_get.kalbach_mann_distribution.energy_out(end - 1, kalbach_mann, data)
 
@@ -487,13 +485,11 @@ def sample_kalbach_mann(E, rng_state, kalbach_mann, data):
         idx += 1
 
     # Get the table range
-    start = int(mcdc_get.kalbach_mann_distribution.offset(idx, kalbach_mann, data))
+    start = mcdc_get.kalbach_mann_distribution.offset(idx, kalbach_mann, data)
     if idx + 1 == len(grid):
         end = kalbach_mann["energy_length"]
     else:
-        end = int(
-            mcdc_get.kalbach_mann_distribution.offset(idx + 1, kalbach_mann, data)
-        )
+        end = mcdc_get.kalbach_mann_distribution.offset(idx + 1, kalbach_mann, data)
     size = end - start
 
     # The CDF
@@ -569,8 +565,8 @@ def sample_tabulated_energy_angle(E, rng_state, table, data):
     # ==================================================================================
 
     # First table
-    start = int(mcdc_get.tabulated_energy_angle_distribution.offset(idx, table, data))
-    end = int(mcdc_get.tabulated_energy_angle_distribution.offset(idx + 1, table, data))
+    start = mcdc_get.tabulated_energy_angle_distribution.offset(idx, table, data)
+    end = mcdc_get.tabulated_energy_angle_distribution.offset(idx + 1, table, data)
     E0_min = mcdc_get.tabulated_energy_angle_distribution.energy_out(start, table, data)
     E0_max = mcdc_get.tabulated_energy_angle_distribution.energy_out(
         end - 1, table, data
@@ -581,9 +577,7 @@ def sample_tabulated_energy_angle(E, rng_state, table, data):
     if idx + 2 == len(grid):
         end = table["energy_length"]
     else:
-        end = int(
-            mcdc_get.tabulated_energy_angle_distribution.offset(idx + 2, table, data)
-        )
+        end = mcdc_get.tabulated_energy_angle_distribution.offset(idx + 2, table, data)
     E1_min = mcdc_get.tabulated_energy_angle_distribution.energy_out(start, table, data)
     E1_max = mcdc_get.tabulated_energy_angle_distribution.energy_out(
         end - 1, table, data
@@ -598,13 +592,11 @@ def sample_tabulated_energy_angle(E, rng_state, table, data):
         idx += 1
 
     # Get the table range
-    start = int(mcdc_get.tabulated_energy_angle_distribution.offset(idx, table, data))
+    start = mcdc_get.tabulated_energy_angle_distribution.offset(idx, table, data)
     if idx + 1 == len(grid):
         end = table["energy_length"]
     else:
-        end = int(
-            mcdc_get.tabulated_energy_angle_distribution.offset(idx + 1, table, data)
-        )
+        end = mcdc_get.tabulated_energy_angle_distribution.offset(idx + 1, table, data)
     size = end - start
 
     # The CDF
@@ -649,16 +641,14 @@ def sample_tabulated_energy_angle(E, rng_state, table, data):
         idx += 1
 
     # Get the angular table range
-    start = int(
-        mcdc_get.tabulated_energy_angle_distribution.cosine_offset_(idx, table, data)
+    start = mcdc_get.tabulated_energy_angle_distribution.cosine_offset_(
+        idx, table, data
     )
     if idx + 1 == len(grid):
         end = table["cosine_length"]
     else:
-        end = int(
-            mcdc_get.tabulated_energy_angle_distribution.cosine_offset_(
-                idx + 1, table, data
-            )
+        end = mcdc_get.tabulated_energy_angle_distribution.cosine_offset_(
+            idx + 1, table, data
         )
     size = end - start
 
diff --git a/mcdc/transport/geometry/interface.py b/mcdc/transport/geometry/interface.py
index f4c92ac56..55f844ddc 100644
--- a/mcdc/transport/geometry/interface.py
+++ b/mcdc/transport/geometry/interface.py
@@ -129,9 +129,7 @@ def inspect_geometry(particle_container, simulation, data):
                 if ix == -1 or iy == -1 or iz == -1:
                     event = EVENT_LOST
                     continue
-                universe_ID = int(
-                    mcdc_get.lattice.universe_IDs(ix, iy, iz, lattice, data)
-                )
+                universe_ID = mcdc_get.lattice.universe_IDs(ix, iy, iz, lattice, data)
 
                 # Lattice-translate the particle
                 particle["x"] -= lattice["x0"] + (ix + 0.5) * lattice["dx"]
@@ -239,9 +237,7 @@ def locate_particle(particle_container, simulation, data):
                 if ix == -1 or iy == -1 or iz == -1:
                     particle_is_lost = True
                     continue
-                universe_ID = int(
-                    mcdc_get.lattice.universe_IDs(ix, iy, iz, lattice, data)
-                )
+                universe_ID = mcdc_get.lattice.universe_IDs(ix, iy, iz, lattice, data)
 
                 # Lattice-translate the particle
                 particle["x"] -= lattice["x0"] + (ix + 0.5) * lattice["dx"]
@@ -347,7 +343,7 @@ def get_cell(particle_container, universe_ID, simulation, data):
 
     # Check over all cells in the universe
     for i in range(universe["N_cell"]):
-        cell_ID = int(mcdc_get.universe.cell_IDs(i, universe, data))
+        cell_ID = mcdc_get.universe.cell_IDs(i, universe, data)
         cell = simulation["cells"][cell_ID]
         if check_cell(particle_container, cell, simulation, data):
             return cell_ID
@@ -377,7 +373,7 @@ def check_cell(particle_container, cell, simulation, data):
 
     # March forward through RPN tokens
     for idx in range(N_token):
-        token = int(mcdc_get.cell.region_RPN_tokens(idx, cell, data))
+        token = mcdc_get.cell.region_RPN_tokens(idx, cell, data)
 
         if token >= 0:
             surface = simulation["surfaces"][token]
@@ -435,7 +431,7 @@ def distance_to_nearest_surface(particle_container, cell, simulation, data):
 
     # Iterate over all surfaces and find the minimum distance
     for i in range(cell["N_surface"]):
-        candidate_surface_ID = int(mcdc_get.cell.surface_IDs(i, cell, data))
+        candidate_surface_ID = mcdc_get.cell.surface_IDs(i, cell, data)
         surface = simulation["surfaces"][candidate_surface_ID]
         d = get_distance(particle_container, speed, surface, data)
         if d < distance:
diff --git a/mcdc/transport/physics/electron/native.py b/mcdc/transport/physics/electron/native.py
index 170add771..0865fc57c 100644
--- a/mcdc/transport/physics/electron/native.py
+++ b/mcdc/transport/physics/electron/native.py
@@ -58,7 +58,7 @@ def macro_xs(reaction_type, particle_container, simulation, data):
 
     total = 0.0
     for i in range(material["N_element"]):
-        element_ID = int(mcdc_get.native_material.element_IDs(i, material, data))
+        element_ID = mcdc_get.native_material.element_IDs(i, material, data)
         element = simulation["elements"][element_ID]
 
         element_density = mcdc_get.native_material.element_densities(i, material, data)
@@ -136,7 +136,7 @@ def collision(particle_container, collision_data_container, program, data):
     xi = rng.lcg(particle_container) * SigmaT
     total = 0.0
     for i in range(material["N_element"]):
-        element_ID = int(mcdc_get.native_material.element_IDs(i, material, data))
+        element_ID = mcdc_get.native_material.element_IDs(i, material, data)
         element = simulation["elements"][element_ID]
 
         element_density = mcdc_get.native_material.element_densities(i, material, data)
@@ -168,8 +168,8 @@ def collision(particle_container, collision_data_container, program, data):
     if xi < total:
         total -= sigma_ionization
         for i in range(element["N_electron_ionization_reaction"]):
-            reaction_ID = int(
-                mcdc_get.element.electron_ionization_reaction_IDs(i, element, data)
+            reaction_ID = mcdc_get.element.electron_ionization_reaction_IDs(
+                i, element, data
             )
             reaction = simulation["electron_reactions"][reaction_ID]
             total += reaction_micro_xs(E, reaction, element, data)
@@ -190,10 +190,8 @@ def collision(particle_container, collision_data_container, program, data):
     if xi < total:
         total -= sigma_elastic
         for i in range(element["N_electron_elastic_scattering_reaction"]):
-            reaction_ID = int(
-                mcdc_get.element.electron_elastic_scattering_reaction_IDs(
-                    i, element, data
-                )
+            reaction_ID = mcdc_get.element.electron_elastic_scattering_reaction_IDs(
+                i, element, data
             )
             reaction = simulation["electron_reactions"][reaction_ID]
             total += reaction_micro_xs(E, reaction, element, data)
@@ -209,8 +207,8 @@ def collision(particle_container, collision_data_container, program, data):
     if xi < total:
         total -= sigma_bremsstrahlung
         for i in range(element["N_electron_bremsstrahlung_reaction"]):
-            reaction_ID = int(
-                mcdc_get.element.electron_bremsstrahlung_reaction_IDs(i, element, data)
+            reaction_ID = mcdc_get.element.electron_bremsstrahlung_reaction_IDs(
+                i, element, data
             )
             reaction = simulation["electron_reactions"][reaction_ID]
             total += reaction_micro_xs(E, reaction, element, data)
@@ -230,8 +228,8 @@ def collision(particle_container, collision_data_container, program, data):
     if xi < total:
         total -= sigma_excitation
         for i in range(element["N_electron_excitation_reaction"]):
-            reaction_ID = int(
-                mcdc_get.element.electron_excitation_reaction_IDs(i, element, data)
+            reaction_ID = mcdc_get.element.electron_excitation_reaction_IDs(
+                i, element, data
             )
             reaction = simulation["electron_reactions"][reaction_ID]
             total += reaction_micro_xs(E, reaction, element, data)
@@ -443,8 +441,8 @@ def sample_ionization(
     N = int(ionization["N_subshell"])
     total = 0.0
     for i in range(N):
-        xs_sub_ID = int(
-            mcdc_get.electron_ionization_reaction.subshell_x_IDs(i, ionization, data)
+        xs_sub_ID = mcdc_get.electron_ionization_reaction.subshell_x_IDs(
+            i, ionization, data
         )
         xs_sub_table = simulation["data"][xs_sub_ID]
         total += evaluate_data(E, xs_sub_table, simulation, data)
@@ -453,8 +451,8 @@ def sample_ionization(
     total_acc = 0.0
     chosen = 0
     for i in range(N):
-        xs_sub_ID = int(
-            mcdc_get.electron_ionization_reaction.subshell_x_IDs(i, ionization, data)
+        xs_sub_ID = mcdc_get.electron_ionization_reaction.subshell_x_IDs(
+            i, ionization, data
         )
         xs_sub_table = simulation["data"][xs_sub_ID]
         total_acc += evaluate_data(E, xs_sub_table, simulation, data)
@@ -473,10 +471,8 @@ def sample_ionization(
         return
 
     # Sample secondary energy
-    dist_ID = int(
-        mcdc_get.electron_ionization_reaction.subshell_product_IDs(
-            chosen, ionization, data
-        )
+    dist_ID = mcdc_get.electron_ionization_reaction.subshell_product_IDs(
+        chosen, ionization, data
     )
     T_dist = simulation["distributions"][dist_ID]
     T_delta = sample_distribution(E, T_dist, particle_container, simulation, data)
diff --git a/mcdc/transport/physics/neutron/native.py b/mcdc/transport/physics/neutron/native.py
index 916b290e6..4aea35069 100644
--- a/mcdc/transport/physics/neutron/native.py
+++ b/mcdc/transport/physics/neutron/native.py
@@ -78,7 +78,7 @@ def macro_xs(reaction_type, particle_container, simulation, data):
     total = 0.0
 
     for i in range(material["N_nuclide"]):
-        nuclide_ID = int(mcdc_get.native_material.nuclide_IDs(i, material, data))
+        nuclide_ID = mcdc_get.native_material.nuclide_IDs(i, material, data)
         nuclide = simulation["nuclides"][nuclide_ID]
 
         nuclide_density = mcdc_get.native_material.nuclide_densities(i, material, data)
@@ -176,17 +176,15 @@ def _neutron_inelastic_scattering_production_xs(particle_container, simulation,
 
     total = 0.0
     for i in range(material["N_nuclide"]):
-        nuclide_ID = int(mcdc_get.native_material.nuclide_IDs(i, material, data))
+        nuclide_ID = mcdc_get.native_material.nuclide_IDs(i, material, data)
         nuclide = simulation["nuclides"][nuclide_ID]
 
         E = particle["E"]
         nuclide_density = mcdc_get.native_material.nuclide_densities(i, material, data)
 
         for j in range(nuclide["N_neutron_inelastic_scattering_reaction"]):
-            reaction_ID = int(
-                mcdc_get.nuclide.neutron_inelastic_scattering_reaction_IDs(
-                    j, nuclide, data
-                )
+            reaction_ID = mcdc_get.nuclide.neutron_inelastic_scattering_reaction_IDs(
+                j, nuclide, data
             )
             reaction = simulation["neutron_reactions"][reaction_ID]
             inelastic_scattering = simulation["neutron_inelastic_scattering_reactions"][
@@ -211,7 +209,7 @@ def _neutron_fission_production_xs(particle_container, simulation, data):
 
     total = 0.0
     for i in range(material["N_nuclide"]):
-        nuclide_ID = int(mcdc_get.native_material.nuclide_IDs(i, material, data))
+        nuclide_ID = mcdc_get.native_material.nuclide_IDs(i, material, data)
         nuclide = simulation["nuclides"][nuclide_ID]
         if not nuclide["fissionable"]:
             continue
@@ -220,8 +218,8 @@ def _neutron_fission_production_xs(particle_container, simulation, data):
         nuclide_density = mcdc_get.native_material.nuclide_densities(i, material, data)
 
         for j in range(nuclide["N_neutron_fission_reaction"]):
-            reaction_ID = int(
-                mcdc_get.nuclide.neutron_fission_reaction_IDs(j, nuclide, data)
+            reaction_ID = mcdc_get.nuclide.neutron_fission_reaction_IDs(
+                j, nuclide, data
             )
             reaction = simulation["neutron_reactions"][reaction_ID]
 
@@ -268,14 +266,14 @@ def collision(particle_container, collision_data_container, program, data):
 
         # Q-value: xs-weighted average over all nuclides and capture reactions
         for i in range(material["N_nuclide"]):
-            nuclide_ID = int(mcdc_get.native_material.nuclide_IDs(i, material, data))
+            nuclide_ID = mcdc_get.native_material.nuclide_IDs(i, material, data)
             nuclide = simulation["nuclides"][nuclide_ID]
             nuclide_density = mcdc_get.native_material.nuclide_densities(
                 i, material, data
             )
             for j in range(nuclide["N_neutron_capture_reaction"]):
-                reaction_ID = int(
-                    mcdc_get.nuclide.neutron_capture_reaction_IDs(j, nuclide, data)
+                reaction_ID = mcdc_get.nuclide.neutron_capture_reaction_IDs(
+                    j, nuclide, data
                 )
                 reaction = simulation["neutron_reactions"][reaction_ID]
                 xs = reaction_micro_xs(E, reaction, nuclide, data)
@@ -293,7 +291,7 @@ def collision(particle_container, collision_data_container, program, data):
     xi = rng.lcg(particle_container) * SigmaT
     total = 0.0
     for i in range(material["N_nuclide"]):
-        nuclide_ID = int(mcdc_get.native_material.nuclide_IDs(i, material, data))
+        nuclide_ID = mcdc_get.native_material.nuclide_IDs(i, material, data)
         nuclide = simulation["nuclides"][nuclide_ID]
 
         nuclide_density = mcdc_get.native_material.nuclide_densities(i, material, data)
@@ -329,10 +327,8 @@ def collision(particle_container, collision_data_container, program, data):
         # Sample the actual reaction from the group
         total -= sigma_elastic
         for i in range(nuclide["N_neutron_elastic_scattering_reaction"]):
-            reaction_ID = int(
-                mcdc_get.nuclide.neutron_elastic_scattering_reaction_IDs(
-                    i, nuclide, data
-                )
+            reaction_ID = mcdc_get.nuclide.neutron_elastic_scattering_reaction_IDs(
+                i, nuclide, data
             )
             reaction = simulation["neutron_reactions"][reaction_ID]
             total += reaction_micro_xs(E, reaction, nuclide, data)
@@ -357,8 +353,8 @@ def collision(particle_container, collision_data_container, program, data):
             # Sample the actual reaction from the group
             total -= sigma_capture
             for i in range(nuclide["N_neutron_capture_reaction"]):
-                reaction_ID = int(
-                    mcdc_get.nuclide.neutron_capture_reaction_IDs(i, nuclide, data)
+                reaction_ID = mcdc_get.nuclide.neutron_capture_reaction_IDs(
+                    i, nuclide, data
                 )
                 reaction = simulation["neutron_reactions"][reaction_ID]
                 xs = reaction_micro_xs(E, reaction, nuclide, data)
@@ -382,10 +378,8 @@ def collision(particle_container, collision_data_container, program, data):
         # Sample the actual reaction from the group
         total -= sigma_inelastic
         for i in range(nuclide["N_neutron_inelastic_scattering_reaction"]):
-            reaction_ID = int(
-                mcdc_get.nuclide.neutron_inelastic_scattering_reaction_IDs(
-                    i, nuclide, data
-                )
+            reaction_ID = mcdc_get.nuclide.neutron_inelastic_scattering_reaction_IDs(
+                i, nuclide, data
             )
             reaction = simulation["neutron_reactions"][reaction_ID]
             xs = reaction_micro_xs(E, reaction, nuclide, data)
@@ -409,8 +403,8 @@ def collision(particle_container, collision_data_container, program, data):
         # Sample the actual reaction from the group
         total -= sigma_fission
         for i in range(nuclide["N_neutron_fission_reaction"]):
-            reaction_ID = int(
-                mcdc_get.nuclide.neutron_fission_reaction_IDs(i, nuclide, data)
+            reaction_ID = mcdc_get.nuclide.neutron_fission_reaction_IDs(
+                i, nuclide, data
             )
             reaction = simulation["neutron_reactions"][reaction_ID]
             total += reaction_micro_xs(E, reaction, nuclide, data)
@@ -659,10 +653,8 @@ def sample_inelastic_scattering(
 
         # Get energy spectrum
         if use_all_spectrum:
-            ID = int(
-                mcdc_get.neutron_inelastic_scattering_reaction.energy_spectrum_IDs(
-                    n, inelastic_scattering, data
-                )
+            ID = mcdc_get.neutron_inelastic_scattering_reaction.energy_spectrum_IDs(
+                n, inelastic_scattering, data
             )
             spectrum = simulation["distributions"][ID]
         else:
@@ -684,10 +676,8 @@ def sample_inelastic_scattering(
                 )
                 total += probability
                 if xi < total:
-                    ID = int(
-                        mcdc_get.neutron_inelastic_scattering_reaction.energy_spectrum_IDs(
-                            j, inelastic_scattering, data
-                        )
+                    ID = mcdc_get.neutron_inelastic_scattering_reaction.energy_spectrum_IDs(
+                        j, inelastic_scattering, data
                     )
                     spectrum = simulation["distributions"][ID]
                     break
diff --git a/mcdc/transport/simulation.py b/mcdc/transport/simulation.py
index 7d949acec..b630b681b 100644
--- a/mcdc/transport/simulation.py
+++ b/mcdc/transport/simulation.py
@@ -301,7 +301,7 @@ def step_particle(particle_container, program, data):
         if simulation["cycle_active"]:
             cell = simulation["cells"][particle["cell_ID"]]
             for i in range(cell["N_collision_tally"]):
-                tally_ID = int(mcdc_get.cell.collision_tally_IDs(i, cell, data))
+                tally_ID = mcdc_get.cell.collision_tally_IDs(i, cell, data)
                 tally = simulation["tallies"][tally_ID]
                 tally_module.score.collision(
                     particle_container,
@@ -430,7 +430,7 @@ def move_to_event(particle_container, simulation, data):
     if simulation["cycle_active"]:
         cell = simulation["cells"][particle["cell_ID"]]
         for i in range(cell["N_tracklength_tally"]):
-            tally_ID = int(mcdc_get.cell.tracklength_tally_IDs(i, cell, data))
+            tally_ID = mcdc_get.cell.tracklength_tally_IDs(i, cell, data)
             tally = simulation["tallies"][tally_ID]
             tally_module.score.tracklength(
                 particle_container, distance, tally, simulation, data
@@ -462,7 +462,7 @@ def surface_crossing(particle_container, simulation, data):
 
     # Score tally
     for i in range(surface["N_surface_crossing_tally"]):
-        tally_ID = int(mcdc_get.surface.surface_crossing_tally_IDs(i, surface, data))
+        tally_ID = mcdc_get.surface.surface_crossing_tally_IDs(i, surface, data)
         tally = simulation["tallies"][tally_ID]
         tally_module.score.surface_crossing(
             particle_container, surface, tally, simulation, data
diff --git a/test/unit/test_numba_layers_generator.py b/test/unit/test_numba_layers_generator.py
new file mode 100644
index 000000000..43f93884f
--- /dev/null
+++ b/test/unit/test_numba_layers_generator.py
@@ -0,0 +1,100 @@
+from typing import Annotated
+
+import numpy as np
+import pytest
+from numpy.typing import NDArray
+
+from mcdc.code_factory.numba_layers_generator import (
+    AccessorTarget,
+    _accessor_1d_all,
+    _accessor_1d_element,
+    _accessor_1d_last,
+    _accessor_2d_element,
+    _accessor_3d_element,
+    _accessor_4d_element,
+    set_structure,
+    validate_accessor_targets,
+)
+from mcdc.mcdc_get import cell as get_cell
+from mcdc.object_.surface import Surface
+
+
+def test_set_structure_tracks_logical_accessor_types():
+    annotations = {
+        "example": {
+            "integer_values": NDArray[np.int64],
+            "float_values": NDArray[np.float64],
+            "integer_grid": Annotated[NDArray[np.int64], ("Nx", "Ny", "Nz")],
+            "surfaces": list[Surface],
+        }
+    }
+    structures = {"example": []}
+    accessor_targets = {"example": []}
+
+    set_structure("example", structures, accessor_targets, annotations)
+
+    assert accessor_targets["example"] == [
+        ("integer_values", ("integer_values_length",), True),
+        ("float_values", ("float_values_length",), False),
+        ("integer_grid", ("Nx", "Ny", "Nz"), True),
+        ("surface_IDs", ("N_surface",), True),
+    ]
+
+
+def test_scalar_integer_getters_cast_values_from_data():
+    assert "return int64(data[offset + index])" in _accessor_1d_element(
+        "example", "values", cast_to_int=True
+    )
+    assert "return int64(data[end - 1])" in _accessor_1d_last(
+        "example", "values", "values_length", cast_to_int=True
+    )
+    assert "return int64(data[offset + index_1 * stride + index_2])" in (
+        _accessor_2d_element("example", "values", "Ny", cast_to_int=True)
+    )
+    assert "return int64(data[offset + index_1 * stride_2 * stride_3" in (
+        _accessor_3d_element("example", "values", "Ny", "Nz", cast_to_int=True)
+    )
+
+
+def test_float_and_bulk_getters_remain_zero_copy_views():
+    assert "return data[offset + index]" in _accessor_1d_element("example", "values")
+    assert "return data[start:end]" in _accessor_1d_all(
+        "example", "values", "values_length"
+    )
+
+
+def test_mixed_literal_and_named_strides_are_generated():
+    getter_3d = _accessor_3d_element("example", "values", 3, "Nz")
+    getter_4d = _accessor_4d_element("example", "values", 2, "Nz", 4)
+
+    assert "stride_2 = 3" in getter_3d
+    assert 'stride_3 = example["Nz"]' in getter_3d
+    assert "stride_2 = 2" in getter_4d
+    assert 'stride_3 = example["Nz"]' in getter_4d
+    assert "stride_4 = 4" in getter_4d
+
+
+def test_unsupported_accessor_rank_is_rejected_before_generation():
+    targets = {
+        "example": [AccessorTarget("values", ("N1", "N2", "N3", "N4", "N5"), False)]
+    }
+
+    with pytest.raises(ValueError, match="one through four dimensions"):
+        validate_accessor_targets(targets)
+
+
+def test_generated_integer_getter_returns_int_and_bulk_getter_returns_view():
+    cell = np.zeros(
+        1,
+        dtype=[("surface_IDs_offset", np.int64), ("N_surface", np.int64)],
+    )[0]
+    cell["N_surface"] = 2
+    data = np.array([3.0, 7.0])
+
+    surface_ID = get_cell.surface_IDs(1, cell, data)
+    surface_IDs = get_cell.surface_IDs_all(cell, data)
+
+    assert isinstance(surface_ID, (int, np.integer))
+    assert surface_ID == 7
+    assert surface_IDs.dtype == np.float64
+    assert np.shares_memory(surface_IDs, data)

From e3668d7d1f737a88dbb031086a80401778685f70 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 16:03:29 +0700
Subject: [PATCH 088/202] update transport exec dev doc

---
 .../developer_guide/architecture/index.rst    |   7 +-
 .../python_first_numba_accelerated_design.rst |  12 +-
 .../python_numba_cpu_execution.rst            | 123 ------------------
 .../architecture/runtime_data_layout.rst      |   3 +-
 ..._execution.rst => transport_execution.rst} |  31 +++--
 .../architecture/execution_modes.svg          |  43 ------
 docs/source/user_guide/execution/cpu.rst      |   2 +-
 docs/source/user_guide/execution/gpu.rst      |   2 +-
 8 files changed, 31 insertions(+), 192 deletions(-)
 delete mode 100644 docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
 rename docs/source/developer_guide/architecture/{numba_gpu_execution.rst => transport_execution.rst} (87%)
 delete mode 100644 docs/source/images/developer_guide/architecture/execution_modes.svg

diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index 954463ae0..9d86a9c2a 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -19,7 +19,7 @@ The flow has three major processing stages:
 #. **Runtime preparation** converts the compiled model into the structured ``simulation`` state and flat ``data`` array consumed by transport.
    :doc:`runtime_data_layout` explains this numerical representation and its generated access helpers, ``mcdc_get`` and ``mcdc_set``.
 #. **Transport execution** runs the common, adaptable transport implementation in the selected execution mode.
-   :doc:`python_numba_cpu_execution` describes Python and Numba-CPU execution, while :doc:`numba_gpu_execution` continues into GPU code generation, memory placement, and Harmonize scheduling.
+   :doc:`transport_execution` explains how Python, Numba-CPU, and Numba-GPU execute it, including GPU code generation, memory placement, and Harmonize scheduling.
 
 Visit :doc:`python_first_numba_accelerated_design` for the rationale, boundaries, and tradeoffs that shape MC/DC's architecture.
 It explains why method development begins in unrestricted Python mode and may progress through Numba-CPU to Numba-GPU.
@@ -72,7 +72,7 @@ The ``numba_layers_generator.py``, runtime ``simulation`` and ``data``, and gene
 :doc:`runtime_data_layout` explains their roles.
 
 The ``mcdc/transport`` package implements the shared-transport stage.
-:doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution` explain how the execution modes run it.
+:doc:`transport_execution` explains how the execution modes run it.
 :doc:`../extending/writing_numba_compatible_transport_code` provides practical rules for extending its algorithms.
 
 .. toctree::
@@ -82,5 +82,4 @@ The ``mcdc/transport`` package implements the shared-transport stage.
    python_first_numba_accelerated_design
    simulation_compilation
    runtime_data_layout
-   python_numba_cpu_execution
-   numba_gpu_execution
+   transport_execution
diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
index fe759c675..fed3c8571 100644
--- a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -67,14 +67,14 @@ Numba-CPU Compilation
 
 Once the method is verified and larger calculations require more performance, it can be adapted for Numba-CPU.
 Unless the Python implementation was already written against the compatible subset, reaching this stage requires deliberate porting rather than simply changing an execution option.
-See :doc:`python_numba_cpu_execution` for the execution path and :doc:`../extending/writing_numba_compatible_transport_code` for the practical porting requirements.
+See :doc:`transport_execution` for the execution architecture and :doc:`../extending/writing_numba_compatible_transport_code` for the practical porting requirements.
 
 Numba-GPU Compilation
 ^^^^^^^^^^^^^^^^^^^^^
 
 GPU execution is a further stage with additional hardware constraints.
 Some code that works with Numba-CPU therefore requires further adaptation before it can execute on a GPU.
-These additional layers are described in :doc:`numba_gpu_execution`.
+These additional layers are described in :doc:`transport_execution`.
 
 Valid Stopping Points
 ^^^^^^^^^^^^^^^^^^^^^
@@ -121,7 +121,7 @@ What changes between development stages is how transport runs and which Python f
 Model construction and preparation may use object-oriented interfaces, variable-length collections, validation, and other expressive Python features.
 Transport in the Python backend may also use ordinary Python facilities beyond the prepared execution data.
 The accelerated backends require predictable numerical data and explicit behavior.
-See :doc:`simulation_compilation` and :doc:`runtime_data_layout` for the two preparation stages, then :doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution` for backend execution.
+See :doc:`simulation_compilation` and :doc:`runtime_data_layout` for the two preparation stages, then :doc:`transport_execution` for execution.
 
 Architectural Consequences
 --------------------------
@@ -140,7 +140,7 @@ Contributor guidance belongs in :doc:`../extending/writing_numba_compatible_tran
 
 **CPU and GPU share a portable core.**
 Common transport algorithms use behavior supported by both accelerated targets, while hardware-specific concerns remain isolated.
-The two execution paths are described in :doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`.
+The execution modes are described in :doc:`transport_execution`.
 
 Design Tradeoffs
 ----------------
@@ -153,7 +153,7 @@ Beginning with simple numerical data and operations that Numba supports can redu
 
 Portability also increases compiler, backend, and validation work.
 MC/DC accepts these costs so that maintained features can share transport logic across Python, CPU, and GPU execution rather than becoming separate implementations that may drift apart.
-Practical constraints are covered in :doc:`../extending/writing_numba_compatible_transport_code`; backend-specific costs are covered in :doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`.
+Practical constraints are covered in :doc:`../extending/writing_numba_compatible_transport_code`; mode-specific execution mechanisms are covered in :doc:`transport_execution`.
 
 Related Design Choices
 ----------------------
@@ -187,5 +187,5 @@ Where to Go Next
 ----------------
 
 For model preparation, continue with :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
-For execution, read :doc:`python_numba_cpu_execution` and :doc:`numba_gpu_execution`.
+For execution, read :doc:`transport_execution`.
 Contributors implementing a transport change should use :doc:`../extending/writing_numba_compatible_transport_code`.
diff --git a/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst b/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
deleted file mode 100644
index a045a9cd9..000000000
--- a/docs/source/developer_guide/architecture/python_numba_cpu_execution.rst
+++ /dev/null
@@ -1,123 +0,0 @@
-.. _python_numba_cpu_execution:
-
-==============================
-Python and Numba-CPU Execution
-==============================
-
-MC/DC uses one transport implementation for both Python and Numba-CPU execution.
-The Python path is the conceptual baseline: it is the easiest mode to inspect and debug, and it establishes the behavior that the accelerated path preserves.
-
-Both modes operate on the same packed :doc:`runtime_data_layout` and call the same functions under ``mcdc/transport``.
-The difference is whether Numba executes functions decorated with ``@njit`` as ordinary Python functions or compiles them for the CPU.
-
-Shared Preparation
-------------------
-
-Before transport begins, both modes follow the same preparation path:
-
-#. :class:`mcdc.Simulation` compiles the reachable Python object graph.
-#. ``mcdc.main.prepare`` derives run-dependent values such as particle-bank sizes and physics-mode selections.
-#. ``mcdc.code_factory`` builds the structured ``simulation`` state and flat ``data`` array.
-#. Generated ``mcdc_get`` and ``mcdc_set`` helpers provide transport-safe access to variable-length fields.
-#. The fixed-source or k-eigenvalue driver calls the transport kernels.
-
-This shared preparation is why Python mode can expose the same data-layout and transport behavior as Numba mode without maintaining a separate reference implementation.
-
-.. image:: ../../images/developer_guide/architecture/execution_modes.svg
-   :width: 100%
-   :alt: Shared MC/DC preparation feeding Python, Numba-CPU, and Numba-GPU execution.
-
-Python Mode
------------
-
-Python mode is the default:
-
-.. code-block:: sh
-
-   python input.py --mode=python
-
-In this mode, MC/DC sets ``numba.config.DISABLE_JIT``.
-Functions decorated with ``@njit`` therefore execute through Python while retaining the same signatures and packed runtime inputs used by accelerated execution.
-
-Python mode is best for:
-
-- Prototyping, developing, and inspecting transport logic.
-- Checking model construction and object compilation.
-- Obtaining ordinary Python tracebacks.
-- Running small smoke tests before enabling acceleration.
-
-Python mode does not bypass simulation compilation or runtime packing.
-It bypasses machine-code generation for the CPU transport functions.
-
-Python Prototyping
-^^^^^^^^^^^^^^^^^^
-
-The standard MC/DC Python execution path is also the environment for initial methods development.
-A prototype remains a complete MC/DC calculation and does not bypass model compilation, runtime preparation, or transport.
-Because JIT compilation is disabled, its transport code may temporarily access arbitrary Python objects or global state, import external packages, perform I/O or visualization, and use hard-coded or dynamic behavior.
-
-These freedoms do not form a separate execution architecture.
-Advancing the method to Numba-CPU requires adapting the parts used by accelerated transport to the packed runtime representation and compiler-compatible interfaces.
-
-Before Numba Acceleration
--------------------------
-
-At the transition from an MC/DC-Python-only method to Numba acceleration, :doc:`python_first_numba_accelerated_design` is the main conceptual guide.
-It explains why MC/DC converts its flexible Python model into typed runtime data, which parts remain shared across execution backends, and which constraints follow from supporting Numba-CPU and Numba-GPU.
-
-If you have not already read that design page as an overview, read it before continuing when developing MC/DC or studying its acceleration architecture.
-Readers who only need the mechanics of the Python and Numba-CPU modes may continue directly below.
-
-Numba-CPU Mode
---------------
-
-Numba-CPU mode enables just-in-time compilation:
-
-.. code-block:: sh
-
-   python input.py --mode=numba
-
-The target defaults to ``cpu``.
-Numba specializes the shared transport functions for the structured simulation dtype, flat data array, particle records, and other argument types encountered during execution.
-The initial run therefore includes compilation work; subsequent transport work uses the compiled functions.
-
-The runtime representation is unchanged:
-
-.. list-table::
-   :header-rows: 1
-   :widths: 24 38 38
-
-   * - Concern
-     - Python mode
-     - Numba-CPU mode
-   * - Model ownership
-     - Explicit ``Simulation``
-     - Explicit ``Simulation``
-   * - Object-graph compilation
-     - Required
-     - Required
-   * - Packed ``simulation`` and ``data``
-     - Required
-     - Required
-   * - Transport implementation
-     - ``mcdc/transport``
-     - ``mcdc/transport``
-   * - ``@njit`` behavior
-     - JIT disabled
-     - Compiled for CPU
-
-Numba debug mode keeps JIT compilation enabled while adding bounds checking, fuller tracebacks, and compiler diagnostics:
-
-.. code-block:: sh
-
-   python input.py --mode=numba_debug
-
-Use the ordinary Python mode first to separate model or algorithm errors from Numba typing and compilation errors.
-For operational commands, MPI execution, and caching options, see :doc:`../../user_guide/execution/cpu`.
-For coding rules and a staged verification workflow, see :doc:`../extending/writing_numba_compatible_transport_code`.
-
-From CPU to GPU
----------------
-
-Numba-GPU execution retains the same Python model-compilation and runtime-layout concepts, then replaces the CPU execution backend with device compilation and Harmonize scheduling.
-Continue with :doc:`numba_gpu_execution` after the Python and Numba-CPU paths are clear.
diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index 3c9f8e7d6..065d8ef4c 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -237,5 +237,4 @@ Changing the prepared MC/DC model requires a new model compilation and runtime p
 Execution Backends
 ------------------
 
-Continue with :doc:`python_numba_cpu_execution` to see how Python mode and Numba-CPU mode consume this shared layout.
-GPU allocation and Harmonize integration are described in :doc:`numba_gpu_execution`.
+Continue with :doc:`transport_execution` to see how Python, Numba-CPU, and Numba-GPU consume this shared layout.
diff --git a/docs/source/developer_guide/architecture/numba_gpu_execution.rst b/docs/source/developer_guide/architecture/transport_execution.rst
similarity index 87%
rename from docs/source/developer_guide/architecture/numba_gpu_execution.rst
rename to docs/source/developer_guide/architecture/transport_execution.rst
index 27c879b4c..5a22023bc 100644
--- a/docs/source/developer_guide/architecture/numba_gpu_execution.rst
+++ b/docs/source/developer_guide/architecture/transport_execution.rst
@@ -1,25 +1,32 @@
-.. _numba_gpu_execution:
+.. _transport_execution:
 
 ===================
-Numba-GPU Execution
+Transport Execution
 ===================
 
-GPU execution is the final layer in MC/DC's execution model.
-MC/DC first compiles the Python model and creates the same logical runtime representation used on the CPU.
-It then adapts the transport functions for device execution, allocates or transfers runtime state, and uses Harmonize to schedule particle work.
+MC/DC uses one adaptable transport implementation with the runtime representation described in :doc:`runtime_data_layout`.
+The selected execution mode determines how that implementation runs after the common model-preparation stages.
+See :doc:`python_first_numba_accelerated_design` for the rationale behind this design.
 
-Read :doc:`simulation_compilation`, :doc:`runtime_data_layout`, and :doc:`python_numba_cpu_execution` first.
-This page focuses on the additional GPU-specific compilation and runtime machinery.
+Execution Modes
+---------------
+
+In **Python mode**, MC/DC disables Numba just-in-time (JIT) compilation, and functions decorated with ``@njit`` execute as ordinary Python functions.
+This mode provides the most inspectable execution of the shared transport implementation.
+
+In **Numba-CPU mode**, Numba specializes those transport functions for the prepared runtime types and compiles them into machine code for the host CPU.
+The first call includes compilation work, while subsequent calls use the compiled functions.
+
+In **Numba-GPU mode**, MC/DC adapts the transport functions for device execution, places runtime state in GPU-accessible memory, and uses Harmonize to schedule particle work.
+The remaining sections describe this additional GPU-specific compilation machinery.
+
+Contributor-facing constraints, porting guidance, and staged verification are discussed in in :doc:`../extending/writing_numba_compatible_transport_code`.
+Operational commands are detailed in the :doc:`../../user_guide/execution/index`.
 
 GPU Compilation
 ---------------
 
 When targeting GPUs, MC/DC functions are just-in-time (JIT) compiled with Numba and integrated with Harmonize.
-A GPU run selects Numba mode and the GPU target:
-
-.. code-block:: sh
-
-   python input.py --mode=numba --target=gpu
 
 When considered in totality the MC/DC+Numba+Harmonize JIT compilation structure is akin to "portability framework", in that it allows dynamic targeting and developer abstraction of hardware architectures, like OpenMP target-offloading used by OpenMC.
 This JIT compilation process allows MC/DC to pair the idea of a portability framework with a high-level language in an effort to enable more rapid methods development on Exascale systems.
diff --git a/docs/source/images/developer_guide/architecture/execution_modes.svg b/docs/source/images/developer_guide/architecture/execution_modes.svg
deleted file mode 100644
index 88e2a5513..000000000
--- a/docs/source/images/developer_guide/architecture/execution_modes.svg
+++ /dev/null
@@ -1,43 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="520" viewBox="0 0 1200 520" role="img" aria-labelledby="title desc">
-  <title id="title">Progressive MC/DC execution modes</title>
-  <desc id="desc">Shared model compilation, runtime packing, and transport functions feed Python-only execution first, Numba CPU compilation second, and Numba GPU device compilation with Harmonize third.</desc>
-  <defs>
-    <marker id="arrow" markerWidth="10" markerHeight="10" refX="8" refY="3" orient="auto">
-      <path d="M0,0 L0,6 L9,3 z" fill="#566573"/>
-    </marker>
-    <style>
-      .title { font-family: system-ui, sans-serif; font-size: 23px; font-weight: 700; fill: #17202a; }
-      .label { font-family: system-ui, sans-serif; font-size: 18px; font-weight: 650; fill: #17202a; }
-      .body { font-family: system-ui, sans-serif; font-size: 14px; fill: #273746; }
-      .box { stroke: #34495e; stroke-width: 2; rx: 10; }
-      .arrow { stroke: #566573; stroke-width: 3; fill: none; }
-    </style>
-  </defs>
-
-  <text x="600" y="35" text-anchor="middle" class="title">Add acceleration without changing model semantics</text>
-
-  <rect x="80" y="75" width="1040" height="85" class="box" fill="#fef9e7"/>
-  <text x="600" y="108" text-anchor="middle" class="label">Shared preparation</text>
-  <text x="600" y="135" text-anchor="middle" class="body">Simulation.compile → prepare → structured simulation + flat data → mcdc/transport</text>
-
-  <line x1="600" y1="160" x2="600" y2="195" style="stroke:#566573;stroke-width:3"/>
-
-  <rect x="110" y="205" width="980" height="75" class="box" fill="#eaf2f8"/>
-  <text x="285" y="237" text-anchor="middle" class="label">1 · Python-only</text>
-  <text x="680" y="237" text-anchor="middle" class="body">@njit functions execute with JIT disabled</text>
-  <text x="680" y="260" text-anchor="middle" class="body">inspectable baseline for model and algorithm development</text>
-
-  <line x1="600" y1="280" x2="600" y2="315" style="stroke:#566573;stroke-width:3"/>
-
-  <rect x="110" y="325" width="980" height="75" class="box" fill="#e8f8f5"/>
-  <text x="285" y="357" text-anchor="middle" class="label">2 · Numba-CPU</text>
-  <text x="680" y="357" text-anchor="middle" class="body">the same functions specialize to machine code for CPU types</text>
-  <text x="680" y="380" text-anchor="middle" class="body">the model, packed layout, and transport decisions stay the same</text>
-
-  <line x1="600" y1="400" x2="600" y2="435" style="stroke:#566573;stroke-width:3"/>
-
-  <rect x="110" y="445" width="980" height="60" class="box" fill="#f4ecf7"/>
-  <text x="285" y="481" text-anchor="middle" class="label">3 · Numba-GPU</text>
-  <text x="715" y="472" text-anchor="middle" class="body">adapt device functions and place runtime state on the GPU</text>
-  <text x="715" y="493" text-anchor="middle" class="body">Harmonize supplies scheduling and the NVIDIA/AMD integration layer</text>
-</svg>
diff --git a/docs/source/user_guide/execution/cpu.rst b/docs/source/user_guide/execution/cpu.rst
index 472cacf68..0522741b9 100644
--- a/docs/source/user_guide/execution/cpu.rst
+++ b/docs/source/user_guide/execution/cpu.rst
@@ -12,7 +12,7 @@ MPI can be quite tricky to configure if on an HPC; if you're having trouble,
 consult our :ref:`installation`, your HPC admin, or our `GitHub issues page <https://github.com/mcdc-project/mcdc/issues>`_.
 
 For the architectural relationship between Python and Numba-CPU execution, see
-:doc:`../../developer_guide/architecture/python_numba_cpu_execution`.
+:doc:`../../developer_guide/architecture/transport_execution`.
 
 Pure Python Mode
 ----------------
diff --git a/docs/source/user_guide/execution/gpu.rst b/docs/source/user_guide/execution/gpu.rst
index da98f8fea..a53baae2b 100644
--- a/docs/source/user_guide/execution/gpu.rst
+++ b/docs/source/user_guide/execution/gpu.rst
@@ -11,7 +11,7 @@ Harmonize acts as the GPU runtime for MC/DC and has two major scheduling schemes
 For more information on Harmonize and how we compile MC/DC with it see our publications in M&C 2025.
 
 For the developer-level compilation and runtime design, see
-:doc:`../../developer_guide/architecture/numba_gpu_execution`.
+:doc:`../../developer_guide/architecture/transport_execution`.
 
 Single GPU Launches
 -------------------

From 11690a818faf209564c19239382a017708a1e97f Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 19:59:40 +0700
Subject: [PATCH 089/202] update docs

---
 .../extending/extending_the_object_model.rst  | 238 +++++++++++++-----
 .../developer_guide/extending/index.rst       |   2 +
 ...riting_numba_compatible_transport_code.rst | 102 +++++---
 3 files changed, 247 insertions(+), 95 deletions(-)

diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index bda8967d8..1696c05ad 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -4,11 +4,9 @@
 Extending the Object Model
 ==========================
 
-MC/DC extensions normally begin as ordinary Python model objects, but an extension is complete only when its state and behavior are available in every required execution mode.
-This page describes how to extend the object model without breaking simulation-local compilation or the generated runtime layout.
-
-Read :doc:`../architecture/simulation_compilation` first for the ``MCDCBase``--``MCDCObject``--``MCDCPolymorphic`` hierarchy.
-Read :doc:`../architecture/runtime_data_layout` for the structured ``simulation`` record, flat ``data`` array, and generated accessors.
+Use this page when an extension changes a model class, introduces runtime-visible state, or adds a registered or polymorphic object type.
+It assumes the hierarchy and data representation described in :doc:`../architecture/simulation_compilation` and :doc:`../architecture/runtime_data_layout`.
+The guidance below applies those designs as implementation recipes instead of restating them.
 
 When the new state is consumed during particle transport, continue with :doc:`writing_numba_compatible_transport_code` for type, dispatch, allocation, CPU/GPU compatibility, and verification guidance.
 
@@ -19,23 +17,28 @@ Choose the narrowest extension that represents the new concept:
 
 .. list-table::
    :header-rows: 1
-   :widths: 24 24 52
+   :widths: 20 20 36 24
 
    * - Change
      - Starting point
      - Use when
+     - Example
    * - Add a field
      - Existing class
      - The concept already belongs to an existing model or configuration object.
+     - Add a new source parameter to ``Source``.
    * - Add embedded state
      - ``MCDCBase``
      - The state belongs to one parent and does not need an independently addressable entry in a simulation registry.
+     - Add technique settings owned by ``Simulation``.
    * - Add a registered category
      - ``MCDCObject``
      - Transport must refer to independently registered instances by simulation-local ``ID``.
+     - Add a new Surface-like category with its own collection.
    * - Add a representation to an existing category
      - ``MCDCPolymorphic``
      - The extension shares a category interface but needs a distinct packed layout and dispatch code.
+     - Add a concrete ``MeshBase`` representation.
 
 Prefer adding a subtype to an existing polymorphic family over creating a new registered category when the new object has the same conceptual role.
 A new tally estimator, for example, belongs under ``Tally``; it does not need an unrelated top-level registry.
@@ -49,26 +52,104 @@ Every MC/DC model class must follow the conventions used by the compiler and Num
    Provide a unique, stable, lower-case label such as ``structured_mesh``.
    The label names generated structured layouts and the corresponding modules under ``mcdc_get`` and ``mcdc_set``.
 
+   .. code-block:: python
+
+      class MeshStructured(MeshBase):
+          label = "structured_mesh"
+
+``sub_type``
+   Give every concrete ``MCDCPolymorphic`` subclass a unique integer constant within its family.
+   The shared base uses ``sub_type = -1``.
+
+   .. code-block:: python
+
+      class MeshStructured(MeshBase):
+          sub_type = MESH_STRUCTURED
+
 Type annotations
    Annotate every field that must be represented at runtime.
    Annotations define scalar fields, embedded structures, object-ID references, and variable-length payloads.
 
+   .. code-block:: python
+
+      active: bool
+      translation: Annotated[NDArray[float64], (3,)]
+      move_velocities: Annotated[NDArray[float64], ("N_move", 3)]
+      surfaces: list[Surface]
+
 Initialization
    Assign every runtime-visible field a valid initial value.
    Subclasses of ``MCDCObject`` must call ``super().__init__()`` so ``ID`` is initialized; subclasses of ``MCDCPolymorphic`` must do the same so both ``ID`` and ``sub_ID`` are initialized.
 
+   .. code-block:: python
+
+      def __init__(self, name, boundaries):
+          super().__init__()
+          self.name = name
+          self.boundaries = np.asarray(boundaries, dtype=float64)
+
 ``non_numba``
    List Python-only fields that should not be traversed or packed automatically.
    The class must explicitly convert any required information from those fields into annotated runtime-visible fields before packing.
 
+   For example, ``Cell`` keeps its expressive ``region`` and ``fill`` objects on the Python side, then derives RPN tokens and a fill ID for transport:
+
+   .. code-block:: python
+
+      non_numba = ["region", "fill"]
+
+      region: Region
+      fill: MaterialBase | Universe | Lattice | None
+      region_RPN_tokens: list[int]
+      fill_ID: int
+
 Compilation hook
    Use the inherited ``_compile_into_simulation`` implementation unless the class must canonicalize objects, compile excluded references, or derive fields from assigned object IDs.
 
+   .. code-block:: python
+
+      def _compile_into_simulation(self, simulation):
+          if not super()._compile_into_simulation(simulation):
+              return False
+
+          self.reference._compile_into_simulation(simulation)
+          self.reference_ID = self.reference.ID
+          return True
+
+   If Python-only members must be canonicalized before ordinary traversal, guard the work with ``compile_ID`` and then call ``super`` exactly once:
+
+   .. code-block:: python
+
+      def _compile_into_simulation(self, simulation):
+          if self.compile_ID == simulation.compile_ID:
+              return False
+
+          self._resolve_python_inputs(simulation)
+
+          if not super()._compile_into_simulation(simulation):
+              return False
+
+          self._derive_post_registration_fields()
+          return True
+
+   Do not assign ``compile_ID``, ``ID``, or ``sub_ID`` manually.
+
 Ownership boundary
    Design each model-object instance for one ``Simulation`` context.
    Reuse the instance within that model when sharing is intentional, but construct a new object graph for another simulation or process.
    Extension code must not keep process-wide singleton model objects that can be attached to several simulations.
 
+   .. code-block:: python
+
+      surface_a = mcdc.Surface.PlaneZ(z=0.0)
+      surface_b = mcdc.Surface.PlaneZ(z=0.0)
+
+      simulation_a = mcdc.Simulation()
+      simulation_b = mcdc.Simulation()
+
+      simulation_a.set_model([mcdc.Cell(region=+surface_a)])
+      simulation_b.set_model([mcdc.Cell(region=+surface_b)])
+
 Represent Fields Deliberately
 -----------------------------
 
@@ -76,29 +157,29 @@ The layer generator interprets annotations according to the field's role:
 
 .. list-table::
    :header-rows: 1
-   :widths: 34 30 36
+   :widths: 28 27 45
 
    * - Example annotation
      - Runtime representation
-     - Access pattern
-   * - ``active: bool`` or ``count: int``
+     - Transport access
+   * - ``active: bool``
      - Scalar structured field
-     - Direct structured access
-   * - ``vector: Annotated[NDArray[float64], (3,)]``
+     - ``technique["active"]``
+   * - ``translation: Annotated[NDArray[float64], (3,)]``
      - Fixed-size embedded array
-     - Direct structured access
-   * - ``grid: NDArray[float64]``
+     - ``cell["translation"][axis]``
+   * - ``energy: NDArray[float64]``
      - Offset and length plus values in ``data``
-     - Generated accessor
-   * - ``table: Annotated[NDArray[float64], ("N", 3)]``
+     - ``mcdc_get.tally.energy(index, tally, data)``
+   * - ``move_velocities: Annotated[NDArray[float64], ("N_move", 3)]``
      - Offset, length, and shape metadata plus flattened values
-     - Generated multidimensional accessor
-   * - ``mesh: MeshBase``
+     - ``mcdc_get.surface.move_velocities(move, axis, surface, data)``
+   * - ``energy_group_pmf: DistributionPMF``
      - Simulation-local object ID
-     - Lookup through the mesh collection
-   * - ``tallies: list[Tally]``
+     - ``simulation["distributions"][source["energy_group_pmf_ID"]]``
+   * - ``collision_tallies: list[TallyCollision]``
      - Count and offset to IDs stored in ``data``
-     - Generated ID accessor
+     - ``mcdc_get.cell.collision_tally_IDs(index, cell, data)``
 
 Use an integer-only shape when an array is always the same size.
 Use symbolic dimensions when a shape depends on the model.
@@ -114,6 +195,22 @@ Adding a Field to an Existing Class
 #. Consume the field through direct structured access or its generated ``mcdc_get`` and ``mcdc_set`` helpers.
 #. Update the public docstring and API documentation when users can configure the field.
 
+For example, a new variable-length ``energy_bias`` field on ``Source`` requires an annotation and initialized array on the model class:
+
+.. code-block:: python
+
+   # In Source annotations
+   energy_bias: NDArray[float64]
+
+   # In Source.__init__
+   self.energy_bias = np.asarray(energy_bias, dtype=float64)
+
+Transport then reads one value through the generated accessor:
+
+.. code-block:: python
+
+   bias = mcdc_get.source.energy_bias(group, source, data)
+
 Avoid adding parallel state in several classes.
 If a value belongs to the simulation as a whole, place it in ``Simulation`` or one of its embedded configuration objects and pass or access that representation consistently.
 
@@ -140,6 +237,14 @@ Add an annotated field for the object to its owner and instantiate it with the o
 For simulation-wide configuration, this normally means adding the field to ``Simulation`` and constructing it in ``Simulation.__init__``.
 The embedded object participates in recursive compilation but does not require a registry branch or object ID.
 
+.. code-block:: python
+
+   class Simulation(MCDCBase):
+       new_technique: NewTechnique
+
+       def __init__(self):
+           self.new_technique = NewTechnique()
+
 If the embedded object refers to an ``MCDCObject``, annotate that reference.
 The default traversal will register the referenced object when compilation reaches the embedded configuration.
 
@@ -156,6 +261,32 @@ A genuinely new registered category requires coordinated changes:
    A public class is normally imported through ``mcdc/__init__.py``; an internal class must be imported by another module in the compilation path.
 #. Add the collection and lookup behavior required by transport.
 
+For example, the class and its simulation collection begin with:
+
+.. code-block:: python
+
+   class Detector(MCDCObject):
+       label = "detector"
+
+       name: str
+       response: NDArray[float64]
+
+       def __init__(self, name, response):
+           super().__init__()
+           self.name = name
+           self.response = np.asarray(response, dtype=float64)
+
+
+   class Simulation(MCDCBase):
+       detectors: list[Detector]
+
+The compiler then selects that collection explicitly:
+
+.. code-block:: python
+
+   elif isinstance(object_, Detector):
+       object_list = simulation.detectors
+
 Do not add a fallback registration branch that silently accepts unknown objects.
 An explicit category branch keeps registry ownership and runtime layout reviewable.
 
@@ -189,60 +320,25 @@ For example, the structural part of a mesh subtype follows this pattern:
 No new ``register_object`` branch is needed for a subtype of an already registered family.
 The existing ``isinstance(..., MeshBase)`` or corresponding category check places it in the base collection, while ``sub_type`` and ``sub_ID`` connect it to its concrete packed collection.
 
-Custom Compilation Hooks
-------------------------
-
-Override ``_compile_into_simulation`` only when the default recursive traversal is insufficient.
-The common post-registration pattern is:
-
-.. code-block:: python
-
-   def _compile_into_simulation(self, simulation) -> bool:
-       if not super()._compile_into_simulation(simulation):
-           return False
-
-       # Referenced objects now have simulation-local IDs.
-       self.runtime_field = self.python_reference.ID
-       return True
+Generated Runtime Layers and Accessors
+--------------------------------------
 
-Calling ``super`` first registers an ``MCDCObject`` and recursively compiles its ordinary members.
-The Boolean return prevents repeated work when the same object is reached again.
+The annotation is the source of truth for generated runtime fields and accessors.
+Do not edit ``mcdc/numba_types.py``, ``mcdc_get``, or ``mcdc_set`` to introduce a field.
+Prepare a representative simulation so ``numba_layers_generator.py`` regenerates those files, then verify the access pattern predicted by the field representation chosen above.
 
-Some classes must canonicalize or replace members before the default traversal.
-In that case, check ``compile_ID`` before doing the work, update the runtime-visible members, and then call ``super`` exactly once:
+For example, a variable-length ``Detector.response`` field produces element accessors associated with the ``detector`` label:
 
 .. code-block:: python
 
-   def _compile_into_simulation(self, simulation) -> bool:
-       if self.compile_ID == simulation.compile_ID:
-           return False
-
-       self._resolve_python_inputs(simulation)
-
-       if not super()._compile_into_simulation(simulation):
-           return False
-
-       self._derive_post_registration_fields()
-       return True
-
-Do not assign ``compile_ID``, ``ID``, or ``sub_ID`` manually.
-The shared compiler owns those values.
-
-Generated Runtime Layers and Accessors
---------------------------------------
+   value = mcdc_get.detector.response(index, detector, data)
+   mcdc_set.detector.response(index, detector, data, new_value)
 
-``numba_layers_generator.py`` derives the structured dtypes, flat-data metadata, and accessor targets from the completed model classes.
-It writes:
+A fixed-size field such as ``Cell.translation`` remains embedded and is accessed directly:
 
-- ``mcdc/numba_types.py`` for structured dtype definitions.
-- ``mcdc/mcdc_get/<label>.py`` for generated reads.
-- ``mcdc/mcdc_set/<label>.py`` for generated writes.
-- ``mcdc_get/__init__.py`` and ``mcdc_set/__init__.py`` for generated module imports.
+.. code-block:: python
 
-Do not implement a generated accessor by hand.
-Express the field correctly in the class annotation, prepare a representative simulation, and allow the layer generator to regenerate the modules.
-Then use the generated helper from transport code.
-Fixed-size fields do not need helpers and can be accessed directly from the structured record.
+   value = cell["translation"][axis]
 
 Public API and Documentation
 ----------------------------
@@ -257,6 +353,16 @@ For a user-facing class or constructor:
 Internal helper classes should remain under ``mcdc.object_`` and should not be exported merely to make discovery work.
 Import them explicitly in the compilation path instead.
 
+For example, a public ``Detector`` is re-exported from the package and listed by its qualified name in the API autosummary:
+
+.. code-block:: python
+
+   from mcdc.object_.detector import Detector
+
+.. code-block:: rst
+
+   ~mcdc.Detector
+
 Verification Checklist
 ----------------------
 
diff --git a/docs/source/developer_guide/extending/index.rst b/docs/source/developer_guide/extending/index.rst
index 96e175715..d730eb56a 100644
--- a/docs/source/developer_guide/extending/index.rst
+++ b/docs/source/developer_guide/extending/index.rst
@@ -10,6 +10,8 @@ It complements the :doc:`../architecture/index`, which explains the existing des
 Start with :doc:`extending_the_object_model` when adding a field to an existing model class, introducing simulation-owned configuration, creating a registered model-object category, or implementing a new polymorphic subtype.
 Continue with :doc:`writing_numba_compatible_transport_code` when the extension adds or changes code executed during particle transport.
 
+For example, a new runtime field with no transport behavior uses the object-model guide, a numerical change using existing fields starts with the transport-code guide, and a new tally subtype follows both in that order.
+
 Use the :doc:`../../contributing/index` for repository setup, test commands, continuous-integration coverage, and pull-request requirements.
 
 .. toctree::
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index b6d7af2d4..155dd2b8f 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -4,14 +4,10 @@
 Writing Numba-Compatible Transport Code
 =======================================
 
-Maintained transport code in MC/DC is written in Python but may execute as Python, Numba-compiled CPU code, or Numba-compiled GPU device code.
-A method may be prototyped within the MC/DC Python backend before it is adapted for the two accelerated backends.
-
-Read :doc:`../architecture/python_first_numba_accelerated_design` first for the reason behind this development model.
-If the change introduces new model state, also read :doc:`extending_the_object_model` and :doc:`../architecture/runtime_data_layout`.
-
-The rules below apply when an MC/DC Python prototype is being made portable and maintained as part of MC/DC.
-They are not restrictions on temporary Python-only behavior during initial exploration.
+Use this page when verified Python transport behavior is being prepared for Numba-CPU, Numba-GPU, and long-term maintenance in MC/DC.
+The development rationale and execution mechanisms belong in :doc:`../architecture/python_first_numba_accelerated_design` and :doc:`../architecture/transport_execution`.
+If the change introduces new model state, begin with :doc:`extending_the_object_model`.
+The rules below start at the portability boundary and do not restrict temporary Python-only exploration.
 
 Choose the Host or Transport Layer
 ----------------------------------
@@ -34,25 +30,23 @@ Place work in transport when it must be performed during particle execution:
 Do as much irregular work as practical before transport.
 A small amount of host-side preparation can turn a dynamic operation into simple indexed access inside a frequently called kernel.
 
-Work Python First
------------------
+For example, derive a reusable coefficient once while preparing the model instead of recomputing it for every particle event:
 
-An exploratory method may begin in MC/DC Python, using whichever Python data structures make the algorithm easiest to understand and verify.
-It still runs through MC/DC's normal model preparation and transport path.
-This Python-only implementation is a valid stopping point for a small study that does not need compiled performance.
+.. code-block:: python
 
-At this stage, use module-level global state, arbitrary Python objects, ad hoc imports, dynamic behavior, file I/O, callbacks, visualization, hard-coded assumptions, or direct transport edits whenever they help answer the research question.
-Calls to packages such as SciPy and Matplotlib are acceptable even during transport.
-A formal prototype service or abstraction is not required.
+   # On the model class
+   inverse_dx: float
 
-Keep prototype-only dependencies local to the experiment rather than adding them to MC/DC's required dependencies.
-The prototype is allowed to be disposable and is not expected to compile unchanged.
+   def _prepare_spacing(self):
+       self.inverse_dx = 1.0 / self.dx
 
-Unrestricted prototyping is optional.
-A developer already familiar with MC/DC and Numba may begin with packed runtime inputs, stable types, and supported operations, producing an implementation that is nearly Numba-compatible from the start.
-This can minimize the deliberate porting work while preserving the freedom to use ordinary Python whenever it helps establish the method.
+   # In transport
+   index = int((particle["x"] - mesh["x0"]) * mesh["inverse_dx"])
 
-Porting for accelerated execution begins by adapting the verified method so that the required information and behavior use the packed runtime inputs available to transport.
+Port a Verified Method
+----------------------
+
+Keep the verified Python result as the behavioral baseline while adapting the method to MC/DC's packed runtime inputs and compiler-compatible operations.
 Decorate the maintained function with ``@njit`` like the surrounding transport functions; in Python mode, MC/DC disables JIT compilation and calls the same function as Python.
 
 .. code-block:: python
@@ -66,10 +60,7 @@ Decorate the maintained function with ``@njit`` like the surrounding transport f
        particle["w"] *= factor
 
 Keep the function small enough that its inputs, outputs, and mutations are clear.
-First exercise it in Python mode to verify the algorithm and obtain an ordinary traceback.
-Then run it in Numba-CPU mode to verify type inference.
-Finally, adapt and validate it for Numba-GPU.
-Each stage may reveal constraints that were irrelevant to the preceding implementation.
+Exercise the maintained function in Python mode against the baseline, then use Numba-CPU to resolve typing issues, and finally validate device compatibility in Numba-GPU.
 
 Use Runtime Data, Not Model Objects
 -----------------------------------
@@ -88,6 +79,16 @@ Use the representation appropriate to each field:
 If the required value is unavailable in this form, extend the object model and generated runtime layer before writing the transport behavior.
 Do not create a parallel Python-only lookup inside the kernel.
 
+For example, recover a prepared distribution by simulation-local ID instead of passing its Python model object into transport:
+
+.. code-block:: python
+
+   # Python model construction
+   source_object.energy_group_pmf = distribution_object
+
+   # Portable transport representation
+   distribution = simulation["distributions"][source["energy_group_pmf_ID"]]
+
 Keep Types Stable
 -----------------
 
@@ -104,6 +105,19 @@ Make those types unambiguous:
 Numba may accept a construct on the CPU without making it available on the GPU.
 When a function is shared, compatibility with the stricter target is the relevant standard.
 
+For example, initialize a scalar result before control flow so every path returns the same type:
+
+.. code-block:: python
+
+   @njit
+   def find_energy_bin(E, grid):
+       index = -1
+       for i in range(len(grid) - 1):
+           if grid[i] <= E < grid[i + 1]:
+               index = i
+               break
+       return index
+
 Represent Variable-Length Data Explicitly
 -----------------------------------------
 
@@ -157,6 +171,25 @@ Particle histories repeatedly execute transport functions, so temporary allocati
 The owner of each mutation should be evident from the function signature.
 Avoid hidden module-level mutable state.
 
+For example, select a minimum with scalar state instead of building a temporary list:
+
+.. code-block:: python
+
+   best_distance = INF
+   for i in range(cell["N_surface"]):
+       distance = distance_to_surface(i, particle, cell, simulation, data)
+       if distance < best_distance:
+           best_distance = distance
+
+When a scalar structured record must be mutated across a function boundary, pass its one-element container and recover the record inside the function:
+
+.. code-block:: python
+
+   @njit
+   def increment_counter(counter_container):
+       counter = counter_container[0]
+       counter["value"] += 1
+
 Stay Within the CPU/GPU Common Subset
 -------------------------------------
 
@@ -173,6 +206,18 @@ Backend-specific code is appropriate when the execution model truly differs.
 Keep the shared numerical operation in ``mcdc/transport`` when possible, and put only the required adaptation under ``mcdc/code_factory/gpu``.
 Document why the paths differ and test their physical equivalence.
 
+For example, keep the shared numerical operation free of reporting or device-management code:
+
+.. code-block:: python
+
+   @njit
+   def apply_survival_biasing(particle, survival_probability):
+       particle["w"] *= survival_probability
+
+
+   def report_survival_biasing(survival_probability):
+       print(f"Survival probability: {survival_probability}")
+
 Debug in Layers
 ---------------
 
@@ -186,6 +231,8 @@ When a change fails, isolate the layer:
 Do not begin by diagnosing a GPU compiler error if the same calculation is already incorrect in Python.
 Conversely, a passing Python test does not prove that the function is type-stable or device compatible.
 
+For example, an unexpected physical result in Python belongs in the Python transport layer, a Numba ``TypingError`` belongs in Numba-CPU porting, and a device-link or unsupported-atomic error belongs in the Numba-GPU layer.
+
 Verification Checklist
 ----------------------
 
@@ -200,8 +247,5 @@ Before considering a transport extension complete:
 - Existing examples still construct successfully when the public API or model compilation changed.
 - User and developer documentation describe any new behavior or limitation.
 
-A general feature merged and maintained as part of MC/DC must complete all three execution stages unless the maintainers explicitly accept and document a backend-specific limitation.
-Experimental or study-specific work may stop at Python or Numba-CPU when that stage already satisfies its purpose.
-
 Repository commands, continuous-integration coverage, and regression-test options belong in the :doc:`../../contributing/index`.
 For changes affecting public inputs, follow :doc:`../../contributing/example_validation`.

From f62d38ea1c9a4df62fc729da6a027bc068d9f896 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 20:04:33 +0700
Subject: [PATCH 090/202] update transport exec dev doc

---
 .../developer_guide/extending/extending_the_object_model.rst   | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index 1696c05ad..fca700573 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -5,8 +5,7 @@ Extending the Object Model
 ==========================
 
 Use this page when an extension changes a model class, introduces runtime-visible state, or adds a registered or polymorphic object type.
-It assumes the hierarchy and data representation described in :doc:`../architecture/simulation_compilation` and :doc:`../architecture/runtime_data_layout`.
-The guidance below applies those designs as implementation recipes instead of restating them.
+It assumes the hierarchy and data representation described in :doc:`../architecture/simulation_compilation` and :doc:`../architecture/runtime_data_layout` and applies those designs as implementation recipes.
 
 When the new state is consumed during particle transport, continue with :doc:`writing_numba_compatible_transport_code` for type, dispatch, allocation, CPU/GPU compatibility, and verification guidance.
 

From 2a8794b8b9030c3e9602228fc47cb10e4760f964 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 20:16:43 +0700
Subject: [PATCH 091/202] update docs

---
 .../python_first_numba_accelerated_design.rst |  8 ++--
 .../architecture/transport_execution.rst      | 39 +++++++++----------
 .../extending/extending_the_object_model.rst  |  6 +--
 .../developer_guide/extending/index.rst       |  4 +-
 ...riting_numba_compatible_transport_code.rst |  7 ++--
 5 files changed, 30 insertions(+), 34 deletions(-)

diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
index fed3c8571..82fed894f 100644
--- a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -37,7 +37,7 @@ This supports several project goals:
 - Common transport interfaces provide a shared foundation for CPU and GPU execution, with backend-specific adaptation where the hardware requires it.
 
 The choice therefore preserves an expressive starting point while providing a path to compiled execution.
-It also introduces the constraints discussed in the remainder of this page.
+Those goals introduce the constraints discussed below.
 
 Staged Methods Development
 --------------------------
@@ -132,11 +132,11 @@ Preparing a method for acceleration narrows the freedom available inside transpo
 Python objects remain the natural way to describe a problem, but accelerated transport operates on a numerical representation prepared for one simulation.
 MC/DC therefore replaces Python's implicit object machinery with a purpose-built runtime object model based on structured records, simulation-local IDs, offsets, and generated accessors.
 Mutable runtime records are passed in one-element array containers, providing stable shared storage across Python, Numba-CPU, and Numba-GPU execution.
-The transformation is covered in :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
+See :doc:`simulation_compilation` and :doc:`runtime_data_layout` for this transformation.
 
 **Transport behavior becomes explicit.**
 Dynamic Python techniques that are useful during prototyping must be expressed in forms the compiler can understand when the method is accelerated.
-Contributor guidance belongs in :doc:`../extending/writing_numba_compatible_transport_code` and :doc:`../extending/extending_the_object_model`.
+Use :doc:`../extending/writing_numba_compatible_transport_code` and :doc:`../extending/extending_the_object_model` when implementing these changes.
 
 **CPU and GPU share a portable core.**
 Common transport algorithms use behavior supported by both accelerated targets, while hardware-specific concerns remain isolated.
@@ -153,7 +153,7 @@ Beginning with simple numerical data and operations that Numba supports can redu
 
 Portability also increases compiler, backend, and validation work.
 MC/DC accepts these costs so that maintained features can share transport logic across Python, CPU, and GPU execution rather than becoming separate implementations that may drift apart.
-Practical constraints are covered in :doc:`../extending/writing_numba_compatible_transport_code`; mode-specific execution mechanisms are covered in :doc:`transport_execution`.
+Use :doc:`../extending/writing_numba_compatible_transport_code` for practical constraints and :doc:`transport_execution` for mode-specific execution mechanisms.
 
 Related Design Choices
 ----------------------
diff --git a/docs/source/developer_guide/architecture/transport_execution.rst b/docs/source/developer_guide/architecture/transport_execution.rst
index 5a22023bc..280d9c782 100644
--- a/docs/source/developer_guide/architecture/transport_execution.rst
+++ b/docs/source/developer_guide/architecture/transport_execution.rst
@@ -20,30 +20,27 @@ The first call includes compilation work, while subsequent calls use the compile
 In **Numba-GPU mode**, MC/DC adapts the transport functions for device execution, places runtime state in GPU-accessible memory, and uses Harmonize to schedule particle work.
 The remaining sections describe this additional GPU-specific compilation machinery.
 
-Contributor-facing constraints, porting guidance, and staged verification are discussed in in :doc:`../extending/writing_numba_compatible_transport_code`.
-Operational commands are detailed in the :doc:`../../user_guide/execution/index`.
+Use :doc:`../extending/writing_numba_compatible_transport_code` for contributor constraints, porting guidance, and staged verification.
+Use the :doc:`../../user_guide/execution/index` for operational commands.
 
 GPU Compilation
 ---------------
 
 When targeting GPUs, MC/DC functions are just-in-time (JIT) compiled with Numba and integrated with Harmonize.
 
-When considered in totality the MC/DC+Numba+Harmonize JIT compilation structure is akin to "portability framework", in that it allows dynamic targeting and developer abstraction of hardware architectures, like OpenMP target-offloading used by OpenMC.
-This JIT compilation process allows MC/DC to pair the idea of a portability framework with a high-level language in an effort to enable more rapid methods development on Exascale systems.
+Together, MC/DC, Numba, and Harmonize form a JIT portability framework that dynamically targets different hardware architectures.
+This framework combines hardware portability with high-level Python methods development for exascale systems.
 
-Monte Carlo transport functions from MC/DC are treated as device functions with global, host, and additional device functions coming from Harmonize.
-Mixing codes from various sources (Python and C++) requires the user to provide an *exacting* set of compiler options to achieve an operable executable.
-We provide in-depth descriptions of these sets of commands as we found the definition of this JIT compilation process one of the most difficult parts to get the MC/DC+Harmonize software engineering structure operable.
-
-To examine the compilation strategy in-depth, a simple proxy problem is provided in Figures figcodenvcc and figcodeclang.
-The figures show a simple Python function that does integer addition on a provided value (representing MC/DC transport operations) and a C++ snippet (representing Harmonize) showing first the declaration of an extern device function (eventually coming from Python) and a global function which will act as the GPU runtime for our Python device function.
-Note that for the operability of these examples, extra functions are required in ``dep.cpp`` and ``add_one.py`` but are truncated for brevity.
+MC/DC transport functions become device functions, while Harmonize supplies the associated global, host, and additional device functions.
+Linking device code generated from Python with the C++ Harmonize runtime requires an exact set of compiler options.
+The NVIDIA and AMD proxy examples below demonstrate this process with a Python integer-addition function representing MC/DC transport and a C++ declaration and global function representing Harmonize.
+Supporting functions in ``dep.cpp`` and ``add_one.py`` are omitted from the illustrations.
 
 --------------
 Nvidia Targets
 --------------
 
-To compile to Nvidia GPU hardware-targets at runtime, we rely entirely on the Nvidia C-Compiler (`nvcc`).
+MC/DC uses Numba to produce PTX and the NVIDIA CUDA compiler (``nvcc``) for NVIDIA device compilation and linking.
 Current versions of Numba come with CUDA operability natively, but this is set to be deprecated in future releases in favor of a more modular approach where the Numba-CUDA package will be an optional separate feature.
 
 .. image:: ../../images/developer_guide/architecture/numba_gpu_nvidia_flow.png
@@ -55,7 +52,7 @@ Current versions of Numba come with CUDA operability natively, but this is set t
 Simple proxy example describing how to compile device functions in Numba-Python with external C++ code for targeting Nvidia GPUs.
 In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize
 
-We begin by
+The NVIDIA compilation sequence is:
 
 #. Compiling Python device code to Nvidia PTX by ``numba.cuda.compile_ptx_for_current_device`` (which requires typed function signatures), then place that output into ``add_one.ptx`` file; next
 #. Compiling PTX to relocatable device code using ``nvcc -rdc=true -dc -arch=<arch> --cudart shared --compiler-options -fPIC add.ptx -o add.o`` where ``-dc`` asks the compiler for device code, ``-rdc`` asks to make that device code relocatable, ``--cudart shared`` asks for shared CUDA runtime libraries and ``-fPIC`` generates position-independent code;
@@ -73,8 +70,8 @@ AMD Targets
 
 Just in time compilation and execution to AMD devices are enabled as of `MC/DC v0.11.0 <https://github.com/mcdc-project/mcdc/tree/v0.11.0>`_.
 Significant adaptations from the process of Nvidia compilation are required to target AMD GPUs.
-PTX is a proprietary Nvidia standard, so when targeting AMD GPUs, we rely on intermediate compiler representation (IR) from LLVM for an AMD GPU hardware-target (also called an LLVM target triple).
-AMD's compiler toolchain is based in the LLVM-Clang ecosystem, so we will be calling LLVM-Clang-based tools (e.g., ``hipcc`` is a wrapper function for ``clang``).
+PTX is a proprietary NVIDIA standard, so AMD targets use an LLVM intermediate representation (IR) generated for the selected AMD GPU target triple.
+AMD's compiler toolchain is based on LLVM and Clang, and MC/DC invokes tools such as ``hipcc``, which wraps ``clang``.
 Note that while the LLVM-Clang commands are generic, AMD variations of compilers, linkers, etc. must be invoked.
 For example, to invoke the correct Clang compiler point to the ROCm installed variation (often on LinuxOS at ``opt/rocm/llvm/bin/clang``).
 
@@ -84,11 +81,11 @@ As this patch is a port of AMD's Heterogeneous-computing Interface for Portabili
 The Numba-HIP development team has gone as far as to provide a ``numba.hip.pose_as_cuda()`` function, which, after being called in Python script, will alias all supported Numba-CUDA functions to Numba-HIP ones and compile/run automatically.
 
 
-When moving to compile and execute full MC/DC+Harmonize, we must again enable the compilation of device functions from Numba-HIP and device, global, and host functions from C++.
-To show that process, we again explore a simple proxy application shown in figure fig:codeclang where a Numba-HIP function adds one to an integer value and a C++ function declares an extern function by the same name and runs that function for all values of an array.
+Full MC/DC+Harmonize compilation combines device functions from Numba-HIP with device, global, and host functions from C++.
+The AMD proxy example pairs a Numba-HIP integer-addition function with a C++ declaration and global function that applies it to an array.
 
 Every GPU program is technically a bound set of two complementary applications: one that runs on the host side (CPU) and the other on the device side (GPU), with global functions linking them together.
-To link external device code together for AMD hardware-targets, we have to unbundle these two programs, link the extra device functions (coming from Python) to the device side, then re-bundle the device and host functions back together.
+Linking external device code for AMD hardware requires unbundling the host and device programs, linking the Python-generated functions into the device program, and rebundling both programs.
 This process is done in LLVM-IR.
 
 .. image:: ../../images/developer_guide/architecture/numba_gpu_amd_flow.png
@@ -100,7 +97,7 @@ Simple proxy example describing how to compile device functions in Numba-HIP wit
 In this simplified proxy, the Python function corresponds to MC/DC, and the C++ code corresponds to Harmonize
 
 Figure fig:codeclang shows the compilation structure.
-We begin compilation by
+The AMD compilation sequence is:
 
 #. Compiling C++ source in ``dep.cpp`` to LLVM-IR with host and device code bundled together with ``hipcc -c -fgpu-rdc -S -emit-llvm -o dep.ll -x hip dep.cpp -g`` where ``-fgpu-rdc`` asks the compiler for relocatable device code ``-emit-llvm`` requests the LLVM-IR, ``-c`` only runs preprocess, compile, and assemble steps, and ``-x hip`` specifies that ``dep.cpp`` is HIP code;
 #. Unbundling the LLVM-IR:
@@ -115,5 +112,5 @@ We begin compilation by
 
 As in the Nvidia compilation, non-implemented functions can be brought into the final program via the C++ source.
 This was required for MC/DC on AMD GPUs as vector operable atomics are not currently implemented in the Numba HIP port and thus must come from the C++ side.
-We hope that these more generic adaptations (relying on LLVM-Clang infrastructure instead of CUDA) will allow for greater extensibility as we move to target future accelerator platforms---namely, Intel GPUs.
-For compilation to Nvidia hardware-targets, we will still keep the PTX-based compilation structure.
+The LLVM-Clang-based path is designed to remain extensible to future accelerator platforms, including Intel GPUs.
+NVIDIA compilation continues to use the PTX-based path.
diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index fca700573..521d6df3c 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -40,7 +40,7 @@ Choose the narrowest extension that represents the new concept:
      - Add a concrete ``MeshBase`` representation.
 
 Prefer adding a subtype to an existing polymorphic family over creating a new registered category when the new object has the same conceptual role.
-A new tally estimator, for example, belongs under ``Tally``; it does not need an unrelated top-level registry.
+For example, implement a new tally estimator as a ``Tally`` subtype.
 
 The Common Class Contract
 -------------------------
@@ -349,8 +349,8 @@ For a user-facing class or constructor:
 #. Document parameters, units, defaults, constraints, and at least one usable example in the class docstring.
 #. Update the User Guide when the extension changes how users construct or run a model.
 
-Internal helper classes should remain under ``mcdc.object_`` and should not be exported merely to make discovery work.
-Import them explicitly in the compilation path instead.
+Keep internal helper classes under ``mcdc.object_`` and import them explicitly in the compilation path.
+Export only classes that form part of the public API.
 
 For example, a public ``Detector`` is re-exported from the package and listed by its qualified name in the API autosummary:
 
diff --git a/docs/source/developer_guide/extending/index.rst b/docs/source/developer_guide/extending/index.rst
index d730eb56a..413da8fc4 100644
--- a/docs/source/developer_guide/extending/index.rst
+++ b/docs/source/developer_guide/extending/index.rst
@@ -4,8 +4,8 @@
 Extending MC/DC
 ===============
 
-This section provides implementation-oriented guidance for adding new model concepts and transport capabilities to MC/DC.
-It complements the :doc:`../architecture/index`, which explains the existing design, by describing the changes an extension must make across the Python model, compilation, generated runtime layers, transport implementation, public API, and tests.
+Use this section to extend the Python model, compilation, generated runtime layers, transport implementation, public API, and tests.
+Read :doc:`../architecture/index` for the design that these recipes extend.
 
 Start with :doc:`extending_the_object_model` when adding a field to an existing model class, introducing simulation-owned configuration, creating a registered model-object category, or implementing a new polymorphic subtype.
 Continue with :doc:`writing_numba_compatible_transport_code` when the extension adds or changes code executed during particle transport.
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index 155dd2b8f..10106783f 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -5,9 +5,8 @@ Writing Numba-Compatible Transport Code
 =======================================
 
 Use this page when verified Python transport behavior is being prepared for Numba-CPU, Numba-GPU, and long-term maintenance in MC/DC.
-The development rationale and execution mechanisms belong in :doc:`../architecture/python_first_numba_accelerated_design` and :doc:`../architecture/transport_execution`.
+Read :doc:`../architecture/python_first_numba_accelerated_design` for the development rationale and :doc:`../architecture/transport_execution` for the execution mechanisms.
 If the change introduces new model state, begin with :doc:`extending_the_object_model`.
-The rules below start at the portability boundary and do not restrict temporary Python-only exploration.
 
 Choose the Host or Transport Layer
 ----------------------------------
@@ -231,7 +230,7 @@ When a change fails, isolate the layer:
 Do not begin by diagnosing a GPU compiler error if the same calculation is already incorrect in Python.
 Conversely, a passing Python test does not prove that the function is type-stable or device compatible.
 
-For example, an unexpected physical result in Python belongs in the Python transport layer, a Numba ``TypingError`` belongs in Numba-CPU porting, and a device-link or unsupported-atomic error belongs in the Numba-GPU layer.
+For example, investigate an unexpected physical result in Python transport, a Numba ``TypingError`` during Numba-CPU porting, and a device-link or unsupported-atomic error in the Numba-GPU layer.
 
 Verification Checklist
 ----------------------
@@ -247,5 +246,5 @@ Before considering a transport extension complete:
 - Existing examples still construct successfully when the public API or model compilation changed.
 - User and developer documentation describe any new behavior or limitation.
 
-Repository commands, continuous-integration coverage, and regression-test options belong in the :doc:`../../contributing/index`.
+Use the :doc:`../../contributing/index` for repository commands, continuous-integration coverage, and regression-test options.
 For changes affecting public inputs, follow :doc:`../../contributing/example_validation`.

From ebf445657af4e752bb8bc67906e32cf4e8f90cd0 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 20:23:43 +0700
Subject: [PATCH 092/202] update docs

---
 .../developer_guide/extending/extending_the_object_model.rst    | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index 521d6df3c..618df7638 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -57,7 +57,7 @@ Every MC/DC model class must follow the conventions used by the compiler and Num
           label = "structured_mesh"
 
 ``sub_type``
-   Give every concrete ``MCDCPolymorphic`` subclass a unique integer constant within its family.
+   Give every concrete ``MCDCPolymorphic`` subclass a unique named integer constant within its family.
    The shared base uses ``sub_type = -1``.
 
    .. code-block:: python

From 7171af52c11d37afa3569ea3df8965eb8d9cf7ab Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 20:26:11 +0700
Subject: [PATCH 093/202] update docs

---
 .../developer_guide/extending/extending_the_object_model.rst   | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index 618df7638..2e31a4941 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -91,7 +91,7 @@ Initialization
    List Python-only fields that should not be traversed or packed automatically.
    The class must explicitly convert any required information from those fields into annotated runtime-visible fields before packing.
 
-   For example, ``Cell`` keeps its expressive ``region`` and ``fill`` objects on the Python side, then derives RPN tokens and a fill ID for transport:
+   For example, ``Cell`` keeps its expressive ``region`` and ``fill`` objects on the Python side, then derives RPN tokens, a fill-type code, and a fill ID for transport:
 
    .. code-block:: python
 
@@ -100,6 +100,7 @@ Initialization
       region: Region
       fill: MaterialBase | Universe | Lattice | None
       region_RPN_tokens: list[int]
+      fill_type: int
       fill_ID: int
 
 Compilation hook

From 50cc9991687ea806349f9c1f22ff49f493771b59 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 3 Aug 2026 20:36:48 +0700
Subject: [PATCH 094/202] update docs

---
 .../architecture/simulation_compilation.rst     |  6 +++---
 .../extending/extending_the_object_model.rst    | 17 -----------------
 2 files changed, 3 insertions(+), 20 deletions(-)

diff --git a/docs/source/developer_guide/architecture/simulation_compilation.rst b/docs/source/developer_guide/architecture/simulation_compilation.rst
index 5752a62e1..5dde4fd3d 100644
--- a/docs/source/developer_guide/architecture/simulation_compilation.rst
+++ b/docs/source/developer_guide/architecture/simulation_compilation.rst
@@ -72,14 +72,15 @@ The setter calls identify the roots of the user model:
 - Settings and transport techniques are embedded objects already owned by the simulation.
 
 There is no process-wide model singleton.
-Multiple ``Simulation`` instances can be constructed and configured in the same Python process, provided each owns a distinct object graph.
-Model objects are included only when they are reachable from a simulation's roots or embedded configuration.
+Each ``Simulation`` owns the model objects reachable from its roots or embedded configuration.
 
 Ownership Boundary and Process Model
 ------------------------------------
 
 MC/DC intentionally uses a serial-in-process execution model: one ``Simulation`` is compiled, prepared, or executed at a time within a Python process.
 A model-object instance belongs to one simulation context.
+Repeated in-process calculations should update and recompile the same ``Simulation``.
+See :ref:`example_iterative_source_reweighting` for a complete iterative simulation and result-comparison example.
 
 References may be shared freely within that context.
 For example, several cells may use the same material, and compilation will register that material once.
@@ -249,7 +250,6 @@ For example, two sources can be reweighted while the geometry, materials, and ta
 
 Each call to ``compile`` assigns a new ``compile_ID`` and rebuilds a complete, consistent snapshot even though only the source probabilities changed.
 The objects remain owned by the same ``Simulation`` throughout the study.
-See :ref:`example_iterative_source_reweighting` for a complete executable example and comparison script.
 
 From Objects to Runtime Data
 ----------------------------
diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index 2e31a4941..955fcf05c 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -134,22 +134,6 @@ Compilation hook
 
    Do not assign ``compile_ID``, ``ID``, or ``sub_ID`` manually.
 
-Ownership boundary
-   Design each model-object instance for one ``Simulation`` context.
-   Reuse the instance within that model when sharing is intentional, but construct a new object graph for another simulation or process.
-   Extension code must not keep process-wide singleton model objects that can be attached to several simulations.
-
-   .. code-block:: python
-
-      surface_a = mcdc.Surface.PlaneZ(z=0.0)
-      surface_b = mcdc.Surface.PlaneZ(z=0.0)
-
-      simulation_a = mcdc.Simulation()
-      simulation_b = mcdc.Simulation()
-
-      simulation_a.set_model([mcdc.Cell(region=+surface_a)])
-      simulation_b.set_model([mcdc.Cell(region=+surface_b)])
-
 Represent Fields Deliberately
 -----------------------------
 
@@ -371,7 +355,6 @@ An object-model extension should verify all affected layers:
 - Construction accepts valid input and rejects invalid shapes or types.
 - Compilation discovers the object from the intended root.
 - Shared references register once, and recompilation produces a valid new snapshot.
-- Separate simulations use independently constructed model-object instances.
 - Packed fields, object IDs, offsets, and generated accessors contain the expected values.
 - Python and Numba-CPU modes produce equivalent behavior.
 - GPU execution is covered when the changed transport path supports GPUs.

From b71bf5736acf92951da6fc6a2d6cbef360775626 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 5 Aug 2026 11:16:36 +0700
Subject: [PATCH 095/202] separate CPU and GPU transport guidance

---
 ...riting_numba_compatible_transport_code.rst | 120 +++++++++++-------
 1 file changed, 73 insertions(+), 47 deletions(-)

diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index 10106783f..fc7001631 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -4,12 +4,17 @@
 Writing Numba-Compatible Transport Code
 =======================================
 
-Use this page when verified Python transport behavior is being prepared for Numba-CPU, Numba-GPU, and long-term maintenance in MC/DC.
-Read :doc:`../architecture/python_first_numba_accelerated_design` for the development rationale and :doc:`../architecture/transport_execution` for the execution mechanisms.
+Use this page when verified Python transport behavior is being prepared for Numba-CPU execution and long-term maintenance in MC/DC.
+Read :doc:`../architecture/python_first_numba_accelerated_design` for the development rationale.
 If the change introduces new model state, begin with :doc:`extending_the_object_model`.
 
+Numba-CPU Development
+---------------------
+
+Complete the Python and Numba-CPU implementation before considering additional execution targets.
+
 Choose the Host or Transport Layer
-----------------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 Place work on the host when it changes the model or prepares execution:
 
@@ -43,7 +48,7 @@ For example, derive a reusable coefficient once while preparing the model instea
    index = int((particle["x"] - mesh["x0"]) * mesh["inverse_dx"])
 
 Port a Verified Method
-----------------------
+^^^^^^^^^^^^^^^^^^^^^^
 
 Keep the verified Python result as the behavioral baseline while adapting the method to MC/DC's packed runtime inputs and compiler-compatible operations.
 Decorate the maintained function with ``@njit`` like the surrounding transport functions; in Python mode, MC/DC disables JIT compilation and calls the same function as Python.
@@ -59,10 +64,10 @@ Decorate the maintained function with ``@njit`` like the surrounding transport f
        particle["w"] *= factor
 
 Keep the function small enough that its inputs, outputs, and mutations are clear.
-Exercise the maintained function in Python mode against the baseline, then use Numba-CPU to resolve typing issues, and finally validate device compatibility in Numba-GPU.
+Exercise the maintained function in Python mode against the baseline, then use Numba-CPU to resolve typing and compiled-runtime issues.
 
 Use Runtime Data, Not Model Objects
------------------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 An integrated transport function should accept scalars, NumPy arrays, structured records, one-element record containers, and the packed ``simulation`` and ``data`` state.
 It should not accept an ``MCDCObject`` instance or follow Python object references.
@@ -89,7 +94,7 @@ For example, recover a prepared distribution by simulation-local ID instead of p
    distribution = simulation["distributions"][source["energy_group_pmf_ID"]]
 
 Keep Types Stable
------------------
+^^^^^^^^^^^^^^^^^
 
 Numba determines a compiled function's types from its arguments and control flow.
 Make those types unambiguous:
@@ -101,9 +106,6 @@ Make those types unambiguous:
 - Keep structured-record field names fixed; do not compute field names at run time.
 - Avoid heterogeneous Python lists, dictionaries, sets, generators, and dynamically created classes in transport.
 
-Numba may accept a construct on the CPU without making it available on the GPU.
-When a function is shared, compatibility with the stricter target is the relevant standard.
-
 For example, initialize a scalar result before control flow so every path returns the same type:
 
 .. code-block:: python
@@ -118,7 +120,7 @@ For example, initialize a scalar result before control flow so every path return
        return index
 
 Represent Variable-Length Data Explicitly
------------------------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 Do not recover variable-length model data by allocating a new Python container.
 Read it from ``data`` using the metadata in its owning record.
@@ -136,7 +138,7 @@ For a new variable-length field, declare the field on the Python model class and
 Do not hand-maintain offset arithmetic in several transport modules.
 
 Use Explicit Dispatch
----------------------
+^^^^^^^^^^^^^^^^^^^^^
 
 Dispatch on integer constants through a small interface function rather than using Python ``isinstance`` checks or methods on runtime records:
 
@@ -157,9 +159,9 @@ Use the actual category interface and constants already defined for that family.
 When adding a subtype, update every exhaustive dispatch site and test an unsupported value deliberately if the interface defines fallback behavior.
 
 Control Allocation and Mutation
--------------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Particle histories repeatedly execute transport functions, so temporary allocation can be both expensive and difficult to support consistently across targets.
+Particle histories repeatedly execute transport functions, so temporary allocation can be expensive and difficult for Numba to optimize.
 
 - Reuse particle containers, banks, tally arrays, and scratch state allocated during preparation.
 - Update structured fields or ``data`` through explicit assignments and generated setters.
@@ -189,23 +191,59 @@ When a scalar structured record must be mutated across a function boundary, pass
        counter = counter_container[0]
        counter["value"] += 1
 
-Stay Within the CPU/GPU Common Subset
--------------------------------------
+Debug Python and Numba-CPU
+^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-For code intended to run on both targets:
+When a change fails, isolate the layer:
+
+#. **Python construction** -- confirm that the model compiles and the expected objects, IDs, offsets, and data are present.
+#. **Python transport** -- verify the algorithm and state mutation with JIT disabled.
+#. **Numba-CPU** -- resolve typing, unsupported-operation, and compiled-runtime failures.
+
+Resolve each layer before moving to the next.
+A passing Python test establishes behavior but does not establish Numba type compatibility.
+For example, investigate an unexpected physical result in Python transport and a Numba ``TypingError`` during Numba-CPU porting.
+
+Verify Numba-CPU Support
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+Before considering the Numba-CPU implementation complete:
+
+- The model compiles into the expected packed representation.
+- Focused unit tests exercise the numerical behavior in Python.
+- The same tests or a representative regression case pass in Numba-CPU mode.
+- Python and Numba-CPU results agree within the test's numerical tolerance.
+- Existing examples still construct successfully when the public API or model compilation changed.
+- User and developer documentation describe the new behavior and any CPU limitation.
 
-- Use numerical control flow and operations already established in nearby shared transport modules.
+Numba-GPU Development
+---------------------
+
+Numba-CPU is a valid final implementation when it satisfies the intended workloads and project requirements.
+Add Numba-GPU support as a later phase when those requirements call for accelerator execution.
+Begin this phase from a verified Numba-CPU implementation and retain its tests as the behavioral baseline.
+Read :doc:`../architecture/transport_execution` for MC/DC's GPU compilation and runtime architecture.
+
+Apply Additional GPU Constraints
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Numba-CPU supports Python and Numba features that may not be available in device code.
+For transport code that will execute on a GPU:
+
+- Use numerical control flow and operations established in nearby GPU-compatible transport modules.
 - Avoid Python exceptions as ordinary control flow.
 - Keep file access, printing, timing, MPI orchestration, and other host services outside device functions.
-- Do not use Numba ``objmode`` in a path that must execute on the GPU.
-- Avoid relying on a CPU-only Numba feature merely because Numba-CPU compiles it.
+- Do not use Numba ``objmode`` in a device path.
+- Replace CPU-only Numba features with device-compatible operations.
 - Keep target-specific atomics, memory operations, and scheduling behind the existing GPU adaptation layer.
 
-Backend-specific code is appropriate when the execution model truly differs.
-Keep the shared numerical operation in ``mcdc/transport`` when possible, and put only the required adaptation under ``mcdc/code_factory/gpu``.
-Document why the paths differ and test their physical equivalence.
+Separate Shared and GPU-Specific Code
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Keep the shared numerical operation in ``mcdc/transport`` when possible, and place only the required device adaptation under ``mcdc/code_factory/gpu``.
+Document why a GPU path differs and test its physical equivalence with Python and Numba-CPU.
 
-For example, keep the shared numerical operation free of reporting or device-management code:
+For example, keep reporting on the host while the numerical operation remains available to compiled transport:
 
 .. code-block:: python
 
@@ -217,34 +255,22 @@ For example, keep the shared numerical operation free of reporting or device-man
    def report_survival_biasing(survival_probability):
        print(f"Survival probability: {survival_probability}")
 
-Debug in Layers
----------------
-
-When a change fails, isolate the layer:
-
-#. **Python construction** -- confirm that the model compiles and the expected objects, IDs, offsets, and data are present.
-#. **Python transport** -- verify the algorithm and state mutation with JIT disabled.
-#. **Numba-CPU** -- resolve typing, unsupported-operation, and compiled-runtime failures.
-#. **Numba-GPU** -- resolve device compilation, memory, atomic, and scheduling failures.
-
-Do not begin by diagnosing a GPU compiler error if the same calculation is already incorrect in Python.
-Conversely, a passing Python test does not prove that the function is type-stable or device compatible.
+Debug Numba-GPU
+^^^^^^^^^^^^^^^
 
-For example, investigate an unexpected physical result in Python transport, a Numba ``TypingError`` during Numba-CPU porting, and a device-link or unsupported-atomic error in the Numba-GPU layer.
+Start GPU diagnosis only after the Python and Numba-CPU tests pass.
+Then isolate device compilation, memory placement, atomics, and Harmonize scheduling.
+For example, investigate a device-link or unsupported-atomic error in this phase without reopening already verified CPU behavior.
 
-Verification Checklist
-----------------------
+Verify Numba-GPU Support
+^^^^^^^^^^^^^^^^^^^^^^^^
 
-Before considering a transport extension complete:
+Before claiming Numba-GPU support:
 
-- The model compiles into the expected packed representation.
-- Focused unit tests exercise the new numerical behavior in Python.
-- The same tests or representative regression case pass in Numba-CPU mode.
-- Python and Numba-CPU results agree within the test's numerical tolerance.
-- A supported GPU environment exercises the path.
+- The Python and Numba-CPU verification remains passing.
+- A supported GPU environment exercises every device path being claimed.
 - GPU results preserve the same physical behavior within appropriate numerical and statistical tolerances.
-- Existing examples still construct successfully when the public API or model compilation changed.
-- User and developer documentation describe any new behavior or limitation.
+- GPU-specific adaptations and limitations are documented.
 
 Use the :doc:`../../contributing/index` for repository commands, continuous-integration coverage, and regression-test options.
 For changes affecting public inputs, follow :doc:`../../contributing/example_validation`.

From ca70f1f218bddfe9b30de24a32b9a1f8ae175d9f Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 5 Aug 2026 13:43:39 +0700
Subject: [PATCH 096/202] organize prepare and simulation compilation
 finalization

---
 CHANGELOG.md                                  |   2 +
 .../developer_guide/architecture/index.rst    |  17 +-
 .../python_first_numba_accelerated_design.rst |   2 +-
 .../architecture/runtime_data_layout.rst      |   2 +-
 .../architecture/simulation_compilation.rst   |  26 +-
 .../extending/extending_the_object_model.rst  |  12 +-
 ...riting_numba_compatible_transport_code.rst |  31 +-
 mcdc/code_factory/numba_layers_generator.py   |   3 +-
 mcdc/code_factory/python_objects_compiler.py  |  15 +-
 mcdc/config.py                                | 322 +++++++++++-------
 mcdc/main.py                                  | 164 +--------
 mcdc/object_/base.py                          |   3 +
 mcdc/object_/element.py                       |   2 +-
 mcdc/object_/nuclide.py                       |   2 +-
 mcdc/object_/simulation.py                    | 115 ++++++-
 test/unit/test_config.py                      |  20 ++
 test/unit/test_object_compilation.py          |  38 +++
 17 files changed, 443 insertions(+), 333 deletions(-)
 create mode 100644 test/unit/test_config.py

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 17ec3adcd..d77311deb 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -11,6 +11,8 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/2.0.0/),
 ### Changed
 
 - Move regression tests from the custom `run.py` harness to pytest-based collection and reporting from [@massimolarsen]
+- Modernize and reorganize the documentation around distinct user, API reference, theory, project, and developer paths; adopt the PyData Sphinx Theme; and expand the architecture and extension guidance from [@ilhamv]
+- Move model-specific finalization into simulation compilation and reserve runtime preparation for framework-level packing and execution setup from [@ilhamv]
 - **Breaking:** Redesign model construction around explicit `mcdc.Simulation`
   instances, replacing the global simulation, settings, run, and visualization
   interfaces. Each simulation now owns and compiles its complete object graph,
diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index 9d86a9c2a..e584f3d1c 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -28,8 +28,8 @@ Component Responsibility
 ------------------------
 
 The source tree follows the same separation of responsibilities shown in the architecture flow.
-Model-facing components define and collect the simulation.
-Code-factory components compile the model and prepare its runtime representation.
+Model-facing components define, collect, and finalize the simulation.
+Code-factory components coordinate object discovery and generate its runtime representation.
 Transport components implement the numerical algorithms shared by all execution modes.
 The table maps each component to its corresponding architecture role.
 Paths in the component column are relative to the top-level ``mcdc/`` package.
@@ -42,14 +42,17 @@ Paths in the component column are relative to the top-level ``mcdc/`` package.
      - Architecture role
      - Responsibility
    * - ``object_/``
-     - Model definition
-     - Defines the Python-side model, configuration, and runtime-state classes.
+     - Model definition and compilation
+     - Defines Python-side model classes and their object-local finalization hooks.
    * - :class:`mcdc.Simulation` in ``object_/simulation.py``
      - Model definition and control
-     - Owns model roots and configuration and controls compilation, visualization, and execution.
+     - Owns model roots and configuration, resolves model-wide finalization, and controls compilation, visualization, and execution.
    * - ``code_factory/python_objects_compiler.py``
      - Simulation compilation
-     - Discovers and registers the connected Python object graph.
+     - Coordinates recursive discovery, registration, and model-wide finalization.
+   * - ``main.prepare``
+     - Runtime preparation
+     - Coordinates framework-level packing, execution-resource allocation, backend configuration, and external runtime state.
    * - ``code_factory/numba_layers_generator.py``
      - Runtime preparation
      - Derives structured dtypes, packs runtime state, generates accessors, and initiates GPU-specific preparation when requested.
@@ -68,7 +71,7 @@ Paths in the component column are relative to the top-level ``mcdc/`` package.
 The ``mcdc/object_`` modules, :class:`mcdc.Simulation`, and ``python_objects_compiler.py`` implement the model-definition and simulation-compilation stages.
 :doc:`simulation_compilation` explains their relationships, while :doc:`../extending/extending_the_object_model` explains how contributors can extend them.
 
-The ``numba_layers_generator.py``, runtime ``simulation`` and ``data``, and generated ``mcdc_get`` and ``mcdc_set`` modules implement runtime preparation and form the data boundary between model construction and transport.
+``main.prepare``, ``numba_layers_generator.py``, runtime ``simulation`` and ``data``, and generated ``mcdc_get`` and ``mcdc_set`` implement framework-level runtime preparation and form the data boundary between model compilation and transport.
 :doc:`runtime_data_layout` explains their roles.
 
 The ``mcdc/transport`` package implements the shared-transport stage.
diff --git a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
index 82fed894f..cf4125acb 100644
--- a/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
+++ b/docs/source/developer_guide/architecture/python_first_numba_accelerated_design.rst
@@ -186,6 +186,6 @@ Future changes should preserve the ability to stop at any development stage, kee
 Where to Go Next
 ----------------
 
-For model preparation, continue with :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
+For model compilation and runtime preparation, continue with :doc:`simulation_compilation` and :doc:`runtime_data_layout`.
 For execution, read :doc:`transport_execution`.
 Contributors implementing a transport change should use :doc:`../extending/writing_numba_compatible_transport_code`.
diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index 065d8ef4c..4958e2351 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -4,7 +4,7 @@
 Runtime Data Layout
 ===================
 
-After model compilation has discovered and ordered the Python object graph, ``mcdc.main.prepare`` calls ``generate_numba_layers`` in ``mcdc.code_factory`` to create the runtime representation used by transport.
+After model compilation has discovered, finalized, and ordered the Python object graph, ``mcdc.main.prepare`` calls ``generate_numba_layers`` in ``mcdc.code_factory`` to create the runtime representation used by transport.
 The representation has two complementary parts:
 
 ``simulation``
diff --git a/docs/source/developer_guide/architecture/simulation_compilation.rst b/docs/source/developer_guide/architecture/simulation_compilation.rst
index 5dde4fd3d..64110efcd 100644
--- a/docs/source/developer_guide/architecture/simulation_compilation.rst
+++ b/docs/source/developer_guide/architecture/simulation_compilation.rst
@@ -9,7 +9,7 @@ Materials, surfaces, cells, sources, tallies, settings, and techniques can conta
 A :class:`mcdc.Simulation` owns the roots of one model and turns that connected object graph into a deterministic, simulation-local snapshot.
 
 This first compilation stage is entirely a Python operation.
-It establishes the model that later runtime preparation will pack for Python, Numba-CPU, or Numba-GPU execution.
+It discovers the model, finalizes object-local and model-wide state, and establishes the snapshot that runtime preparation will pack for Python, Numba-CPU, or Numba-GPU execution.
 
 Why a Simulation Context Is Needed
 ----------------------------------
@@ -41,10 +41,10 @@ MC/DC uses several related forms of compilation:
      - Responsibility
      - Primary implementation
    * - Model compilation
-     - Discover objects, register them once, and assign local IDs.
-     - ``Simulation.compile`` and ``mcdc/code_factory/python_objects_compiler.py``
+     - Discover objects, register them once, assign local IDs, and finalize model-dependent state.
+     - ``mcdc/object_/``, ``Simulation.compile``, and ``mcdc/code_factory/python_objects_compiler.py``
    * - Runtime preparation
-     - Derive run state and pack the model into ``simulation`` and ``data``.
+     - Pack the finalized model, allocate execution resources, and configure the selected backend.
      - ``mcdc.main.prepare`` and ``mcdc/code_factory/numba_layers_generator.py``
    * - Backend compilation
      - Compile shared transport functions for a CPU or GPU target.
@@ -174,6 +174,19 @@ Discovery follows actual Python references.
 For example, a root cell reaches its region, the region reaches its surfaces, and the cell's fill reaches its material or child universe.
 Users therefore attach root cells rather than manually registering every referenced object.
 
+Object and Model Finalization
+-----------------------------
+
+Discovery and finalization occur within the same model-compilation snapshot.
+An object's ``_compile_into_simulation`` hook handles work owned by that object, including canonicalizing Python inputs, compiling excluded references, and deriving fields from assigned IDs.
+
+Some values require the complete discovered model rather than one object.
+After the explicit model roots have been traversed, ``Simulation._finalize_compilation`` resolves these model-wide relationships and invariants, such as completing material data, normalizing source probabilities, adapting tally shapes, deriving particle-bank capacities, and initializing state from the final settings and MPI decomposition.
+The compiler traverses embedded simulation configuration before model-wide finalization, and finalization logic explicitly compiles any runtime-visible dependencies it creates.
+
+This boundary keeps scientific model rules in ``mcdc/object_/``.
+The orchestration in ``python_objects_compiler.py`` changes only when the compilation framework gains a new phase or registered category, while ``mcdc.main.prepare`` remains responsible for framework-level runtime setup after the model is complete.
+
 Deduplication and Cycles
 ------------------------
 
@@ -212,6 +225,7 @@ Snapshot Lifecycle
 
 ``set_model``, ``set_sources``, and ``set_tallies`` invalidate the compiled state.
 ``run`` and ``visualize_model`` call ``compile`` automatically when the simulation is not compiled, so most user inputs do not need an explicit call.
+Command-line overrides are applied before this compilation so model-wide derived state reflects the effective settings.
 
 An explicit call is useful for inspecting discovered objects and assigned IDs:
 
@@ -254,8 +268,8 @@ The objects remain owned by the same ``Simulation`` throughout the study.
 From Objects to Runtime Data
 ----------------------------
 
-Model compilation leaves the original Python objects intact and populates the simulation's ordered registries.
-Runtime preparation then reads those objects, derives structured dtypes from their annotations, and packs their values.
+Model compilation finalizes the original Python objects and populates the simulation's ordered registries.
+Runtime preparation then reads that complete snapshot, derives structured dtypes from its annotations, and packs its values while allocating framework-owned execution resources.
 
 Continue with :doc:`runtime_data_layout` for that conversion.
 For the user-facing construct-to-output workflow, see :doc:`../../user_guide/simulation_lifecycle`.
diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index 955fcf05c..bd2faa2d1 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -104,7 +104,7 @@ Initialization
       fill_ID: int
 
 Compilation hook
-   Use the inherited ``_compile_into_simulation`` implementation unless the class must canonicalize objects, compile excluded references, or derive fields from assigned object IDs.
+   Use the inherited ``_compile_into_simulation`` implementation unless the class must canonicalize objects, compile excluded references, derive fields from assigned object IDs, or otherwise finalize state owned by that object.
 
    .. code-block:: python
 
@@ -134,6 +134,16 @@ Compilation hook
 
    Do not assign ``compile_ID``, ``ID``, or ``sub_ID`` manually.
 
+Model-wide finalization
+   Object hooks should not normalize or coordinate unrelated registries.
+   When a value requires the complete discovered model, coordinate it once in ``Simulation._finalize_compilation`` instead.
+   Source-probability normalization, particle-bank capacities, and settings derived from the complete material or tally collections are examples of model-wide finalization.
+   Explicitly compile any new runtime-visible object introduced during this phase because ordinary recursive discovery has already occurred.
+
+   ``compile_simulation`` orchestrates recursive discovery and calls this model-wide finalization phase.
+   Change the compiler orchestration only when adding a new compilation phase or registered category.
+   Do not place model-specific finalization in ``mcdc.main.prepare``; that function is reserved for framework-level packing, resource allocation, backend configuration, and external runtime state.
+
 Represent Fields Deliberately
 -----------------------------
 
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index fc7001631..f9d4aa0c2 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -13,36 +13,49 @@ Numba-CPU Development
 
 Complete the Python and Numba-CPU implementation before considering additional execution targets.
 
-Choose the Host or Transport Layer
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Choose Between Model Compilation and Particle Transport
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Place work on the host when it changes the model or prepares execution:
+First decide whether the change belongs to the Python model or to the algorithms executed during particle transport.
+
+Place model definition and model-finalization work in ``mcdc/object_/`` when it changes or completes the model before execution:
 
 - Validate and normalize user input.
 - Traverse Python objects or inspect their classes.
 - Add, remove, or resize model data.
 - Read files, construct tables, or derive run-wide configuration.
-- Allocate the packed state needed by transport.
+- Define the state that must later be available to transport.
+
+Use an object's ``_compile_into_simulation`` hook when the work belongs to that object and use ``Simulation._finalize_compilation`` when it requires the complete discovered model.
+``compile_simulation`` coordinates those phases and should change only when the compilation framework itself gains a new phase or registered category.
 
-Place work in transport when it must be performed during particle execution:
+``mcdc.main.prepare`` and the runtime generators in ``mcdc/code_factory/`` are framework-level machinery that pack the finalized model, allocate execution resources, and configure execution backends.
+Most scientific-method additions should not change them; extend them only when the runtime representation or execution framework cannot express the required behavior.
+See :doc:`extending_the_object_model` for the model-compilation workflow.
+
+Place event-time numerical work in ``mcdc/transport/`` when it must be performed during particle execution:
 
 - Inspect or mutate particle records.
 - Evaluate geometry or physics from prepared numerical data.
 - Sample distributions and update the random-number state.
 - Score tallies or update preallocated banks and counters.
 
-Do as much irregular work as practical before transport.
-A small amount of host-side preparation can turn a dynamic operation into simple indexed access inside a frequently called kernel.
+Do as much irregular work as practical during model compilation.
+A small amount of object-side finalization can turn a dynamic operation into simple indexed access inside a frequently called kernel.
 
-For example, derive a reusable coefficient once while preparing the model instead of recomputing it for every particle event:
+For example, derive a reusable coefficient in the model object's compilation hook instead of recomputing it for every particle event:
 
 .. code-block:: python
 
    # On the model class
    inverse_dx: float
 
-   def _prepare_spacing(self):
+   def _compile_into_simulation(self, simulation):
+       if not super()._compile_into_simulation(simulation):
+           return False
+
        self.inverse_dx = 1.0 / self.dx
+       return True
 
    # In transport
    index = int((particle["x"] - mesh["x0"]) * mesh["inverse_dx"])
diff --git a/mcdc/code_factory/numba_layers_generator.py b/mcdc/code_factory/numba_layers_generator.py
index afe5cc54a..d4fcf465d 100644
--- a/mcdc/code_factory/numba_layers_generator.py
+++ b/mcdc/code_factory/numba_layers_generator.py
@@ -88,6 +88,7 @@
 
 
 def generate_numba_layers(simulation):
+    """Pack a finalized Python model into the shared runtime data layers."""
     # ==================================================================================
     # Allocate key items for the Numba runtime layers:
     #   - Python annotations
@@ -112,7 +113,7 @@ def generate_numba_layers(simulation):
         else:
             records[mcdc_class.label] = {}
 
-    # Particle banks
+    # Allocate particle banks from capacities finalized during simulation compilation
     for name in bank_names:
         annotations[name] = {}
         structures[name] = []
diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index 0b7aff469..52703f22a 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -1,5 +1,3 @@
-import numpy as np
-
 from mcdc.object_.base import MCDCObject, MCDCPolymorphic
 from mcdc.object_.cell import Region, Cell
 from mcdc.object_.data import DataBase, DataNone
@@ -21,6 +19,12 @@
 
 
 def compile_simulation(simulation: Simulation):
+    """Discover, register, and finalize one simulation's Python model.
+
+    Recursive object hooks perform object-local compilation. Once discovery is
+    complete, the owning :class:`~mcdc.object_.simulation.Simulation` resolves
+    model-wide state before runtime packing begins.
+    """
     # Preserve explicitly configured roots before resetting their registered
     # object lists. Geometry members may reference these objects and compile
     # them while the model graph is traversed.
@@ -56,11 +60,8 @@ def compile_simulation(simulation: Simulation):
     # simulation configuration objects such as transport techniques.
     simulation._compile_members_into_simulation(simulation)
 
-    # Apply settings as needed
-    settings = simulation.settings
-    if simulation.settings.neutron_eigenvalue_mode:
-        simulation.k_cycle = np.zeros(settings.N_cycle)
-        simulation.gyration_radius = np.zeros(settings.N_cycle)
+    # Resolve state that depends on the complete discovered model
+    simulation._finalize_compilation()
 
 
 def register_object(object_: MCDCObject, simulation: Simulation) -> bool:
diff --git a/mcdc/config.py b/mcdc/config.py
index 4979c5fcd..7af96732f 100644
--- a/mcdc/config.py
+++ b/mcdc/config.py
@@ -1,103 +1,103 @@
-import argparse, os
+"""Process-wide command-line and execution configuration for MC/DC.
 
-parser = argparse.ArgumentParser(description="MC/DC: Monte Carlo Dynamic Code")
+Importing this module parses MC/DC's known command-line arguments, manages
+generated-code caches, and configures Numba for the selected execution mode.
+Simulation-specific command-line overrides are applied later, at the beginning
+of :meth:`mcdc.Simulation.compile`.
+"""
 
-# ======================================================================================
-# Run mode
-# ======================================================================================
-
-parser.add_argument(
-    "--mode",
-    type=str,
-    help="Run mode",
-    choices=["python", "numba", "numba_debug"],
-    default="python",
-)
+import argparse
+import shutil
+from pathlib import Path
 
-parser.add_argument(
-    "--target", type=str, help="Target", choices=["cpu", "gpu"], default="cpu"
-)
+from mpi4py import MPI
 
 # ======================================================================================
-# Settings
+# Command-line interface
 # ======================================================================================
 
-parser.add_argument("--N_particle", type=int, help="Number of particles")
-parser.add_argument("--N_batch", type=int, help="Number of batches")
-parser.add_argument("--output", type=str, help="Output file name")
-parser.add_argument("--progress_bar", default=True, action="store_true")
-parser.add_argument("--no-progress_bar", dest="progress_bar", action="store_false")
-parser.add_argument("--runtime_output", default=False, action="store_true")
-
 
-# ======================================================================================
-# Numba
-# ======================================================================================
-
-parser.add_argument("--clear_cache", action="store_true")
-parser.add_argument("--caching", action="store_true", default=False)
-parser.add_argument("--no_caching", dest="caching", action="store_false")
+def _build_parser() -> argparse.ArgumentParser:
+    """Create the MC/DC command-line argument parser."""
+    parser = argparse.ArgumentParser(description="MC/DC: Monte Carlo Dynamic Code")
 
-# ======================================================================================
-# GPU mode
-# ======================================================================================
+    # Execution mode and target
+    parser.add_argument(
+        "--mode",
+        type=str,
+        help="Run mode",
+        choices=["python", "numba", "numba_debug"],
+        default="python",
+    )
+    parser.add_argument(
+        "--target", type=str, help="Target", choices=["cpu", "gpu"], default="cpu"
+    )
 
-parser.add_argument(
-    "--gpu_state_storage",
-    type=str,
-    help="Strategy used in GPU execution (event or async).",
-    choices=["separate", "managed", "united"],
-    default="separate",
-)
-
-parser.add_argument(
-    "--gpu_strategy",
-    type=str,
-    help="Strategy used in GPU execution (event or async).",
-    choices=["async", "event"],
-    default="event",
-)
-
-parser.add_argument(
-    "--gpu_block_count",
-    type=int,
-    help="Number of blocks used in GPU execution.",
-    default=240,
-)
-
-parser.add_argument(
-    "--gpu_arena_size",
-    type=int,
-    help="Capacity of each intermediate data buffer used, as a particle count.",
-    default=0x100000,
-)
-
-parser.add_argument(
-    "--gpu_rocm_path",
-    type=str,
-    help="Path to ROCm installation for use in GPU execution.",
-    default=None,
-)
-
-parser.add_argument(
-    "--gpu_cuda_path",
-    type=str,
-    help="Path to CUDA installation for use in GPU execution.",
-    default=None,
-)
-
-parser.add_argument(
-    "--gpu_share_stride",
-    type=int,
-    help="Number of gpus that are shared across adjacent ranks.",
-    default=1,
-)
+    # Simulation-setting overrides
+    parser.add_argument("--N_particle", type=int, help="Number of particles")
+    parser.add_argument("--N_batch", type=int, help="Number of batches")
+    parser.add_argument("--output", type=str, help="Output file name")
+    parser.add_argument("--progress_bar", default=True, action="store_true")
+    parser.add_argument("--no-progress_bar", dest="progress_bar", action="store_false")
+    parser.add_argument("--runtime_output", default=False, action="store_true")
+
+    # Numba compilation and cache behavior
+    parser.add_argument("--clear_cache", action="store_true")
+    parser.add_argument("--caching", action="store_true", default=False)
+    parser.add_argument("--no_caching", dest="caching", action="store_false")
+
+    # GPU execution
+    parser.add_argument(
+        "--gpu_state_storage",
+        type=str,
+        help="GPU state-storage strategy.",
+        choices=["separate", "managed", "united"],
+        default="separate",
+    )
+    parser.add_argument(
+        "--gpu_strategy",
+        type=str,
+        help="GPU scheduling strategy.",
+        choices=["async", "event"],
+        default="event",
+    )
+    parser.add_argument(
+        "--gpu_block_count",
+        type=int,
+        help="Number of GPU blocks.",
+        default=240,
+    )
+    parser.add_argument(
+        "--gpu_arena_size",
+        type=int,
+        help="Particle capacity of each intermediate GPU data buffer.",
+        default=0x100000,
+    )
+    parser.add_argument(
+        "--gpu_rocm_path",
+        type=str,
+        help="Path to the ROCm installation.",
+        default=None,
+    )
+    parser.add_argument(
+        "--gpu_cuda_path",
+        type=str,
+        help="Path to the CUDA installation.",
+        default=None,
+    )
+    parser.add_argument(
+        "--gpu_share_stride",
+        type=int,
+        help="Number of adjacent MPI ranks sharing each GPU.",
+        default=1,
+    )
 
+    return parser
 
-# ======================================================================================
-# Config processor
-# ======================================================================================
 
+# Preserve these module-level names because execution and GPU modules consume them.
+parser = _build_parser()
+# Ignore unrelated arguments supplied by pytest, notebooks, or outer Python drivers.
 args, unargs = parser.parse_known_args()
 
 mode = args.mode
@@ -106,53 +106,115 @@
 caching = args.caching
 clear_cache = args.clear_cache
 
-from mpi4py import MPI
-import shutil
 
-src_path = os.path.dirname(os.path.abspath(__file__))
-cache_path = f"{src_path}/__pycache__"
+# ======================================================================================
+# Simulation-setting overrides
+# ======================================================================================
+
+
+def override_settings(simulation) -> bool:
+    """Apply command-line overrides before compiling a simulation snapshot."""
+    settings = simulation.settings
+    changed = False
+
+    def set_setting(name, value):
+        nonlocal changed
+        if value is None or getattr(settings, name) == value:
+            return
+        setattr(settings, name, value)
+        changed = True
+
+    # These command-line options directly replace public Simulation settings.
+    set_setting("N_particle", args.N_particle)
+    set_setting("N_batch", args.N_batch)
+    set_setting("output_name", args.output)
+    set_setting("use_progress_bar", args.progress_bar)
+
+    # GPU names are translated into the integer constants stored at runtime.
+    if target == "gpu":
+        from mcdc.constant import (
+            GPU_STORAGE_MANAGED,
+            GPU_STORAGE_SEPARATE,
+            GPU_STORAGE_UNITED,
+            GPU_STRATEGY_ASYNC,
+            GPU_STRATEGY_EVENT,
+        )
+
+        strategy = {
+            "async": GPU_STRATEGY_ASYNC,
+            "event": GPU_STRATEGY_EVENT,
+        }[args.gpu_strategy]
+        storage = {
+            "separate": GPU_STORAGE_SEPARATE,
+            "managed": GPU_STORAGE_MANAGED,
+            "united": GPU_STORAGE_UNITED,
+        }[args.gpu_state_storage]
+
+        set_setting("gpu_strategy", strategy)
+        set_setting("gpu_storage", storage)
+
+    return changed
+
+
+# ======================================================================================
+# Process-wide initialization
+# ======================================================================================
+
+
+def _manage_runtime_caches() -> None:
+    """Clear generated-code caches when caching is disabled or reset."""
+    should_clear = not caching or clear_cache
+    if should_clear and MPI.COMM_WORLD.Get_rank() == 0:
+        cache_directories = (
+            Path(__file__).resolve().parent / "__pycache__",
+            Path.cwd() / "__harmonize_cache__",
+        )
+        for cache_directory in cache_directories:
+            if cache_directory.exists():
+                shutil.rmtree(cache_directory)
 
-if ((caching == False) or (clear_cache == True)) and (MPI.COMM_WORLD.Get_rank() == 0):
-    if os.path.exists(cache_path):
-        shutil.rmtree(cache_path)
-    if os.path.exists("__harmonize_cache__"):
-        shutil.rmtree("__harmonize_cache__")
+    # Other ranks must not use a cache while the root rank is removing it.
+    if MPI.COMM_WORLD.Get_size() > 1:
+        MPI.COMM_WORLD.Barrier()
 
-if MPI.COMM_WORLD.Get_size() > 1:
-    MPI.COMM_WORLD.Barrier()
 
-from mcdc.print_ import (
-    print_warning,
-)
-import numba as nb
+def _configure_numba() -> None:
+    """Configure Numba for Python, compiled, or diagnostic execution."""
+    import numba as nb
+
+    if mode == "python":
+        nb.config.DISABLE_JIT = True
+        return
 
-if mode == "python":
-    nb.config.DISABLE_JIT = True
-elif mode == "numba":
     nb.config.DISABLE_JIT = False
-    nb.config.NUMBA_DEBUG_CACHE = 1
-    nb.config.THREADING_LAYER = "workqueue"
-elif mode == "numba_debug":
-    msg = "\n >> Entering numba debug mode\n >> will result in slower code and longer compile times\n >> to configure debug options see main.py"
-    print_warning(msg)
-
-    nb.config.DISABLE_JIT = False  # turns on the jitter
-    nb.config.DEBUG = False  # turns on debugging options
-    nb.config.NUMBA_FULL_TRACEBACKS = (
-        1  # enables errors from sub-packages to be printed
-    )
-    nb.config.NUMBA_BOUNDSCHECK = 1  # checks bounds errors of vectors
-    nb.config.NUMBA_COLOR_SCHEME = (
-        "dark_bg"  # prints error messages for dark background terminals
-    )
-    nb.config.NUMBA_DEBUG_NRT = 1  # Numba run time (NRT) statistics counter
-    nb.config.NUMBA_DEBUG_TYPEINFER = (
-        1  # print out debugging information about type inference.
-    )
-    nb.config.NUMBA_ENABLE_PROFILING = 1  # enables profiler use
-    nb.config.NUMBA_DUMP_CFG = 1  # prints out a control flow diagram
-    nb.config.NUMBA_OPT = 0  # forums un optimized code from compilers
-    nb.config.NUMBA_DEBUGINFO = 1  #
-    nb.config.NUMBA_EXTEND_VARIABLE_LIFETIMES = (
-        1  # allows for inspection of numba variables after end of compilation
+
+    if mode == "numba":
+        nb.config.NUMBA_DEBUG_CACHE = 1
+        nb.config.THREADING_LAYER = "workqueue"
+        return
+
+    from mcdc.print_ import print_warning
+
+    print_warning(
+        "\n >> Entering Numba debug mode"
+        "\n >> This mode is slower and enables additional diagnostics"
     )
+
+    # Runtime checks and diagnostic output
+    nb.config.DEBUG = False
+    nb.config.NUMBA_FULL_TRACEBACKS = 1
+    nb.config.NUMBA_BOUNDSCHECK = 1
+    nb.config.NUMBA_COLOR_SCHEME = "dark_bg"
+    nb.config.NUMBA_DEBUG_NRT = 1
+    nb.config.NUMBA_DEBUG_TYPEINFER = 1
+
+    # Generated-code inspection and debugger support
+    nb.config.NUMBA_ENABLE_PROFILING = 1
+    nb.config.NUMBA_DUMP_CFG = 1
+    nb.config.NUMBA_OPT = 0
+    nb.config.NUMBA_DEBUGINFO = 1
+    nb.config.NUMBA_EXTEND_VARIABLE_LIFETIMES = 1
+
+
+_manage_runtime_caches()
+_configure_numba()
diff --git a/mcdc/main.py b/mcdc/main.py
index 01ee56487..5c4bbc8b7 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -1,7 +1,4 @@
-from mcdc.object_.material import MaterialBase
 from mcdc.object_.simulation import Simulation
-from mcdc.object_.base import MCDCObject
-from mcdc.object_.universe import Lattice, Universe
 
 # ======================================================================================
 # Run Simulation
@@ -9,6 +6,7 @@
 
 
 def run_simulation(simulationPy: Simulation):
+    """Compile when needed, prepare runtime state, and execute a simulation."""
     import mcdc.print_ as print_module
     from mpi4py import MPI
 
@@ -26,9 +24,6 @@ def run_simulation(simulationPy: Simulation):
     # TIMER: preparation
     time_prep_start = MPI.Wtime()
 
-    # Override settings with command-line arguments
-    override_settings(simulationPy)
-
     # Generate the program state:
     #   - `simulation`: the simulation structure, storing fixed side data and meta data
     #                   that describes arbitrarily-sized data
@@ -115,125 +110,17 @@ def run_simulation(simulationPy: Simulation):
 # ======================================================================================
 
 
-def prepare(simulationPy):
-    import math
+def prepare(simulationPy: Simulation):
+    """Create framework-owned runtime state for a compiled simulation.
 
+    Model-specific finalization occurs during :meth:`mcdc.Simulation.compile`.
+    This function packs that model, allocates execution resources, configures
+    the selected backend, and loads any external source-particle state.
+    """
     from mpi4py import MPI
 
-    from mcdc.object_.material import (
-        Material,
-        MaterialMG,
-        set_elements_from_nuclides,
-        set_nuclides_from_elements,
-        update_fissionable_from_nuclides,
-    )
-
-    # ==================================================================================
-    # Adjust simulation settings as needed
-    # ==================================================================================
-
-    # Get settings
     settings = simulationPy.settings
 
-    # Set appropriate time boundary
-    settings.time_boundary = min(
-        [settings.time_boundary] + [tally.time[-1] for tally in simulationPy.tallies]
-    )
-
-    # ==================================================================================
-    # Set material data as needed
-    # ==================================================================================
-
-    # Set material compositions based on transported particles
-    for material in simulationPy.materials:
-        if not isinstance(material, Material):
-            continue
-
-        if settings.neutron_transport and len(material.nuclides) == 0:
-            set_nuclides_from_elements(material, simulationPy)
-
-        if settings.electron_transport and len(material.elements) == 0:
-            set_elements_from_nuclides(material, simulationPy)
-
-    # Set nuclear and atomic data for transported particles
-    if settings.neutron_transport:
-        for nuclide in simulationPy.nuclides:
-            nuclide.set_neutron_data(simulationPy)
-
-        for material in simulationPy.materials:
-            if isinstance(material, Material):
-                update_fissionable_from_nuclides(material)
-
-    if settings.electron_transport:
-        for element in simulationPy.elements:
-            element.set_electron_data(simulationPy)
-
-    # Set physics mode
-    if len(simulationPy.materials) == 0:
-        # Default physics in dummy mode
-        settings.neutron_multigroup_mode = True
-    else:
-        settings.neutron_multigroup_mode = isinstance(
-            simulationPy.materials[0], MaterialMG
-        )
-
-    # ==================================================================================
-    # Adjust simulation parameters as needed
-    # ==================================================================================
-
-    # Reset time grid size of all tallies if census-based tally is desired
-    if settings.use_census_based_tally:
-        N_bin = settings.census_tally_frequency
-        for tally in simulationPy.tallies:
-            tally._use_census_based_tally(N_bin, simulationPy)
-
-    # Normalize source probability
-    norm = 0.0
-    for source in simulationPy.sources:
-        norm += source.probability
-    for source in simulationPy.sources:
-        source.probability /= norm
-
-    # Create root universe if not defined
-    if len(simulationPy.universes[0].cells) == 0:
-        simulationPy.universes[0].cells = simulationPy.cells
-
-    # Initial guess
-    simulationPy.k_eff = settings.k_init
-
-    # Activate tally scoring for fixed-source
-    if not settings.neutron_eigenvalue_mode:
-        simulationPy.cycle_active = True
-    # All active eigenvalue cycle?
-    elif settings.N_inactive == 0:
-        simulationPy.cycle_active = True
-
-    # ==================================================================================
-    # Set particle bank sizes
-    # ==================================================================================
-
-    # Some sizes
-    N_particle = settings.N_particle
-    N_work = math.ceil(N_particle / MPI.COMM_WORLD.Get_size())
-    N_census = settings.N_census
-
-    # Determine bank size
-    if settings.neutron_eigenvalue_mode or N_census == 1:
-        settings.future_bank_buffer_ratio = 0.0
-    if not settings.neutron_eigenvalue_mode and N_census == 1:
-        settings.census_bank_buffer_ratio = 0.0
-        settings.source_bank_buffer_ratio = 0.0
-    size_active = settings.active_bank_buffer
-    size_census = int((settings.census_bank_buffer_ratio) * N_work)
-    size_source = int((settings.source_bank_buffer_ratio) * N_work)
-    size_future = int((settings.future_bank_buffer_ratio) * N_work)
-
-    # Set bank size
-    simulationPy.bank_active.size[0] = size_active
-    simulationPy.bank_census.size[0] = size_census
-    simulationPy.bank_source.size[0] = size_source
-    simulationPy.bank_future.size[0] = size_future
-
     # ==================================================================================
     # Generate Numba runtime layers
     # ==================================================================================
@@ -320,43 +207,6 @@ def prepare(simulationPy):
 # ======================================================================================
 
 
-def override_settings(simulationPy):
-    import mcdc.config as config
-
-    settings = simulationPy.settings
-
-    if config.args.N_particle is not None:
-        settings.N_particle = config.args.N_particle
-    if config.args.N_batch is not None:
-        settings.N_batch = config.args.N_batch
-    if config.args.output is not None:
-        settings.output_name = config.args.output
-    if config.args.progress_bar is not None:
-        settings.use_progress_bar = config.args.progress_bar
-
-    # GPU settings
-    if config.target == "gpu":
-        from mcdc.constant import (
-            GPU_STRATEGY_ASYNC,
-            GPU_STRATEGY_EVENT,
-            GPU_STORAGE_SEPARATE,
-            GPU_STORAGE_MANAGED,
-            GPU_STORAGE_UNITED,
-        )
-
-        if config.args.gpu_strategy == "async":
-            settings.gpu_strategy = GPU_STRATEGY_ASYNC
-        elif config.args.gpu_strategy == "event":
-            settings.gpu_strategy = GPU_STRATEGY_EVENT
-
-        if config.args.gpu_state_storage == "separate":
-            settings.gpu_storage = GPU_STORAGE_SEPARATE
-        elif config.args.gpu_state_storage == "managed":
-            settings.gpu_storage = GPU_STORAGE_MANAGED
-        elif config.args.gpu_state_storage == "united":
-            settings.gpu_storage = GPU_STORAGE_UNITED
-
-
 def finalize(simulation):
     import mcdc.config as config
 
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index ca50a6ef2..a5fd7479f 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -36,6 +36,9 @@ def _compile_into_simulation(self, simulation) -> bool:
         Embedded ``MCDCBase`` objects participate in compilation without being
         registered in a simulation object collection. Registered
         :class:`MCDCObject` subclasses extend this lifecycle with an object ID.
+        Subclasses may extend this hook to validate or normalize their state,
+        compile excluded references, and derive fields that require the owning
+        simulation.
         """
         # Compile each embedded object once per simulation compilation
         if self.compile_ID == simulation.compile_ID:
diff --git a/mcdc/object_/element.py b/mcdc/object_/element.py
index 16148d8ee..c0234f20f 100644
--- a/mcdc/object_/element.py
+++ b/mcdc/object_/element.py
@@ -179,7 +179,7 @@ def set_electron_data(self, simulation):
 
         file.close()
 
-        # Register data loaded after model compilation.
+        # Register data loaded during object-model finalization.
         for reaction_container in rx_containers:
             for reaction in reaction_container:
                 reaction._compile_into_simulation(simulation)
diff --git a/mcdc/object_/nuclide.py b/mcdc/object_/nuclide.py
index 603c415aa..34f6f13f9 100644
--- a/mcdc/object_/nuclide.py
+++ b/mcdc/object_/nuclide.py
@@ -251,7 +251,7 @@ def set_neutron_data(self, simulation):
 
         file.close()
 
-        # Register data loaded after model compilation.
+        # Register data loaded during object-model finalization.
         for reaction_container in rx_containers:
             for reaction in reaction_container:
                 reaction._compile_into_simulation(simulation)
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 538494235..669477bc3 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -14,9 +14,10 @@
 
 ####
 
-import numpy as np
-
+import math
 from collections.abc import Sequence
+
+import numpy as np
 from mpi4py import MPI
 from numpy import float64, int64
 from numpy.typing import NDArray
@@ -57,8 +58,9 @@ class Simulation(MCDCBase):
     -----
     Geometry, sources, and tallies are supplied with :meth:`set_model`,
     :meth:`set_sources`, and :meth:`set_tallies`. :meth:`compile` walks the
-    resulting object graph, assigns IDs, and prepares it for conversion to the
-    packed arrays consumed by :mod:`mcdc.transport`.
+    resulting object graph, assigns IDs, and finalizes object-local and
+    model-wide state before conversion to the packed arrays consumed by
+    :mod:`mcdc.transport`.
 
     MC/DC uses one active simulation context per Python process. A model-object
     instance belongs to one simulation, although it may be referenced multiple
@@ -300,6 +302,92 @@ def _reset_model(self) -> None:
         self.lattices = []
         self.meshes = []
 
+    def _finalize_compilation(self) -> None:
+        """Finalize model-wide state after object discovery.
+
+        Object-specific compilation hooks register dependencies and derive
+        fields owned by one object. This method handles relationships and
+        invariants that require the complete simulation, before the model is
+        packed into the runtime representation. Any runtime-visible object
+        created here must be compiled explicitly because recursive discovery
+        has already completed.
+        """
+        from mcdc.object_.material import (
+            Material,
+            MaterialMG,
+            set_elements_from_nuclides,
+            set_nuclides_from_elements,
+            update_fissionable_from_nuclides,
+        )
+
+        settings = self.settings
+
+        # Limit transport to the latest requested tally boundary
+        settings.time_boundary = min(
+            [settings.time_boundary] + [tally.time[-1] for tally in self.tallies]
+        )
+
+        # Complete native-material compositions for the transported particles
+        for material in self.materials:
+            if not isinstance(material, Material):
+                continue
+            if settings.neutron_transport and len(material.nuclides) == 0:
+                set_nuclides_from_elements(material, self)
+            if settings.electron_transport and len(material.elements) == 0:
+                set_elements_from_nuclides(material, self)
+
+        # Load the physics data required by the completed material model
+        if settings.neutron_transport:
+            for nuclide in self.nuclides:
+                nuclide.set_neutron_data(self)
+            for material in self.materials:
+                if isinstance(material, Material):
+                    update_fissionable_from_nuclides(material)
+
+        if settings.electron_transport:
+            for element in self.elements:
+                element.set_electron_data(self)
+
+        # Determine the neutron physics representation
+        if len(self.materials) == 0:
+            settings.neutron_multigroup_mode = True
+        else:
+            settings.neutron_multigroup_mode = isinstance(self.materials[0], MaterialMG)
+
+        # Derive tally shapes that depend on simulation-wide settings
+        if settings.use_census_based_tally:
+            for tally in self.tallies:
+                tally._use_census_based_tally(settings.census_tally_frequency, self)
+
+        # Normalize source-selection probabilities across the complete source set
+        source_probability = sum(source.probability for source in self.sources)
+        for source in self.sources:
+            source.probability /= source_probability
+
+        # Derive particle-bank capacities from settings and the MPI decomposition
+        N_work = math.ceil(settings.N_particle / self.mpi_size)
+        N_census = settings.N_census
+
+        if settings.neutron_eigenvalue_mode or N_census == 1:
+            settings.future_bank_buffer_ratio = 0.0
+        if not settings.neutron_eigenvalue_mode and N_census == 1:
+            settings.census_bank_buffer_ratio = 0.0
+            settings.source_bank_buffer_ratio = 0.0
+
+        self.bank_active.size[0] = settings.active_bank_buffer
+        self.bank_census.size[0] = int(settings.census_bank_buffer_ratio * N_work)
+        self.bank_source.size[0] = int(settings.source_bank_buffer_ratio * N_work)
+        self.bank_future.size[0] = int(settings.future_bank_buffer_ratio * N_work)
+
+        # Initialize run state derived from the compiled settings
+        self.k_eff = settings.k_init
+        self.cycle_active = (
+            not settings.neutron_eigenvalue_mode or settings.N_inactive == 0
+        )
+        if settings.neutron_eigenvalue_mode:
+            self.k_cycle = np.zeros(settings.N_cycle)
+            self.gyration_radius = np.zeros(settings.N_cycle)
+
     # ==================================================================================
     # Simulation object setters
     # ==================================================================================
@@ -360,17 +448,22 @@ def set_tallies(self, tallies: Sequence[Tally]) -> None:
     # ==================================================================================
 
     def compile(self) -> None:
-        """Compile the Python object graph into a new simulation snapshot.
+        """Compile and finalize the Python model into a simulation snapshot.
 
-        A globally unique ``compile_ID`` identifies the snapshot. Every
-        embedded or registered :class:`~mcdc.object_.base.MCDCBase` reached
-        during compilation records that ID.
+        A globally unique ``compile_ID`` identifies the snapshot. Command-line overrides
+        are applied before any derived state is resolved. Every embedded or registered
+        :class:`~mcdc.object_.base.MCDCBase` reached during compilation records that ID.
+        Object-local hooks discover and prepare their dependencies, then model-wide
+        finalization resolves state that requires the complete simulation.
         """
+        from mcdc.config import override_settings
         from mcdc.code_factory.python_objects_compiler import compile_simulation
 
         self.compile_ID = type(self)._next_compile_ID
         type(self)._next_compile_ID += 1
 
+        override_settings(self)
+
         compile_simulation(self)
         self.compiled = True
 
@@ -413,7 +506,7 @@ def visualize_model(
         visualize_model(self, vis_plane, x, y, z, pixels, colors, time, save_as)
 
     def run(self) -> None:
-        """Compile if needed, execute particle transport, and write output.
+        """Compile when needed, execute transport, and write output.
 
         Examples
         --------
@@ -421,11 +514,11 @@ def run(self) -> None:
 
         >>> simulation.run()
         """
-        from mcdc.main import run_simulation
-
         if not self.compiled:
             self.compile()
 
+        from mcdc.main import run_simulation
+
         run_simulation(self)
         self.compiled = False
 
diff --git a/test/unit/test_config.py b/test/unit/test_config.py
new file mode 100644
index 000000000..de10e2abb
--- /dev/null
+++ b/test/unit/test_config.py
@@ -0,0 +1,20 @@
+import mcdc
+import mcdc.config as config
+
+from mcdc.config import override_settings
+
+
+def test_compilation_applies_command_line_overrides(monkeypatch):
+    simulation = mcdc.Simulation()
+    monkeypatch.setattr(config, "target", "cpu")
+    monkeypatch.setattr(config.args, "N_particle", 100)
+    monkeypatch.setattr(config.args, "N_batch", None)
+    monkeypatch.setattr(config.args, "output", None)
+    monkeypatch.setattr(
+        config.args, "progress_bar", simulation.settings.use_progress_bar
+    )
+
+    simulation.compile()
+
+    assert simulation.settings.N_particle == 100
+    assert not override_settings(simulation)
diff --git a/test/unit/test_object_compilation.py b/test/unit/test_object_compilation.py
index 3f44408df..b36f6666b 100644
--- a/test/unit/test_object_compilation.py
+++ b/test/unit/test_object_compilation.py
@@ -99,3 +99,41 @@ def compile_nuclide(nuclide, simulation):
     assert material_b.nuclides == simulation.nuclides
     assert material_a.fissionable
     assert material_b.fissionable
+
+
+def test_simulation_compilation_finalizes_model_wide_state():
+    source_a = mcdc.Source(probability=1.0)
+    source_b = mcdc.Source(probability=3.0)
+    simulation = mcdc.Simulation()
+    simulation.set_sources([source_a, source_b])
+    simulation.settings.neutron_eigenvalue_mode = True
+    simulation.settings.N_inactive = 2
+    simulation.settings.N_cycle = 4
+    simulation.settings.k_init = 1.25
+
+    simulation.compile()
+
+    assert np.allclose([source_a.probability, source_b.probability], [0.25, 0.75])
+    assert simulation.settings.neutron_multigroup_mode
+    assert simulation.k_eff == 1.25
+    assert not simulation.cycle_active
+    assert simulation.k_cycle.shape == (4,)
+    assert simulation.gyration_radius.shape == (4,)
+
+
+def test_simulation_compilation_sets_particle_bank_capacities():
+    simulation = mcdc.Simulation()
+    simulation.settings.N_particle = 100
+    simulation.settings.N_census = 2
+    simulation.settings.active_bank_buffer = 11
+    simulation.settings.census_bank_buffer_ratio = 2.0
+    simulation.settings.source_bank_buffer_ratio = 3.0
+    simulation.settings.future_bank_buffer_ratio = 4.0
+
+    simulation.compile()
+
+    N_work = int(np.ceil(100 / simulation.mpi_size))
+    assert simulation.bank_active.size[0] == 11
+    assert simulation.bank_census.size[0] == 2 * N_work
+    assert simulation.bank_source.size[0] == 3 * N_work
+    assert simulation.bank_future.size[0] == 4 * N_work

From 262504cba0696be7f6c61208d55304e2d05350a3 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 5 Aug 2026 14:22:32 +0700
Subject: [PATCH 097/202] minor update

---
 .../writing_numba_compatible_transport_code.rst        | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index f9d4aa0c2..4ea285340 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -27,7 +27,7 @@ Place model definition and model-finalization work in ``mcdc/object_/`` when it
 - Define the state that must later be available to transport.
 
 Use an object's ``_compile_into_simulation`` hook when the work belongs to that object and use ``Simulation._finalize_compilation`` when it requires the complete discovered model.
-``compile_simulation`` coordinates those phases and should change only when the compilation framework itself gains a new phase or registered category.
+``compile_simulation`` in ``mcdc/code_factory/`` coordinates those phases and should change only when the compilation framework itself gains a new phase or registered category.
 
 ``mcdc.main.prepare`` and the runtime generators in ``mcdc/code_factory/`` are framework-level machinery that pack the finalized model, allocate execution resources, and configure execution backends.
 Most scientific-method additions should not change them; extend them only when the runtime representation or execution framework cannot express the required behavior.
@@ -161,11 +161,11 @@ Dispatch on integer constants through a small interface function rather than usi
    def get_mesh_x(index, mesh, simulation, data):
        sub_ID = mesh["sub_ID"]
        if mesh["sub_type"] == MESH_STRUCTURED:
-           concrete = simulation["structured_meshes"][sub_ID]
-           return mcdc_get.structured_mesh.x(index, concrete, data)
+           structured_mesh = simulation["structured_meshes"][sub_ID]
+           return mcdc_get.structured_mesh.x(index, structured_mesh, data)
        if mesh["sub_type"] == MESH_UNIFORM:
-           concrete = simulation["uniform_meshes"][sub_ID]
-           return concrete["x0"] + index * concrete["dx"]
+           uniform_mesh = simulation["uniform_meshes"][sub_ID]
+           return uniform_mesh["x0"] + index * uniform_mesh["dx"]
        return 0.0
 
 Use the actual category interface and constants already defined for that family.

From 959b1095c900e158291c925b6f4fb0f2e5de0144 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 5 Aug 2026 15:44:10 +0700
Subject: [PATCH 098/202] use local_array for collision_data

---
 mcdc/transport/simulation.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/mcdc/transport/simulation.py b/mcdc/transport/simulation.py
index b630b681b..7ae7bc4b7 100644
--- a/mcdc/transport/simulation.py
+++ b/mcdc/transport/simulation.py
@@ -1,5 +1,3 @@
-import numpy as np
-
 from numba import njit, objmode, uint64
 
 ####
@@ -292,7 +290,7 @@ def step_particle(particle_container, program, data):
 
     # Collision
     if particle["event"] & EVENT_COLLISION:
-        collision_data_container = np.zeros(1, type_.collision_data)
+        collision_data_container = util.local_array(1, type_.collision_data)
 
         # Execute the physics
         physics.collision(particle_container, collision_data_container, program, data)

From 7bd374e59300e7a8e136fd67688ac8564872e00c Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 5 Aug 2026 15:51:35 +0700
Subject: [PATCH 099/202] finalize extending

---
 ...riting_numba_compatible_transport_code.rst | 111 +++++++++++++++---
 1 file changed, 95 insertions(+), 16 deletions(-)

diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index 4ea285340..f6a44db42 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -174,18 +174,12 @@ When adding a subtype, update every exhaustive dispatch site and test an unsuppo
 Control Allocation and Mutation
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Particle histories repeatedly execute transport functions, so temporary allocation can be expensive and difficult for Numba to optimize.
+Transport functions execute repeatedly for every particle history, so they should normally operate on storage prepared before transport begins.
+Reuse particle banks, tally arrays, and other prepared runtime state instead of rebuilding them inside the particle loop.
+Update structured fields or ``data`` through explicit assignments and generated setters, and do not append model entities or change field shapes during transport.
 
-- Reuse particle containers, banks, tally arrays, and scratch state allocated during preparation.
-- Update structured fields or ``data`` through explicit assignments and generated setters.
-- Prefer scalar calculations or bounded loops over constructing intermediate Python collections.
-- Do not append a new model entity or change a field's shape during transport.
-- Preserve the one-element container convention when a mutable record must be shared across function boundaries.
-
-The owner of each mutation should be evident from the function signature.
-Avoid hidden module-level mutable state.
-
-For example, select a minimum with scalar state instead of building a temporary list:
+Prefer scalar state and bounded loops when an intermediate container is unnecessary.
+For example, select a minimum directly instead of building a temporary list of distances:
 
 .. code-block:: python
 
@@ -195,14 +189,78 @@ For example, select a minimum with scalar state instead of building a temporary
        if distance < best_distance:
            best_distance = distance
 
-When a scalar structured record must be mutated across a function boundary, pass its one-element container and recover the record inside the function:
+Some transport operations genuinely require new local storage.
+Fission and scattering create secondary-particle records during transport, while geometry and physics routines may require small bounded work arrays.
+Use ``util.local_array`` with a known shape and stable dtype for these cases.
+In Numba-CPU mode, it provides a NumPy array that Numba can compile and mutate within the transport function.
+
+For example, fission allocates one reusable record for newly generated particles, initializes it for each secondary, and passes its container to a particle bank:
 
 .. code-block:: python
 
-   @njit
-   def increment_counter(counter_container):
-       counter = counter_container[0]
-       counter["value"] += 1
+   particle_container_new = util.local_array(1, type_.particle_data)
+   particle_new = particle_container_new[0]
+
+   for _ in range(N):
+       particle_module.copy_as_child(
+           particle_container_new, particle_container
+       )
+       particle_new["w"] = weight_product
+       particle_bank_module.bank_census_particle(
+           particle_container_new, program
+       )
+
+Use generated structured dtypes from ``mcdc.numba_types`` for local transport records.
+Keep local work arrays small and predictable, and reuse the same allocation within a loop when its contents can be overwritten.
+Make every mutation visible through function arguments rather than hidden module-level mutable state.
+The one-element container preserves the mutable record across function boundaries; the next section explains when functions should receive such a container and when they should receive the record itself.
+
+Use Runtime Arguments Deliberately
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+MC/DC uses ``particle_container``, ``simulation_container``, and ``program`` for different purposes.
+They are calling conventions that preserve mutation and backend portability, not interchangeable names for simulation state.
+
+``particle_container``
+   A one-element structured array that owns one mutable particle record.
+   Pass the container when a function must mutate the particle and recover the record locally for field access.
+   The container may be caller-owned, a one-element view into a particle bank, or local storage created with ``util.local_array``.
+
+   .. code-block:: python
+
+      @njit
+      def reduce_weight(particle_container, factor):
+          particle = particle_container[0]
+          particle["w"] *= factor
+
+``simulation_container``
+   A one-element structured array that owns the mutable top-level ``simulation`` record.
+   It establishes storage and lifetime at an execution entry point; ordinary transport functions normally receive the recovered record rather than the container.
+
+   .. code-block:: python
+
+      def fixed_source_simulation(simulation_container, data):
+          simulation = simulation_container[0]
+          settings = simulation["settings"]
+          for idx_batch in range(settings["N_batch"]):
+              simulation["idx_batch"] = idx_batch
+
+``program``
+   A backend-neutral execution handle used when an operation requires execution services such as particle banking or scheduling.
+   In Python and Numba-CPU modes, ``program`` is the ``simulation`` record and ``util.access_simulation(program)`` returns it unchanged.
+   Treat the handle as opaque even in these modes so the same transport function can later use a GPU implementation.
+
+   .. code-block:: python
+
+      @njit
+      def bank_active_particle(particle_container, program):
+          simulation = util.access_simulation(program)
+          bank = simulation["bank_active"]
+          _bank_particle(particle_container, bank)
+
+Accept ``simulation`` when a function only needs prepared simulation state.
+Accept ``program`` when it needs backend-dependent execution services, and recover ``simulation`` through ``util.access_simulation``.
+Create one-element containers only at ownership or local-storage boundaries; do not wrap every structured record passed between helpers.
 
 Debug Python and Numba-CPU
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -250,6 +308,27 @@ For transport code that will execute on a GPU:
 - Replace CPU-only Numba features with device-compatible operations.
 - Keep target-specific atomics, memory operations, and scheduling behind the existing GPU adaptation layer.
 
+Use the GPU Program Handle
+^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+In Numba-GPU execution, ``program`` is a Harmonize program handle rather than the ``simulation`` record itself.
+The GPU adaptation replaces ``util.access_simulation`` so shared transport functions can recover the device-resident simulation state without knowing how the handle stores it.
+Do not index ``program`` directly or assume its CPU representation.
+The same adaptation replaces ``util.local_array`` with device-local allocation, which is why shared code should use the utility consistently before GPU porting begins.
+
+For example, a GPU entry point recovers state from the handle before calling shared transport behavior:
+
+.. code-block:: python
+
+   def step(program: nb.uintp, particle_input: particle_gpu):
+       simulation = access_simulation(program)
+       data_ptr = access_data_ptr(program)
+       data = harmonize.array_from_ptr(data_ptr, shape, nb.float64)
+
+       particle_container = util.local_array(1, type_.particle)
+       particle_container[0] = particle_input
+       step_particle(particle_container, program, data)
+
 Separate Shared and GPU-Specific Code
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 

From 0e52e433fbb47d6a7f288e96f71d0eee7a10cb71 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 5 Aug 2026 16:51:57 +0700
Subject: [PATCH 100/202] remove config import

---
 mcdc/__init__.py | 6 ------
 1 file changed, 6 deletions(-)

diff --git a/mcdc/__init__.py b/mcdc/__init__.py
index bbcd4f153..06c5fa3c4 100644
--- a/mcdc/__init__.py
+++ b/mcdc/__init__.py
@@ -16,9 +16,3 @@
 from mcdc.object_.source import Source
 from mcdc.object_.surface import Surface
 from mcdc.object_.tally import Tally
-
-# ======================================================================================
-# Misc.
-# ======================================================================================
-
-import mcdc.config

From edd886244008db03815f55f476213d6219bddc78 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 5 Aug 2026 16:52:10 +0700
Subject: [PATCH 101/202] include output, config, and constant

---
 .../developer_guide/architecture/index.rst    | 61 ++++++++++++++++++-
 .../architecture/runtime_data_layout.rst      | 26 ++++++++
 .../architecture/simulation_compilation.rst   | 15 +++++
 ...riting_numba_compatible_transport_code.rst | 15 +++--
 4 files changed, 112 insertions(+), 5 deletions(-)

diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index e584f3d1c..4a3b7422e 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -12,7 +12,7 @@ Architecture documentation explains how MC/DC translates flexible Python model d
    :alt: MC/DC's architecture flow from model definition through simulation compilation and runtime preparation to shared transport, which runs with Python, Numba-CPU, or Numba-GPU execution modes.
 
 The architecture flow follows a Monte Carlo transport model from definition through one common preparation path, then branches into the Python, Numba-CPU, or Numba-GPU execution modes.
-The flow has three major processing stages:
+The figure above emphasizes three major model-to-execution stages:
 
 #. **Simulation compilation** discovers the Python objects owned by a :class:`mcdc.Simulation`, deduplicates them, and assigns simulation-local identifiers.
    :doc:`simulation_compilation` explains model ownership, discovery, and finalization.
@@ -21,6 +21,9 @@ The flow has three major processing stages:
 #. **Transport execution** runs the common, adaptable transport implementation in the selected execution mode.
    :doc:`transport_execution` explains how Python, Numba-CPU, and Numba-GPU execute it, including GPU code generation, memory placement, and Harmonize scheduling.
 
+After transport, ``main.run_simulation`` passes the completed runtime state to ``mcdc.output`` for result aggregation and HDF5 serialization.
+This final results-and-output stage completes the calculation lifecycle but remains outside the shared transport implementation shown in the figure.
+
 Visit :doc:`python_first_numba_accelerated_design` for the rationale, boundaries, and tradeoffs that shape MC/DC's architecture.
 It explains why method development begins in unrestricted Python mode and may progress through Numba-CPU to Numba-GPU.
 
@@ -31,6 +34,7 @@ The source tree follows the same separation of responsibilities shown in the arc
 Model-facing components define, collect, and finalize the simulation.
 Code-factory components coordinate object discovery and generate its runtime representation.
 Transport components implement the numerical algorithms shared by all execution modes.
+Output components aggregate and serialize completed results.
 The table maps each component to its corresponding architecture role.
 Paths in the component column are relative to the top-level ``mcdc/`` package.
 
@@ -47,12 +51,24 @@ Paths in the component column are relative to the top-level ``mcdc/`` package.
    * - :class:`mcdc.Simulation` in ``object_/simulation.py``
      - Model definition and control
      - Owns model roots and configuration, resolves model-wide finalization, and controls compilation, visualization, and execution.
+   * - ``config.py``
+     - Calculation configuration
+     - Parses command-line controls, configures process-wide execution behavior, and applies supported simulation-setting overrides before compilation.
+   * - ``constant.py``
+     - Shared static definitions
+     - Defines named numerical codes, event flags, numerical limits, and tolerances used across model, transport, and output components.
    * - ``code_factory/python_objects_compiler.py``
      - Simulation compilation
      - Coordinates recursive discovery, registration, and model-wide finalization.
+   * - ``main.run_simulation``
+     - Calculation orchestration
+     - Coordinates runtime preparation, transport execution, result generation, runtime reporting, and backend finalization.
    * - ``main.prepare``
      - Runtime preparation
      - Coordinates framework-level packing, execution-resource allocation, backend configuration, and external runtime state.
+   * - ``code_factory/literals_generator.py`` and ``literals.py``
+     - Runtime preparation
+     - Derive and expose simulation-specific values that compiled transport requires as literals.
    * - ``code_factory/numba_layers_generator.py``
      - Runtime preparation
      - Derives structured dtypes, packs runtime state, generates accessors, and initiates GPU-specific preparation when requested.
@@ -65,6 +81,9 @@ Paths in the component column are relative to the top-level ``mcdc/`` package.
    * - ``transport/``
      - Shared transport
      - Implements the particle-transport algorithms used by every execution mode.
+   * - ``output.py``
+     - Results and output
+     - Aggregates completed tally results and writes settings, tallies, eigenvalue data, saved particles, and runtime measurements to HDF5.
 
 .. rst-class:: architecture-component-followup
 
@@ -78,6 +97,46 @@ The ``mcdc/transport`` package implements the shared-transport stage.
 :doc:`transport_execution` explains how the execution modes run it.
 :doc:`../extending/writing_numba_compatible_transport_code` provides practical rules for extending its algorithms.
 
+Results and Output
+------------------
+
+After the selected transport driver returns, ``main.run_simulation`` calls ``output.generate_output`` with the prepared ``simulation`` record, flat ``data`` array, and Python :class:`mcdc.Simulation`.
+``output.py`` reads fixed fields directly, uses ``mcdc_get`` for variable-length runtime data, and retains Python-side settings and names where they form part of the output schema.
+
+The module writes the primary HDF5 file, serializes tally and eigenvalue results, optionally saves particles, recombines census-based tally files, and appends runtime measurements.
+It may reshape or aggregate finalized results for storage, but particle tracking and tally scoring remain responsibilities of ``transport/``.
+
+When a new result must persist after a run, define and prepare its runtime storage first, populate it during the appropriate transport or closeout stage, and add only the serialization step to ``output.py``.
+Changes to the user-visible HDF5 structure should also update the corresponding user documentation, regression coverage, and ``CHANGELOG.md`` entry.
+
+Utility Module Scope
+--------------------
+
+``util`` denotes helpers shared within the package that contains the module; it does not identify one codebase-wide utility layer.
+The complete import path therefore defines the helper's architectural scope.
+
+.. list-table::
+   :header-rows: 1
+   :widths: 34 66
+
+   * - Module
+     - Scope
+   * - ``util.py``
+     - Contains framework-neutral helpers shared across top-level MC/DC packages, currently the nested-list ``flatten`` operation.
+   * - ``object_/util.py``
+     - Supports Python model construction and finalization, including distribution conversion, validation, motion processing, and model-side reference data.
+   * - ``transport/util.py``
+     - Provides Numba-compatible helpers shared across transport domains, including binning, interpolation, atomic updates, local arrays, and backend-neutral simulation access.
+   * - ``transport/physics/util.py``
+     - Contains numerical helpers shared specifically by neutron and electron physics implementations.
+   * - ``code_factory/gpu/transport/util.py``
+     - Implements GPU-compatible replacements and compiler lowering for the adaptable operations exposed by ``transport/util.py``.
+
+Place a new helper in the narrowest package that contains all of its consumers.
+Model-construction helpers may use ordinary Python and NumPy behavior, while helpers reachable from ``transport/`` must follow the compiled-execution constraints described in :doc:`../extending/writing_numba_compatible_transport_code`.
+Hardware-specific replacements belong in the corresponding backend adaptation rather than the shared transport utility module.
+Promote a helper to a broader ``util.py`` only when multiple sibling components genuinely share it, and avoid treating any utility module as a collection for otherwise unrelated code.
+
 .. toctree::
    :maxdepth: 1
    :hidden:
diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index 4958e2351..2458e1d56 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -205,6 +205,32 @@ Packing is performed in two passes:
 
 The structured ``simulation`` dtype can then be finalized because collection sizes, particle-bank sizes, and nested record types are known.
 
+.. _simulation_specific_literals:
+
+Static Constants and Simulation-Specific Literals
+-------------------------------------------------
+
+MC/DC distinguishes static implementation constants from values derived for one prepared simulation.
+``mcdc.constant`` defines stable codes, event flags, numerical limits, and tolerances that have the same meaning for every simulation.
+These values can be imported directly by the model, transport, and output layers.
+
+Some compiled operations instead require a simulation-dependent value to be known as a Numba literal.
+During ``mcdc.main.prepare``, ``make_literals`` in ``mcdc.code_factory.literals_generator`` derives those values from the compiled Python model and replaces the placeholder functions in ``mcdc.literals`` with JIT-compatible implementations that return them.
+
+The current example is the work-array size used to evaluate cell-region reverse Polish notation.
+The generator finds the largest required evaluation buffer in the compiled model, and geometry transport obtains that value through:
+
+.. code-block:: python
+
+   value = util.local_array(
+       literals.rpn_evaluation_buffer_size(),
+       np.bool_,
+   )
+
+Use a generated literal only for a single simulation-wide value that compiled code must treat as fixed during the prepared run.
+Store values that vary by object or particle in the structured ``simulation`` state or ``data`` instead.
+Because literals are derived from a particular model snapshot, runtime preparation regenerates them whenever that simulation is prepared again.
+
 The One-element Container
 -------------------------
 
diff --git a/docs/source/developer_guide/architecture/simulation_compilation.rst b/docs/source/developer_guide/architecture/simulation_compilation.rst
index 64110efcd..151512036 100644
--- a/docs/source/developer_guide/architecture/simulation_compilation.rst
+++ b/docs/source/developer_guide/architecture/simulation_compilation.rst
@@ -52,6 +52,21 @@ MC/DC uses several related forms of compilation:
 
 Unless otherwise qualified, this page uses *compilation* to mean model compilation.
 
+Configuration Boundary
+----------------------
+
+``mcdc.config`` connects command-line execution controls to the simulation lifecycle.
+When imported, it parses the command-line arguments known to MC/DC, establishes process-wide choices such as Python or Numba mode, CPU or GPU target, caching behavior, and GPU execution options, then configures Numba and generated-code caches accordingly.
+Unknown arguments are retained rather than rejected so MC/DC can run under notebooks, test runners, and higher-level Python drivers.
+
+Simulation settings remain owned by :class:`mcdc.Simulation` and its embedded ``Settings`` object.
+At the beginning of ``Simulation.compile``, ``config.override_settings`` applies the supported command-line overrides before object discovery and model-wide finalization.
+Consequently, derived state such as particle-bank capacities is calculated from the effective settings that will be used for the run.
+
+This separation distinguishes process-wide execution configuration from simulation-owned model configuration.
+A new physical or numerical setting should normally be added to ``Settings`` or another simulation-owned object.
+Add a ``config.py`` option only when that setting also needs a command-line override or when the choice controls the execution framework itself.
+
 Ownership and Roots
 -------------------
 
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index f6a44db42..6b45ae042 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -150,10 +150,15 @@ Do not resize the returned view or retain it beyond the prepared run.
 For a new variable-length field, declare the field on the Python model class and regenerate its accessors as described in :doc:`extending_the_object_model`.
 Do not hand-maintain offset arithmetic in several transport modules.
 
-Use Explicit Dispatch
-^^^^^^^^^^^^^^^^^^^^^
+Use Named Constants and Explicit Dispatch
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The packed runtime representation expresses categories, events, and other discrete states as primitive numerical values rather than Python types.
+``mcdc.constant`` gives those values shared names and also defines common numerical limits and tolerances.
+These definitions form a static implementation contract and retain the same meaning across simulations.
+Use the named constants instead of repeating their numerical values in model, transport, scoring, or output code.
 
-Dispatch on integer constants through a small interface function rather than using Python ``isinstance`` checks or methods on runtime records:
+Dispatch on those constants through a small interface function rather than using Python ``isinstance`` checks or methods on runtime records:
 
 .. code-block:: python
 
@@ -169,7 +174,9 @@ Dispatch on integer constants through a small interface function rather than usi
        return 0.0
 
 Use the actual category interface and constants already defined for that family.
-When adding a subtype, update every exhaustive dispatch site and test an unsupported value deliberately if the interface defines fallback behavior.
+When introducing a new subtype, event, or score, give its constant a unique value within the corresponding family and update every consumer of that family.
+Test an unsupported value deliberately when the interface defines fallback behavior.
+Do not place a size or setting derived from one simulation in ``constant.py``; simulation-specific values that must be visible to Numba as compile-time values use the generated literals described in :ref:`simulation_specific_literals`.
 
 Control Allocation and Mutation
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

From 3d423e2011a2e0069aaee9b76e0d4120107694b1 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 5 Aug 2026 17:17:05 +0700
Subject: [PATCH 102/202] clean up printers

---
 mcdc/print_.py          | 357 ++++++++++++++++++++--------------------
 test/unit/test_print.py |  58 +++++++
 2 files changed, 235 insertions(+), 180 deletions(-)
 create mode 100644 test/unit/test_print.py

diff --git a/mcdc/print_.py b/mcdc/print_.py
index 7a381d0fd..42c70594d 100644
--- a/mcdc/print_.py
+++ b/mcdc/print_.py
@@ -1,47 +1,89 @@
-import numba as nb
+"""Terminal diagnostics and progress reporting for MC/DC."""
+
 import sys
+
+import numba as nb
+from colorama import Fore, Style
 from mpi4py import MPI
-from colorama import Fore, Back, Style
 
-master = MPI.COMM_WORLD.Get_rank() == 0
+import mcdc.mcdc_get as mcdc_get
 
+_IS_MASTER = MPI.COMM_WORLD.Get_rank() == 0
 
-import numba as nb
-import sys
 
-from colorama import Fore, Style
+# ======================================================================================
+# General formatting and diagnostics
+# ======================================================================================
 
-import mcdc.mcdc_get as mcdc_get
 
+def print_1d_array(array):
+    """Return a compact representation of a one-dimensional array."""
+    size = len(array)
+    if size > 5:
+        return (
+            f"(size={size}): "
+            f"[{array[0]:.5g}, {array[1]:.5g}, ..., "
+            f"{array[-2]:.5g}, {array[-1]:.5g}]"
+        )
 
-def print_1d_array(arr):
-    N = len(arr)
-    if N > 5:
-        return f"(size={len(arr)}): [{arr[0]:.5g}, {arr[1]:.5g}, ..., {arr[-2]:.5g}, {arr[-1]:.5g}]"
-    else:
-        text = f"(size={len(arr)}): ["
-        for i in range(N):
-            text += f"{arr[i]:.5g}, "
-        if N > 0:
-            text = text[:-2]
-        text += "]"
-        return text
-
-
-def print_error(text):
-    print(Fore.RED + f"[ERROR]: {text}\n")
-    print(Style.RESET_ALL)
+    values = ", ".join(f"{value:.5g}" for value in array)
+    return f"(size={size}): [{values}]"
+
+
+def print_msg(message):
+    """Print a framework message on the MPI master rank."""
+    if not _IS_MASTER:
+        return
+    print(message)
     sys.stdout.flush()
-    sys.exit()
 
 
-def print_warning(text):
-    print(Fore.YELLOW + f"[WARNING]: {text}\n")
-    print(Style.RESET_ALL)
+def print_error(message):
+    """Print a fatal error and terminate the current process unsuccessfully."""
+    print(f"{Fore.RED}[ERROR]: {message}{Style.RESET_ALL}")
     sys.stdout.flush()
+    raise SystemExit(1)
+
+
+def print_warning(message):
+    """Print a warning on the MPI master rank."""
+    if not _IS_MASTER:
+        return
+    print(f"{Fore.YELLOW}[WARNING]: {message}{Style.RESET_ALL}")
+    sys.stdout.flush()
+
+
+def print_structure(structure):
+    """Print every field in a NumPy structured record."""
+    for name in structure.dtype.names:
+        print(f"{name} = {structure[name]}")
+
+
+def print_bank(bank, show_content=False):
+    """Print summary information for a particle bank."""
+    size_field = bank["size"]
+    size = int(size_field[0]) if getattr(size_field, "ndim", 0) else int(size_field)
+    particles = bank["particles"]
+
+    print("\n=============")
+    print("Particle bank")
+    print("  tag  :", bank["tag"])
+    print("  size :", size, "of", len(particles))
+    if show_content:
+        for index in range(size):
+            print(" ", particles[index])
+    print()
+
+
+# ======================================================================================
+# Calculation headers
+# ======================================================================================
 
 
 def print_banner():
+    """Print the MC/DC banner on the MPI master rank."""
+    if not _IS_MASTER:
+        return
     print(
         "\n"
         + r"  __  __  ____  __ ____   ____ "
@@ -59,17 +101,19 @@ def print_banner():
 
 
 def print_configuration():
+    """Print the active execution configuration on the MPI master rank."""
+    if not _IS_MASTER:
+        return
     mode = "Python" if nb.config.DISABLE_JIT else "Numba"
     mpi_size = MPI.COMM_WORLD.Get_size()
-
-    text = ""
-    text += f"           Mode | {mode}\n"
-    text += f"  MPI Processes | {mpi_size}\n"
-    print(text)
+    print(f"           Mode | {mode}\n  MPI Processes | {mpi_size}\n")
     sys.stdout.flush()
 
 
 def print_eigenvalue_header(simulation):
+    """Print the eigenvalue-cycle table header."""
+    if not _IS_MASTER:
+        return
     if simulation["settings"]["use_gyration_radius"]:
         print("\n #     k        GyRad.  k (avg)            ")
         print(" ====  =======  ======  ===================")
@@ -79,170 +123,123 @@ def print_eigenvalue_header(simulation):
     sys.stdout.flush()
 
 
-def print_batch_header(i, N):
-    print(f"\nBatch {i}/{N}")
+def print_header_batch(index, size):
+    """Print a one-based batch header."""
+    if not _IS_MASTER:
+        return
+    print(f"\nBatch {index + 1}/{size}")
     sys.stdout.flush()
 
 
-def print_time(tag, t, percent):
-    if t >= 24 * 60 * 60:
-        print("   %s | %.2f days (%.1f%%)" % (tag, t / 24 / 60 / 60), percent)
-    elif t >= 60 * 60:
-        print("   %s | %.2f hours (%.1f%%)" % (tag, t / 60 / 60, percent))
-    elif t >= 60:
-        print("   %s | %.2f minutes (%.1f%%)" % (tag, t / 60, percent))
-    else:
-        print("   %s | %.2f seconds (%.1f%%)" % (tag, t, percent))
-
-
-def print_runtime(simulation):
-    total = simulation["runtime_total"]
-    preparation = simulation["runtime_preparation"]
-    simulation = simulation["runtime_simulation"]
-    output = simulation["runtime_output"]
-    print("\n Runtime report:")
-    print_time("Total      ", total, 100)
-    print_time("Preparation", preparation, preparation / total * 100)
-    print_time("Simulation ", simulation, simulation / total * 100)
-    print_time("Output     ", output, output / total * 100)
-    print("\n")
-    sys.stdout.flush()
-
-
-def print_structure(struct):
-    dtype = struct.dtype
-    for name in dtype.names:
-        print(f"{name} = {struct[name]}")
-
-
-# TODO: below is not evaulated yet during the refactor
-
-
-def print_msg(msg):
-    if master:
-        print(msg)
-        sys.stdout.flush()
-
-
-def print_error(msg):
-    print("ERROR: %s\n" % msg)
-    sys.stdout.flush()
-    sys.exit()
-
-
-def print_warning(msg):
-    if master:
-        print(Fore.RED + "Warning: %s\n" % msg)
-        print(Style.RESET_ALL)
-        sys.stdout.flush()
+# ======================================================================================
+# Calculation progress
+# ======================================================================================
 
 
 def print_progress(percent, simulation):
-    if master:
-        sys.stdout.write("\r")
-        if not simulation["settings"]["neutron_eigenvalue_mode"]:
-            if simulation["settings"]["N_census"] == 1:
-                sys.stdout.write(
-                    " [%-28s] %d%%" % ("=" * int(percent * 28), percent * 100.0)
-                )
-            else:
-                idx = simulation["idx_census"] + 1
-                N = simulation["settings"]["N_census"]
-                sys.stdout.write(
-                    " Census %i/%i: [%-28s] %d%%"
-                    % (idx, N, "=" * int(percent * 28), percent * 100.0)
-                )
+    """Update the fixed-source or eigenvalue progress bar."""
+    if not _IS_MASTER:
+        return
+
+    sys.stdout.write("\r")
+    settings = simulation["settings"]
+    if not settings["neutron_eigenvalue_mode"]:
+        if settings["N_census"] == 1:
+            sys.stdout.write(
+                " [%-28s] %d%%" % ("=" * int(percent * 28), percent * 100.0)
+            )
         else:
-            if simulation["settings"]["use_gyration_radius"]:
-                sys.stdout.write(
-                    " [%-40s] %d%%" % ("=" * int(percent * 40), percent * 100.0)
-                )
-            else:
-                sys.stdout.write(
-                    " [%-32s] %d%%" % ("=" * int(percent * 32), percent * 100.0)
-                )
-        sys.stdout.flush()
+            index = simulation["idx_census"] + 1
+            size = settings["N_census"]
+            sys.stdout.write(
+                " Census %i/%i: [%-28s] %d%%"
+                % (index, size, "=" * int(percent * 28), percent * 100.0)
+            )
+    elif settings["use_gyration_radius"]:
+        sys.stdout.write(" [%-40s] %d%%" % ("=" * int(percent * 40), percent * 100.0))
+    else:
+        sys.stdout.write(" [%-32s] %d%%" % ("=" * int(percent * 32), percent * 100.0))
+    sys.stdout.flush()
 
 
-def print_header_eigenvalue(simulation):
-    if master:
-        if simulation["settings"]["use_gyration_radius"]:
-            print("\n #     k        GyRad.  k (avg)            ")
-            print(" ====  =======  ======  ===================")
+def print_progress_eigenvalue(simulation, data):
+    """Print one eigenvalue-cycle result."""
+    if not _IS_MASTER:
+        return
+
+    index = simulation["idx_cycle"]
+    k_effective = simulation["k_eff"]
+    k_average = simulation["k_avg_running"]
+    k_standard_deviation = simulation["k_sdv_running"]
+    settings = simulation["settings"]
+
+    if settings["use_progress_bar"]:
+        sys.stdout.write("\r\033[K")
+
+    if settings["use_gyration_radius"]:
+        gyration_radius = mcdc_get.simulation.gyration_radius(index, simulation, data)
+        if simulation["cycle_active"]:
+            print(
+                " %-4i  %.5f  %6.2f  %.5f +/- %.5f"
+                % (
+                    index + 1,
+                    k_effective,
+                    gyration_radius,
+                    k_average,
+                    k_standard_deviation,
+                )
+            )
         else:
-            print("\n #     k        k (avg)            ")
-            print(" ====  =======  ===================")
+            print(" %-4i  %.5f  %6.2f" % (index + 1, k_effective, gyration_radius))
+    elif simulation["cycle_active"]:
+        print(
+            " %-4i  %.5f  %.5f +/- %.5f"
+            % (index + 1, k_effective, k_average, k_standard_deviation)
+        )
+    else:
+        print(" %-4i  %.5f" % (index + 1, k_effective))
+    sys.stdout.flush()
 
 
-def print_header_batch(i, N):
-    if master:
-        print(f"\nBatch {i+1}/{N}")
-        sys.stdout.flush()
+# ======================================================================================
+# Runtime report
+# ======================================================================================
 
 
-def print_progress_eigenvalue(simulation, data):
-    if master:
-        idx_cycle = simulation["idx_cycle"]
-        k_eff = simulation["k_eff"]
-        k_avg = simulation["k_avg_running"]
-        k_sdv = simulation["k_sdv_running"]
-        gr = mcdc_get.simulation.gyration_radius(idx_cycle, simulation, data)
-        if simulation["settings"]["use_progress_bar"]:
-            sys.stdout.write("\r")
-            sys.stdout.write("\033[K")
-        if simulation["settings"]["use_gyration_radius"]:
-            if not simulation["cycle_active"]:
-                print(" %-4i  %.5f  %6.2f" % (idx_cycle + 1, k_eff, gr))
-            else:
-                print(
-                    " %-4i  %.5f  %6.2f  %.5f +/- %.5f"
-                    % (idx_cycle + 1, k_eff, gr, k_avg, k_sdv)
-                )
-        else:
-            if not simulation["cycle_active"]:
-                print(" %-4i  %.5f" % (idx_cycle + 1, k_eff))
-            else:
-                print(
-                    " %-4i  %.5f  %.5f +/- %.5f" % (idx_cycle + 1, k_eff, k_avg, k_sdv)
-                )
+def print_time(label, duration, percent):
+    """Print one duration using an appropriate time unit."""
+    if duration >= 24 * 60 * 60:
+        value = duration / (24 * 60 * 60)
+        unit = "days"
+    elif duration >= 60 * 60:
+        value = duration / (60 * 60)
+        unit = "hours"
+    elif duration >= 60:
+        value = duration / 60
+        unit = "minutes"
+    else:
+        value = duration
+        unit = "seconds"
+    print(f"   {label} | {value:.2f} {unit} ({percent:.1f}%)")
 
 
 def print_runtime(simulation):
-    t_total = simulation["runtime_total"]
-    t_preparation = simulation["runtime_preparation"]
-    t_simulation = simulation["runtime_simulation"]
-    t_output = simulation["runtime_output"]
-    if master:
-        print("\n Runtime report:")
-        print_time("Total      ", t_total, 100)
-        print_time("Preparation", t_preparation, t_preparation / t_total * 100)
-        print_time("Simulation ", t_simulation, t_simulation / t_total * 100)
-        print_time("Output     ", t_output, t_output / t_total * 100)
-        print("\n")
-        sys.stdout.flush()
-
-
-def print_time(tag, t, percent):
-    if t >= 24 * 60 * 60:
-        print("   %s | %.2f days (%.1f%%)" % (tag, t / 24 / 60 / 60), percent)
-    elif t >= 60 * 60:
-        print("   %s | %.2f hours (%.1f%%)" % (tag, t / 60 / 60, percent))
-    elif t >= 60:
-        print("   %s | %.2f minutes (%.1f%%)" % (tag, t / 60, percent))
-    else:
-        print("   %s | %.2f seconds (%.1f%%)" % (tag, t, percent))
+    """Print preparation, transport, and output runtimes."""
+    if not _IS_MASTER:
+        return
 
+    total = simulation["runtime_total"]
+    preparation = simulation["runtime_preparation"]
+    transport = simulation["runtime_simulation"]
+    output = simulation["runtime_output"]
 
-def print_bank(bank, show_content=False):
-    tag = bank["tag"]
-    size = bank["size"]
-    particles = bank["particles"]
+    def percentage(duration):
+        return duration / total * 100.0 if total > 0.0 else 0.0
 
-    print("\n=============")
-    print("Particle bank")
-    print("  tag  :", tag)
-    print("  size :", size, "of", len(bank["particles"]))
-    if show_content and size > 0:
-        for i in range(size):
-            print(" ", particles[i])
-    print("\n")
+    print("\n Runtime report:")
+    print_time("Total      ", total, 100.0)
+    print_time("Preparation", preparation, percentage(preparation))
+    print_time("Simulation ", transport, percentage(transport))
+    print_time("Output     ", output, percentage(output))
+    print()
+    sys.stdout.flush()
diff --git a/test/unit/test_print.py b/test/unit/test_print.py
new file mode 100644
index 000000000..5fdad9cb5
--- /dev/null
+++ b/test/unit/test_print.py
@@ -0,0 +1,58 @@
+import numpy as np
+import pytest
+
+import mcdc.print_ as print_module
+
+
+def test_print_1d_array():
+    assert print_module.print_1d_array(np.array([])) == "(size=0): []"
+    assert print_module.print_1d_array(np.array([1.0, 2.0])) == "(size=2): [1, 2]"
+    assert print_module.print_1d_array(np.arange(6.0)) == "(size=6): [0, 1, ..., 4, 5]"
+
+
+@pytest.mark.parametrize(
+    ("duration", "expected"),
+    [
+        (2.0, "2.00 seconds"),
+        (120.0, "2.00 minutes"),
+        (7_200.0, "2.00 hours"),
+        (172_800.0, "2.00 days"),
+    ],
+)
+def test_print_time(duration, expected, capsys):
+    print_module.print_time("Stage", duration, 25.0)
+
+    assert capsys.readouterr().out == f"   Stage | {expected} (25.0%)\n"
+
+
+def test_print_runtime_handles_zero_total(monkeypatch, capsys):
+    monkeypatch.setattr(print_module, "_IS_MASTER", True)
+    simulation = {
+        "runtime_total": 0.0,
+        "runtime_preparation": 0.0,
+        "runtime_simulation": 0.0,
+        "runtime_output": 0.0,
+    }
+
+    print_module.print_runtime(simulation)
+
+    output = capsys.readouterr().out
+    assert "Runtime report:" in output
+    assert "Preparation | 0.00 seconds (0.0%)" in output
+
+
+def test_master_only_message(monkeypatch, capsys):
+    monkeypatch.setattr(print_module, "_IS_MASTER", False)
+
+    print_module.print_msg("hidden")
+    print_module.print_warning("hidden")
+
+    assert capsys.readouterr().out == ""
+
+
+def test_print_error_exits_unsuccessfully(capsys):
+    with pytest.raises(SystemExit) as error:
+        print_module.print_error("invalid model")
+
+    assert error.value.code == 1
+    assert "[ERROR]: invalid model" in capsys.readouterr().out

From 278e278027cfa1a2be725535107d208ea03ab6c6 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 5 Aug 2026 17:44:18 +0700
Subject: [PATCH 103/202] clean up printers

---
 .../developer_guide/architecture/index.rst    |  3 ++
 ...riting_numba_compatible_transport_code.rst | 36 +++++++++++++++++++
 2 files changed, 39 insertions(+)

diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index 4a3b7422e..7a688acec 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -63,6 +63,9 @@ Paths in the component column are relative to the top-level ``mcdc/`` package.
    * - ``main.run_simulation``
      - Calculation orchestration
      - Coordinates runtime preparation, transport execution, result generation, runtime reporting, and backend finalization.
+   * - ``print_.py``
+     - Diagnostics and reporting
+     - Centralizes fatal errors, master-rank messages, calculation progress, and runtime summaries used across the model, transport, and output stages.
    * - ``main.prepare``
      - Runtime preparation
      - Coordinates framework-level packing, execution-resource allocation, backend configuration, and external runtime state.
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index 6b45ae042..23ec078db 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -269,6 +269,42 @@ Accept ``simulation`` when a function only needs prepared simulation state.
 Accept ``program`` when it needs backend-dependent execution services, and recover ``simulation`` through ``util.access_simulation``.
 Create one-element containers only at ownership or local-storage boundaries; do not wrap every structured record passed between helpers.
 
+Cross the Python Boundary with ``objmode``
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Numba's ``objmode`` temporarily returns from compiled Numba-CPU execution to the Python interpreter for one bounded block.
+MC/DC uses this boundary when compiled orchestration must invoke a Python service that Numba cannot compile and moving the complete operation outside the compiled driver would obscure its ownership or timing.
+
+Current uses include:
+
+- MPI collectives and particle-bank communication.
+- Wall-clock timing through ``MPI.Wtime``.
+- Progress and fatal diagnostics provided by ``mcdc.print_``.
+- Census-based HDF5 output performed between transport stages.
+
+Keep the ``objmode`` block as small and infrequent as possible because entering the interpreter interrupts compiled execution and adds conversion and dispatch overhead.
+Perform the surrounding numerical work in compiled code, and do not use ``objmode`` merely to avoid expressing a maintained numerical algorithm in Numba-compatible form.
+
+If a value produced in Python is used after the block, declare its Numba type on the context manager:
+
+.. code-block:: python
+
+   time_start = 0.0
+   with objmode(time_start="float64"):
+       time_start = MPI.Wtime()
+
+No output declaration is needed when the block only performs a side effect or mutates an array that was allocated before entering it:
+
+.. code-block:: python
+
+   local_total = np.array([particle_weight], dtype=np.float64)
+   global_total = np.zeros(1, dtype=np.float64)
+   with objmode():
+       MPI.COMM_WORLD.Allreduce(local_total, global_total, MPI.SUM)
+
+``objmode`` is a deliberate Numba-CPU escape hatch, not part of the GPU execution model.
+Code intended for Numba-GPU must keep the Python service outside device execution or provide a backend-specific implementation.
+
 Debug Python and Numba-CPU
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
 

From 315ac161f11fc89a47f3973732caeee50ee87e44 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Wed, 5 Aug 2026 18:11:49 +0700
Subject: [PATCH 104/202] consider method vs framework development area

---
 .../developer_guide/architecture/index.rst    |  6 ++--
 .../developer_guide/documentation/index.rst   |  2 +-
 .../documentation/philosophy.rst              | 30 +++++++++----------
 .../developer_guide/extending/index.rst       | 10 ++++++-
 docs/source/developer_guide/index.rst         | 16 ++++++++++
 .../user_guide/simulation_lifecycle.rst       |  2 +-
 6 files changed, 46 insertions(+), 20 deletions(-)

diff --git a/docs/source/developer_guide/architecture/index.rst b/docs/source/developer_guide/architecture/index.rst
index 7a688acec..f2c2cd9fa 100644
--- a/docs/source/developer_guide/architecture/index.rst
+++ b/docs/source/developer_guide/architecture/index.rst
@@ -35,6 +35,8 @@ Model-facing components define, collect, and finalize the simulation.
 Code-factory components coordinate object discovery and generate its runtime representation.
 Transport components implement the numerical algorithms shared by all execution modes.
 Output components aggregate and serialize completed results.
+For :ref:`methods development <development_areas>`, ``object_/`` and ``transport/`` form the primary extension surface.
+The ``code_factory/`` package implements the framework-level compilation and generation bridge between them.
 The table maps each component to its corresponding architecture role.
 Paths in the component column are relative to the top-level ``mcdc/`` package.
 
@@ -115,7 +117,7 @@ Changes to the user-visible HDF5 structure should also update the corresponding
 Utility Module Scope
 --------------------
 
-``util`` denotes helpers shared within the package that contains the module; it does not identify one codebase-wide utility layer.
+``util`` denotes helpers shared within the package that contains the module.
 The complete import path therefore defines the helper's architectural scope.
 
 .. list-table::
@@ -137,7 +139,7 @@ The complete import path therefore defines the helper's architectural scope.
 
 Place a new helper in the narrowest package that contains all of its consumers.
 Model-construction helpers may use ordinary Python and NumPy behavior, while helpers reachable from ``transport/`` must follow the compiled-execution constraints described in :doc:`../extending/writing_numba_compatible_transport_code`.
-Hardware-specific replacements belong in the corresponding backend adaptation rather than the shared transport utility module.
+Hardware-specific replacements belong in the corresponding backend adaptation.
 Promote a helper to a broader ``util.py`` only when multiple sibling components genuinely share it, and avoid treating any utility module as a collection for otherwise unrelated code.
 
 .. toctree::
diff --git a/docs/source/developer_guide/documentation/index.rst b/docs/source/developer_guide/documentation/index.rst
index cfb758bf9..9da4a533e 100644
--- a/docs/source/developer_guide/documentation/index.rst
+++ b/docs/source/developer_guide/documentation/index.rst
@@ -4,7 +4,7 @@ Documentation
 =============
 
 High-quality documentation is an essential part of MC/DC.
-Clear documentation helps users perform simulations, enables method developers to understand and extend computational methods, and assists framework developers in maintaining and evolving the software.
+Clear documentation supports simulation work, the development of computational methods, and the maintenance and evolution of the software framework.
 
 This section explains both the philosophy behind MC/DC's documentation and the tools used to build it.
 
diff --git a/docs/source/developer_guide/documentation/philosophy.rst b/docs/source/developer_guide/documentation/philosophy.rst
index c3a8834b8..38648a159 100644
--- a/docs/source/developer_guide/documentation/philosophy.rst
+++ b/docs/source/developer_guide/documentation/philosophy.rst
@@ -17,28 +17,28 @@ This philosophy applies to all forms of MC/DC documentation, including Getting S
 The Layered Documentation Philosophy
 ------------------------------------
 
-MC/DC documentation is written for three complementary audiences.
-Rather than maintaining separate documentation for each audience, individual documents should progressively layer information from high-level usage to mathematical concepts and implementation details.
+MC/DC documentation supports three complementary kinds of work.
+Individual documents should progressively layer information from high-level usage to mathematical concepts and implementation details.
 Readers can naturally stop at the level of detail appropriate for their needs.
 
-Users
-^^^^^
+Using MC/DC
+^^^^^^^^^^^
 
-Users build geometry, define materials and sources, configure simulations, execute transport calculations, and analyze results.
+Using MC/DC involves building geometry, defining materials and sources, configuring simulations, executing transport calculations, and analyzing results.
 
-Documentation for users should emphasize:
+Documentation supporting this work should emphasize:
 
 - What MC/DC provides.
 - How to use the public API.
 - Tutorials, examples, and recommended workflows.
 - Best practices for building transport models.
 
-Method Developers
-^^^^^^^^^^^^^^^^^
+Developing Methods
+^^^^^^^^^^^^^^^^^^
 
-Method Developers use MC/DC as a platform for developing and evaluating new transport methods and computational algorithms.
+Developing methods in MC/DC includes creating and evaluating new transport methods and computational algorithms.
 
-Documentation for Method Developers should explain:
+Documentation supporting this work should explain:
 
 - Mathematical formulations.
 - Numerical algorithms.
@@ -47,12 +47,12 @@ Documentation for Method Developers should explain:
 - Extensibility points.
 - Relationships between the public API and transport algorithms.
 
-Framework Developers
-^^^^^^^^^^^^^^^^^^^^
+Developing the Framework
+^^^^^^^^^^^^^^^^^^^^^^^^
 
-Framework Developers extend and maintain the MC/DC software framework itself.
+Developing the framework includes extending and maintaining MC/DC's software infrastructure.
 
-Documentation for Framework Developers should describe:
+Documentation supporting this work should describe:
 
 - Software architecture.
 - Internal APIs.
@@ -89,7 +89,7 @@ In general:
 
 - The opening description should explain the public purpose of the object, function, or module.
 - Parameters, return values, attributes, and examples should focus on the public interface.
-- Mathematical representations, algorithms, and design rationale should be documented in the ``Notes`` section when they help Method Developers.
+- Mathematical representations, algorithms, and design rationale should be documented in the ``Notes`` section when they support methods development.
 - Framework-specific implementation details should be documented separately as implementation notes when appropriate.
 
 Not every API requires all of these sections.
diff --git a/docs/source/developer_guide/extending/index.rst b/docs/source/developer_guide/extending/index.rst
index 413da8fc4..4240efb0a 100644
--- a/docs/source/developer_guide/extending/index.rst
+++ b/docs/source/developer_guide/extending/index.rst
@@ -4,9 +4,17 @@
 Extending MC/DC
 ===============
 
-Use this section to extend the Python model, compilation, generated runtime layers, transport implementation, public API, and tests.
+Use this section to extend the Python model, transport implementation, public API, and tests.
 Read :doc:`../architecture/index` for the design that these recipes extend.
 
+.. tip::
+
+   :ref:`Methods development <development_areas>` usually takes place in ``mcdc/object_`` and ``mcdc/transport``.
+   The object modules define model-facing state and its runtime-visible declarations, while the transport modules implement the corresponding numerical behavior.
+   ``mcdc/code_factory`` provides compilation, layer-generation, accessor-generation, and backend-adaptation services behind this interface.
+   This separation allows methods development to use those services without managing the framework machinery directly.
+   Modify ``code_factory`` when changing compilation, layer generation, accessor generation, or backend adaptation.
+
 Start with :doc:`extending_the_object_model` when adding a field to an existing model class, introducing simulation-owned configuration, creating a registered model-object category, or implementing a new polymorphic subtype.
 Continue with :doc:`writing_numba_compatible_transport_code` when the extension adds or changes code executed during particle transport.
 
diff --git a/docs/source/developer_guide/index.rst b/docs/source/developer_guide/index.rst
index 165d43c99..24fb96233 100644
--- a/docs/source/developer_guide/index.rst
+++ b/docs/source/developer_guide/index.rst
@@ -6,6 +6,22 @@ Developer Guide
 
 The Developer Guide explains how MC/DC works internally and how to extend or maintain its implementation.
 
+.. _development_areas:
+
+Development Areas
+-----------------
+
+MC/DC development spans two complementary areas.
+
+**Methods development** covers the implementation and evaluation of transport methods, numerical algorithms, and their model-facing data.
+This work primarily uses ``mcdc/object_`` and ``mcdc/transport``.
+
+**Framework development** covers the machinery that compiles models, generates runtime layers and accessors, configures execution, and supports CPU and GPU backends.
+This work primarily uses ``mcdc/code_factory``, ``mcdc/main.py``, and related execution infrastructure.
+
+Where to Go Next
+----------------
+
 - Read :doc:`architecture/index` to understand MC/DC's Python-first design and follow a transport model through simulation compilation, runtime preparation, shared transport algorithm, and the available execution modes.
 - Read :doc:`extending/index` when adding model fields, registered objects, polymorphic subtypes, or Numba-compatible transport behavior.
 - Read :doc:`documentation/index` when writing or reviewing project documentation.
diff --git a/docs/source/user_guide/simulation_lifecycle.rst b/docs/source/user_guide/simulation_lifecycle.rst
index 29e5198ac..8bcd598ac 100644
--- a/docs/source/user_guide/simulation_lifecycle.rst
+++ b/docs/source/user_guide/simulation_lifecycle.rst
@@ -187,6 +187,6 @@ The example suite demonstrates the lifecycle in complete inputs:
 - :ref:`example_c5g7_transient` — a larger reactor transient.
 
 For exact public signatures, use the :doc:`../reference/python_api/index`.
-Framework developers can continue with
+For framework implementation details, continue with
 :doc:`../developer_guide/architecture/simulation_compilation` and
 :doc:`../developer_guide/architecture/runtime_data_layout`.

From 6b367606f35921f0fef56ad8e56d6786f1704ce6 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 11:46:06 +0700
Subject: [PATCH 105/202] more expressive annotation

---
 mcdc/code_factory/numba_layers_generator.py | 19 ++++++++++---------
 1 file changed, 10 insertions(+), 9 deletions(-)

diff --git a/mcdc/code_factory/numba_layers_generator.py b/mcdc/code_factory/numba_layers_generator.py
index d4fcf465d..de60f263f 100644
--- a/mcdc/code_factory/numba_layers_generator.py
+++ b/mcdc/code_factory/numba_layers_generator.py
@@ -26,6 +26,7 @@
 )
 from mcdc.object_.particle import Particle, ParticleBank, ParticleData
 from mcdc.object_.tally import Tally
+from mcdc.object_.util import parse_dimension_expression
 from mcdc.print_ import print_error, print_structure
 from mcdc.util import flatten
 
@@ -1123,7 +1124,13 @@ def accessor_return(expression, cast_to_int):
 
 def accessor_dimension(variable_name, dimension, object_name):
     if isinstance(dimension, str):
-        return f'    {variable_name} = {object_name}["{dimension}"]\n'
+        attribute, offset = parse_dimension_expression(dimension)
+        expression = f'{object_name}["{attribute}"]'
+        if offset > 0:
+            expression += f" + {offset}"
+        elif offset < 0:
+            expression += f" - {-offset}"
+        return f"    {variable_name} = {expression}\n"
     return f"    {variable_name} = {dimension}\n"
 
 
@@ -1148,10 +1155,7 @@ def _accessor_1d_all(object_name, attribute_name, size, setter=False):
     else:
         text += f"def {attribute_name}_all({object_name}, data):\n"
     text += f'    start = {object_name}["{attribute_name}_offset"]\n'
-    if type(size) == str:
-        text += f'    size = {object_name}["{size}"]\n'
-    else:
-        text += f"    size = {size}\n"
+    text += accessor_dimension("size", size, object_name)
     text += f"    end = start + size\n"
     if setter:
         text += f"    data[start:end] = value\n\n\n"
@@ -1169,10 +1173,7 @@ def _accessor_1d_last(
     else:
         text += f"def {attribute_name}_last({object_name}, data):\n"
     text += f'    start = {object_name}["{attribute_name}_offset"]\n'
-    if type(size) == str:
-        text += f'    size = {object_name}["{size}"]\n'
-    else:
-        text += f"    size = {size}\n"
+    text += accessor_dimension("size", size, object_name)
     text += f"    end = start + size\n"
     if setter:
         text += f"    data[end - 1] = value\n\n\n"

From 14195a68a026740d78df99e6aa97842b6a8e0b98 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 12:10:52 +0700
Subject: [PATCH 106/202] move type checker from base to util

---
 mcdc/object_/base.py | 269 +-------------------------------
 mcdc/object_/util.py | 359 ++++++++++++++++++++++++++++++++++++++++++-
 2 files changed, 358 insertions(+), 270 deletions(-)

diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index a5fd7479f..00b7748f2 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -1,3 +1,4 @@
+from mcdc.object_.util import check_type
 from mcdc.print_ import print_error
 
 
@@ -159,271 +160,3 @@ def __repr__(self) -> str:
             text += f"  (compile_ID={self.compile_ID}, ID={self.ID}, sub_ID={self.sub_ID})\n"
 
         return text
-
-
-# ======================================================================================
-# Type checker
-# ======================================================================================
-
-
-import re
-import numpy as np
-from typing import get_origin, get_args, Union, Annotated
-
-
-def check_type(value, hint, cls, obj=None) -> bool:
-    """
-    Best-effort runtime checker tolerant of *string* annotations (no eval).
-    Supports:
-      - typing objects: list[T], set[T], dict[K,V], tuple[...,], Union/|, Annotated
-      - string 'Annotated[NDArray[float], (shape,)]' (dtype+shape)
-      - plain string class names (accept subclasses via MRO)
-      - string unions 'A | B'
-    """
-    # -------- STRING annotations path (no resolution) --------
-    if isinstance(hint, str):
-        h = hint.strip()
-
-        # Handle plain "NDArray[...]" (dtype-only) without Annotated
-        if _is_ndarray_base_str(h):
-            if not isinstance(value, np.ndarray):
-                return False
-            dtype_key = _extract_ndarray_dtype_key_from_str(h)
-            return _dtype_matches(value, dtype_key)
-
-        # String Annotated[...]
-        parsed = _parse_annotated_str(h)
-        if parsed:
-            base_str, meta = parsed
-
-            # NDArray with shape metadata
-            if _is_ndarray_base_str(base_str) and meta:
-                shape = _shape_tuple_from_str(meta[0])
-                dtype_key = _extract_ndarray_dtype_key_from_str(base_str)
-                if not isinstance(value, np.ndarray):
-                    return False
-                if shape is not None and not _shape_matches(value, shape):
-                    return False
-                return _dtype_matches(value, dtype_key)
-
-            # Otherwise treat base as class-like name → accept subclasses via MRO
-            return _mro_name_match(value, base_str)
-
-        # String union: "A | B"
-        if "|" in h:
-            parts = _split_top_level(h, sep="|")
-            return any(check_type(value, p.strip(), cls) for p in parts)
-
-        # Simple string container: "list[str]" (lightweight support)
-        if h.startswith("list[") and h.endswith("]"):
-            inner = _name_from_str(h[5:-1])
-            if not isinstance(value, list):
-                return False
-            if inner == "str":
-                return all(isinstance(x, str) for x in value)
-            if inner in ("float", "float32", "float64"):
-                return all(isinstance(x, (float, int)) for x in value)
-            return True  # permissive other inners
-
-        # Plain forward-ref name → subclass-friendly check
-        return _mro_name_match(value, h)
-
-    # -------- Structured typing objects path --------
-    origin = get_origin(hint)
-
-    # Annotated[T, meta...] (real object)
-    if origin is Annotated:
-        base, *meta = get_args(hint)
-        if isinstance(value, np.ndarray) and meta and isinstance(meta[0], tuple):
-            expected_shape = meta[0]
-            base_args = get_args(base)  # e.g., NDArray[dtype]
-            dtype_key = None
-            if base_args:
-                dtype_arg = base_args[0]
-                if dtype_arg is float:
-                    dtype_key = "float"
-                elif hasattr(dtype_arg, "name"):  # np.float64
-                    dtype_key = dtype_arg.name
-            expected_shape_list = list(expected_shape)
-            for i, item in enumerate(expected_shape):
-                if type(item) == str:
-                    expected_shape_list[i] = getattr(obj, item)
-            expected_shape = tuple(expected_shape_list)
-            return _shape_matches(value, expected_shape) and _dtype_matches(
-                value, dtype_key
-            )
-        return check_type(value, base, cls)
-
-    # NDArray[...] without shape meta
-    if origin is np.ndarray:
-        return isinstance(value, np.ndarray)
-
-    # Builtins / classes
-    if origin is None:
-        try:
-            return isinstance(value, hint)
-        except TypeError:
-            return True
-
-    # list[T]
-    if origin is list:
-        (t,) = get_args(hint)
-        return isinstance(value, list) and all(check_type(x, t, cls) for x in value)
-
-    # set[T]
-    if origin is set:
-        (t,) = get_args(hint)
-        return isinstance(value, set) and all(check_type(x, t, cls) for x in value)
-
-    # dict[K, V]
-    if origin is dict:
-        kt, vt = get_args(hint)
-        return isinstance(value, dict) and all(
-            check_type(k, kt, cls) and check_type(v, vt, cls) for k, v in value.items()
-        )
-
-    # tuple[T1, T2] or tuple[T, ...]
-    if origin is tuple:
-        args = get_args(hint)
-        if len(args) == 2 and args[1] is Ellipsis:
-            return isinstance(value, tuple) and all(
-                check_type(x, args[0], cls) for x in value
-            )
-        return (
-            isinstance(value, tuple)
-            and len(value) == len(args)
-            and all(check_type(x, t, cls) for x, t in zip(value, args))
-        )
-
-    # Union[...] (incl Optional[T])
-    if origin is Union:
-        return any(check_type(value, t, cls) for t in get_args(hint))
-
-    # Fallback: ABCs (Iterable, Sequence, etc.)
-    try:
-        return isinstance(value, origin)
-    except TypeError:
-        return True
-
-
-def _name_from_str(s: str) -> str:
-    s = _strip_prefixes(s)
-    # strip generic args like "NDArray[float64]" → "NDArray"
-    s = s.split("[", 1)[0]
-    return s.split(".")[-1].strip()
-
-
-def _mro_name_match(value, want: str) -> bool:
-    """Subclass-friendly match without resolving: compare wanted name to any base in MRO."""
-    want_name = _name_from_str(want)
-    return any(base.__name__ == want_name for base in value.__class__.mro())
-
-
-# ---------- helpers for STRING annotations ----------
-_ANN_RE = re.compile(r"^\s*(?:typing\.)?Annotated\[(.*)\]\s*$")
-
-
-def _split_top_level(s: str, sep: str = ",", brackets: str = "[]()") -> list[str]:
-    out, buf, depth = [], [], 0
-    opens = set(brackets[::2])
-    closes = set(brackets[1::2])
-    pairs = dict(zip(brackets[1::2], brackets[::2]))
-    for ch in s:
-        if ch in opens:
-            depth += 1
-        elif ch in closes:
-            depth -= 1
-        if ch == sep and depth == 0:
-            out.append("".join(buf).strip())
-            buf = []
-        else:
-            buf.append(ch)
-    if buf:
-        out.append("".join(buf).strip())
-    return out
-
-
-def _strip_prefixes(s: str) -> str:
-    # normalize common module prefixes used in annotations
-    return (
-        s.replace("typing.", "")
-        .replace("numpy.typing.", "")
-        .replace("numpy.", "")
-        .replace("np.", "")
-    )
-
-
-def _parse_annotated_str(hint_str: str):
-    """
-    If hint_str is 'Annotated[ ... ]', return (base_str, meta_list) else None.
-    meta_list items remain raw strings (no eval).
-    """
-    m = _ANN_RE.match(_strip_prefixes(hint_str))
-    if not m:
-        return None
-    inner = m.group(1)
-    parts = _split_top_level(inner, sep=",")
-    if not parts:
-        return None
-    base = parts[0].strip()
-    meta = [p.strip() for p in parts[1:]]
-    return base, meta
-
-
-def _shape_tuple_from_str(s: str):
-    """
-    Parse '(3,)', '(None, 3)', '(2,3,4)' → tuple[int|None, ...] or None if not a shape.
-    """
-    s = s.strip()
-    if not (s.startswith("(") and s.endswith(")")):
-        return None
-    body = s[1:-1].strip()
-    if not body:
-        return ()
-    items = _split_top_level(body, sep=",")
-    out = []
-    for it in items:
-        it = it.strip()
-        if it == "":
-            continue  # allow trailing comma
-        if it == "None":
-            out.append(None)
-        else:
-            try:
-                out.append(int(it))
-            except ValueError:
-                return None
-    return tuple(out)
-
-
-def _is_ndarray_base_str(base_str: str) -> bool:
-    base_norm = _strip_prefixes(base_str)
-    return base_norm.startswith("NDArray[") or base_norm.startswith("ndarray[")
-
-
-def _extract_ndarray_dtype_key_from_str(base_str: str) -> str | None:
-    base_norm = _strip_prefixes(base_str)
-    if "[" not in base_norm or "]" not in base_norm:
-        return None
-    inside = base_norm[base_norm.find("[") + 1 : base_norm.rfind("]")].strip()
-    return _strip_prefixes(inside)  # e.g. 'float' or 'float64'
-
-
-def _dtype_matches(arr: np.ndarray, dtype_key: str | None) -> bool:
-    if dtype_key is None:
-        return True
-    key = dtype_key.lower()
-    if key == "float":
-        return np.issubdtype(arr.dtype, np.floating)
-    if key == "int":
-        return np.issubdtype(arr.dtype, np.integer)
-    try:
-        return arr.dtype == np.dtype(key)  # e.g. 'float64', 'int32'
-    except TypeError:
-        return True  # unknown key → do not fail hard
-
-
-def _shape_matches(arr: np.ndarray, shape: tuple[int | None, ...]) -> bool:
-    if arr.ndim != len(shape):
-        return False
-    return all(dim is None or dim == s for s, dim in zip(arr.shape, shape))
diff --git a/mcdc/object_/util.py b/mcdc/object_/util.py
index d7de7dbb1..eec8ff919 100644
--- a/mcdc/object_/util.py
+++ b/mcdc/object_/util.py
@@ -1,11 +1,352 @@
-import numpy as np
+import re
+from typing import Annotated, Union, get_args, get_origin
 
-from mcdc.constant import INF
+import numpy as np
 from numpy import float64
 from numpy.typing import NDArray
 
+from mcdc.constant import INF
 from mcdc.print_ import print_error
 
+# ======================================================================================
+# Runtime annotation checking
+# ======================================================================================
+
+_DIMENSION_EXPRESSION_RE = re.compile(r"^\s*([A-Za-z_]\w*)\s*(?:([+-])\s*(\d+))?\s*$")
+_ANNOTATED_RE = re.compile(r"^\s*(?:typing\.)?Annotated\[(.*)\]\s*$")
+
+
+def parse_dimension_expression(expression: str) -> tuple[str, int]:
+    """Parse a dimension name with an optional integer offset.
+
+    Expressions such as ``"G"``, ``"G+1"``, and ``"N - 2"`` resolve to an
+    object attribute name and a signed offset without evaluating arbitrary
+    Python code.
+    """
+    match = _DIMENSION_EXPRESSION_RE.fullmatch(expression)
+    if match is None:
+        raise ValueError(f"Invalid dimension expression: {expression!r}")
+
+    attribute, operator, magnitude = match.groups()
+    offset = 0
+    if magnitude is not None:
+        offset = int(magnitude)
+        if operator == "-":
+            offset *= -1
+
+    return attribute, offset
+
+
+def check_type(value, hint, cls, obj=None) -> bool:
+    """Check a value against an MC/DC runtime type annotation.
+
+    The checker supports structured and stringified annotations, shaped NumPy
+    arrays, containers, unions, and unresolved class names. Annotation strings
+    are parsed without evaluating arbitrary Python code.
+    """
+    # Check stringified annotations without resolving forward references
+    if isinstance(hint, str):
+        hint = hint.strip()
+
+        if _is_ndarray_string(hint):
+            if not isinstance(value, np.ndarray):
+                return False
+            return _dtype_matches(value, _ndarray_dtype_key_from_string(hint))
+
+        annotated = _parse_annotated_string(hint)
+        if annotated is not None:
+            base, metadata = annotated
+            if _is_ndarray_string(base) and metadata:
+                if not isinstance(value, np.ndarray):
+                    return False
+                shape = _shape_from_string(metadata[0])
+                expected_shape = _resolve_shape(shape, obj)
+                if expected_shape is None or not _shape_matches(value, expected_shape):
+                    return False
+                return _dtype_matches(value, _ndarray_dtype_key_from_string(base))
+            return _mro_name_matches(value, base)
+
+        if "|" in hint:
+            return any(
+                check_type(value, item.strip(), cls)
+                for item in _split_top_level(hint, separator="|")
+            )
+
+        if hint.startswith("list[") and hint.endswith("]"):
+            item_type = _type_name_from_string(hint[5:-1])
+            if not isinstance(value, list):
+                return False
+            if item_type == "str":
+                return all(isinstance(item, str) for item in value)
+            if item_type in ("float", "float32", "float64"):
+                return all(isinstance(item, (float, int)) for item in value)
+            return True
+
+        return _mro_name_matches(value, hint)
+
+    # Check structured typing annotations
+    origin = get_origin(hint)
+
+    if origin is Annotated:
+        base, *metadata = get_args(hint)
+        if (
+            isinstance(value, np.ndarray)
+            and metadata
+            and isinstance(metadata[0], tuple)
+        ):
+            expected_shape = _resolve_shape(metadata[0], obj)
+            if expected_shape is None:
+                return False
+            return _shape_matches(value, expected_shape) and _dtype_matches(
+                value, _ndarray_dtype_key(base)
+            )
+        return check_type(value, base, cls)
+
+    if origin is np.ndarray:
+        return isinstance(value, np.ndarray)
+
+    if origin is None:
+        try:
+            return isinstance(value, hint)
+        except TypeError:
+            return True
+
+    if origin is list:
+        (item_type,) = get_args(hint)
+        return isinstance(value, list) and all(
+            check_type(item, item_type, cls) for item in value
+        )
+
+    if origin is set:
+        (item_type,) = get_args(hint)
+        return isinstance(value, set) and all(
+            check_type(item, item_type, cls) for item in value
+        )
+
+    if origin is dict:
+        key_type, value_type = get_args(hint)
+        return isinstance(value, dict) and all(
+            check_type(key, key_type, cls) and check_type(item, value_type, cls)
+            for key, item in value.items()
+        )
+
+    if origin is tuple:
+        item_types = get_args(hint)
+        if len(item_types) == 2 and item_types[1] is Ellipsis:
+            return isinstance(value, tuple) and all(
+                check_type(item, item_types[0], cls) for item in value
+            )
+        return (
+            isinstance(value, tuple)
+            and len(value) == len(item_types)
+            and all(
+                check_type(item, item_type, cls)
+                for item, item_type in zip(value, item_types)
+            )
+        )
+
+    if origin is Union:
+        return any(check_type(value, item_type, cls) for item_type in get_args(hint))
+
+    try:
+        return isinstance(value, origin)
+    except TypeError:
+        return True
+
+
+# --------------------------------------------------------------------------------------
+# Stringified annotation helpers
+# --------------------------------------------------------------------------------------
+
+
+def _parse_annotated_string(hint: str):
+    """Split a stringified Annotated type into its base and metadata."""
+    match = _ANNOTATED_RE.fullmatch(_strip_annotation_prefixes(hint))
+    if match is None:
+        return None
+
+    parts = _split_top_level(match.group(1))
+    if not parts:
+        return None
+    return parts[0].strip(), [part.strip() for part in parts[1:]]
+
+
+def _shape_from_string(shape: str):
+    """Parse shape metadata such as ``(3,)`` or ``("G+1",)``."""
+    shape = shape.strip()
+    if not (shape.startswith("(") and shape.endswith(")")):
+        return None
+
+    body = shape[1:-1].strip()
+    if not body:
+        return ()
+
+    dimensions = []
+    for item in _split_top_level(body):
+        item = item.strip()
+        if not item:
+            continue
+        if item == "None":
+            dimensions.append(None)
+            continue
+        try:
+            dimensions.append(int(item))
+            continue
+        except ValueError:
+            pass
+
+        if len(item) >= 2 and item[0] == item[-1] and item[0] in ("'", '"'):
+            item = item[1:-1]
+        try:
+            parse_dimension_expression(item)
+        except ValueError:
+            return None
+        dimensions.append(item)
+
+    return tuple(dimensions)
+
+
+def _split_top_level(
+    value: str,
+    separator: str = ",",
+    brackets: str = "[]()",
+) -> list[str]:
+    """Split text at separators that are not nested inside brackets."""
+    parts = []
+    buffer = []
+    depth = 0
+    opening = set(brackets[::2])
+    closing = set(brackets[1::2])
+
+    for character in value:
+        if character in opening:
+            depth += 1
+        elif character in closing:
+            depth -= 1
+
+        if character == separator and depth == 0:
+            parts.append("".join(buffer).strip())
+            buffer = []
+        else:
+            buffer.append(character)
+
+    if buffer:
+        parts.append("".join(buffer).strip())
+    return parts
+
+
+def _strip_annotation_prefixes(value: str) -> str:
+    """Remove module prefixes accepted in stringified annotations."""
+    return (
+        value.replace("typing.", "")
+        .replace("numpy.typing.", "")
+        .replace("numpy.", "")
+        .replace("np.", "")
+    )
+
+
+def _type_name_from_string(value: str) -> str:
+    """Return the unqualified base name of a stringified type."""
+    value = _strip_annotation_prefixes(value)
+    value = value.split("[", 1)[0]
+    return value.split(".")[-1].strip()
+
+
+def _mro_name_matches(value, expected: str) -> bool:
+    """Match an unresolved class name against the value's inheritance tree."""
+    expected_name = _type_name_from_string(expected)
+    return any(base.__name__ == expected_name for base in value.__class__.mro())
+
+
+# --------------------------------------------------------------------------------------
+# NumPy array annotation helpers
+# --------------------------------------------------------------------------------------
+
+
+def _is_ndarray_string(value: str) -> bool:
+    value = _strip_annotation_prefixes(value)
+    return value.startswith("NDArray[") or value.startswith("ndarray[")
+
+
+def _ndarray_dtype_key_from_string(value: str) -> str | None:
+    value = _strip_annotation_prefixes(value)
+    if "[" not in value or "]" not in value:
+        return None
+    dtype = value[value.find("[") + 1 : value.rfind("]")].strip()
+    return _strip_annotation_prefixes(dtype)
+
+
+def _ndarray_dtype_key(hint) -> str | None:
+    """Return the logical dtype from a structured NDArray annotation."""
+    arguments = get_args(hint)
+    if not arguments:
+        return None
+
+    dtype = arguments[-1]
+    dtype_arguments = get_args(dtype)
+    if dtype_arguments:
+        dtype = dtype_arguments[-1]
+
+    if dtype is float:
+        return "float"
+    if hasattr(dtype, "name"):
+        return dtype.name
+    try:
+        return np.dtype(dtype).name
+    except TypeError:
+        return None
+
+
+def _resolve_shape(shape, obj):
+    """Resolve dimension expressions against the object being validated."""
+    if shape is None:
+        return None
+
+    resolved = []
+    for dimension in shape:
+        if not isinstance(dimension, str):
+            resolved.append(dimension)
+            continue
+
+        if obj is None:
+            return None
+        try:
+            attribute, offset = parse_dimension_expression(dimension)
+            resolved.append(getattr(obj, attribute) + offset)
+        except (AttributeError, TypeError, ValueError):
+            return None
+
+    return tuple(resolved)
+
+
+def _dtype_matches(array: np.ndarray, dtype_key: str | None) -> bool:
+    if dtype_key is None:
+        return True
+
+    dtype_key = dtype_key.lower()
+    if dtype_key == "float":
+        return np.issubdtype(array.dtype, np.floating)
+    if dtype_key == "int":
+        return np.issubdtype(array.dtype, np.integer)
+    try:
+        return array.dtype == np.dtype(dtype_key)
+    except TypeError:
+        return True
+
+
+def _shape_matches(array: np.ndarray, shape: tuple[int | None, ...]) -> bool:
+    if array.ndim != len(shape):
+        return False
+    return all(
+        expected is None or actual == expected
+        for actual, expected in zip(array.shape, shape)
+    )
+
+
+# ======================================================================================
+# Probability distribution conversions
+# ======================================================================================
+
 
 def cmf_from_pmf(
     pmf: NDArray[float64],
@@ -173,11 +514,20 @@ def multi_cdf_from_pdf(offset, value, pdf):
     return pdf, cdf
 
 
+# ======================================================================================
+# Array helpers
+# ======================================================================================
+
+
 def is_sorted(a):
     """Return whether an array is monotonically nondecreasing."""
     return np.all(a[:-1] <= a[1:])
 
 
+# ======================================================================================
+# Natural isotopic abundance
+# ======================================================================================
+
 # Natural isotopic abundance data from
 # https://www.nndc.bnl.gov/walletcards/search.html
 ISOTOPIC_ABUNDANCE = {
@@ -640,6 +990,11 @@ def is_sorted(a):
 }
 
 
+# ======================================================================================
+# Object helpers
+# ======================================================================================
+
+
 def move_object(object_, velocities, durations):
     """Populate the shared piecewise-constant motion representation.
 

From ff9348b5b4723cd4849aed191883c0932243b163 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 12:35:19 +0700
Subject: [PATCH 107/202] reorganize constant. add mgxs modes

---
 mcdc/constant.py | 295 ++++++++++++++++++++++++++---------------------
 1 file changed, 162 insertions(+), 133 deletions(-)

diff --git a/mcdc/constant.py b/mcdc/constant.py
index 79ade2223..c26dc6063 100644
--- a/mcdc/constant.py
+++ b/mcdc/constant.py
@@ -1,60 +1,131 @@
 import math
 
-# Data index
-TALLY = 0
+# ======================================================================================
+# Mathematical and numerical constants
+# ======================================================================================
 
-# Tally types
-TALLY_SURFACE_CROSSING = 0
-TALLY_COLLISION = 1
-TALLY_TRACKLENGTH = 2
+PI = math.pi
+PI_HALF = PI / 2.0
+PI_SQRT = math.sqrt(PI)
 
-# Meshes
-MESH_UNIFORM = 0
-MESH_STRUCTURED = 1
+TINY = 1e-10
+INF = 1e10
 
-# Tally scores
-## Tracklength
-SCORE_FLUX = 0
-SCORE_DENSITY = 1
-SCORE_COLLISION = 2
-SCORE_CAPTURE = 3
-SCORE_FISSION = 4
-## Surface-crossing
-SCORE_CURRENT_NET = 100
-SCORE_CURRENT_IN = 101
-SCORE_CURRENT_OUT = 102
-## Collision
-SCORE_ENERGY_DEPOSITION = 200
 
-# Supported tally scores for estimator types
-SUPPORTED_SCORES_SURFACE_CROSSING = {"current-net", "current-in", "current-out"}
-SUPPORTED_SCORES_TRACKLENGTH = {"flux", "density", "collision", "capture", "fission"}
-SUPPORTED_SCORES_COLLISION = {"energy_deposition"}
-SUPPORTED_SCORES = (
-    SUPPORTED_SCORES_SURFACE_CROSSING
-    | SUPPORTED_SCORES_TRACKLENGTH
-    | SUPPORTED_SCORES_COLLISION
-)
+# ======================================================================================
+# Physics and nuclear data
+# ======================================================================================
+
+# Physical constants
+LIGHT_SPEED = 2.99792458e10  # cm/s
+NEUTRON_MASS = 939.565413e6  # eV/c^2
+ELECTRON_MASS = 510.99895069e3  # eV/c^2
+BOLTZMANN_K = 8.61733326e-5  # eV/K
+
+# Physics thresholds
+ELECTRON_CUTOFF_ENERGY = 100  # eV
+MU_CUTOFF = 0.999999
+THERMAL_THRESHOLD_FACTOR = 400
+
+# Particle types
+PARTICLE_NEUTRON = 0
+PARTICLE_ELECTRON = 1
+PARTICLE_PROTON = 2
+
+# Material types
+# TODO: Remove these after Material no longer uses polymorphic type IDs.
+MATERIAL = 0
+MATERIAL_MG = 1
+
+# Neutron multigroup energy-grid organization
+MULTIGROUP_NEUTRON_GRID_SHARED = 0
+MULTIGROUP_NEUTRON_GRID_LOCAL = 1
+
+# Neutron multigroup energy representation
+MULTIGROUP_NEUTRON_ENERGY_MIDPOINT = 0
+MULTIGROUP_NEUTRON_ENERGY_LOG_MIDPOINT = 1
+MULTIGROUP_NEUTRON_ENERGY_UNIFORM = 2
+MULTIGROUP_NEUTRON_ENERGY_LOG_UNIFORM = 3
+
+# Neutron reactions
+NEUTRON_REACTION_TOTAL = 0
+NEUTRON_REACTION_ELASTIC_SCATTERING = 1
+NEUTRON_REACTION_CAPTURE = 2
+NEUTRON_REACTION_INELASTIC_SCATTERING = 3
+NEUTRON_REACTION_FISSION = 4
+NEUTRON_REACTION_FISSION_PROMPT = 5
+NEUTRON_REACTION_FISSION_DELAYED = 6
+
+# Electron reactions
+ELECTRON_REACTION_TOTAL = 100
+ELECTRON_REACTION_ELASTIC_SCATTERING = 101
+ELECTRON_REACTION_IONIZATION = 102
+ELECTRON_REACTION_BREMSSTRAHLUNG = 103
+ELECTRON_REACTION_EXCITATION = 104
+
+# Data representations
+DATA_NONE = 0
+DATA_TABLE = 1
+DATA_POLYNOMIAL = 2
+
+# Interpolation laws
+INTERPOLATION_HISTOGRAM = 1
+INTERPOLATION_LINEAR = 2
+INTERPOLATION_SEMILOGX = 3
+INTERPOLATION_SEMILOGY = 4
+INTERPOLATION_LOG = 5
+
+# Probability distributions
+DISTRIBUTION_NONE = 0
+DISTRIBUTION_PMF = 1
+DISTRIBUTION_TABULATED = 2
+DISTRIBUTION_MULTITABLE = 3
+DISTRIBUTION_LEVEL_SCATTERING = 4
+DISTRIBUTION_EVAPORATION = 5
+DISTRIBUTION_MAXWELLIAN = 6
+DISTRIBUTION_KALBACH_MANN = 7
+DISTRIBUTION_TABULATED_ENERGY_ANGLE = 8
+DISTRIBUTION_N_BODY = 9
+
+# Angular distributions
+ANGLE_ISOTROPIC = 0
+ANGLE_DISTRIBUTED = 1
+ANGLE_ENERGY_CORRELATED = 2
+
+# Reference frames
+REFERENCE_FRAME_LAB = 0
+REFERENCE_FRAME_COM = 1
+
+
+# ======================================================================================
+# Geometry
+# ======================================================================================
+
+# Axes
+AXIS_X = 0
+AXIS_Y = 1
+AXIS_Z = 2
+AXIS_T = 3
+
+# Mesh types
+MESH_UNIFORM = 0
+MESH_STRUCTURED = 1
 
-# Boundary condition
+# Boundary conditions
 BC_NONE = 0
 BC_VACUUM = 1
 BC_REFLECTIVE = 2
 
-# Cell fill
+# Cell fills
 FILL_MATERIAL = 0
 FILL_UNIVERSE = 1
 FILL_LATTICE = 2
 FILL_NONE = 3
 
-# Region
-REGION_HALFSPACE = 0
-REGION_INTERSECTION = 1
-REGION_UNION = 2
-REGION_COMPLEMENT = 3
-REGION_ALL = 4
+# Universe
+UNIVERSE_ROOT = 0
 
-# Surface type
+# Surface types
 SURFACE_PLANE_X = 1
 SURFACE_PLANE_Y = 2
 SURFACE_PLANE_Z = 3
@@ -73,88 +144,72 @@
 SURFACE_TORUS_Z = 16
 SURFACE_TORUS = 17
 
-# Boolean operator
+# Boolean operators
 BOOL_AND = -1
 BOOL_OR = -2
 BOOL_NOT = -3
 
-# Universe
-UNIVERSE_ROOT = 0
 
-# Events
-#   The << operator represents a bitshift.
-#   Each event is assigned 1 << X, which is equal to 2 to the power of X.
+# ======================================================================================
+# Transport
+# ======================================================================================
+
+# Events are bit flags and may be combined with bitwise operations.
 EVENT_NONE = 1 << 0
-# Geometry events
 EVENT_SURFACE_CROSSING = 1 << 1
 EVENT_LATTICE_CROSSING = 1 << 2
 EVENT_LOST = 1 << 3
-# Collision/reaction events
 EVENT_COLLISION = 1 << 4
-# Miscellanies
 EVENT_TIME_CENSUS = 1 << 5
 EVENT_TIME_BOUNDARY = 1 << 6
 
-# Materials
-MATERIAL = 0
-MATERIAL_MG = 1
-MATERIAL_ELEMENTAL = 2
+# Coincidence tolerances
+COINCIDENCE_TOLERANCE = TINY
+COINCIDENCE_TOLERANCE_DIRECTION = 1e-5
+COINCIDENCE_TOLERANCE_ENERGY = 1e-5
+COINCIDENCE_TOLERANCE_TIME = TINY * 1e-2
 
-# Reactions
-NEUTRON_REACTION_TOTAL = 0
-NEUTRON_REACTION_ELASTIC_SCATTERING = 1
-NEUTRON_REACTION_CAPTURE = 2
-NEUTRON_REACTION_INELASTIC_SCATTERING = 3
-NEUTRON_REACTION_FISSION = 4
-NEUTRON_REACTION_FISSION_PROMPT = 5
-NEUTRON_REACTION_FISSION_DELAYED = 6
-ELECTRON_REACTION_TOTAL = 100
-ELECTRON_REACTION_ELASTIC_SCATTERING = 101
-ELECTRON_REACTION_ELASTIC_SMALL_ANGLE = 102
-ELECTRON_REACTION_ELASTIC_LARGE_ANGLE = 103
-ELECTRON_REACTION_IONIZATION = 104
-ELECTRON_REACTION_BREMSSTRAHLUNG = 105
-ELECTRON_REACTION_EXCITATION = 106
 
-# Particle types
-PARTICLE_NEUTRON = 0
-PARTICLE_ELECTRON = 1
-PARTICLE_PROTON = 2
+# ======================================================================================
+# Tallies
+# ======================================================================================
 
-# Data
-DATA_NONE = 0
-DATA_TABLE = 1
-DATA_POLYNOMIAL = 2
+# Tally estimator types
+TALLY_SURFACE_CROSSING = 0
+TALLY_COLLISION = 1
+TALLY_TRACKLENGTH = 2
 
-# Distribution
-DISTRIBUTION_NONE = 0
-DISTRIBUTION_PMF = 1
-DISTRIBUTION_TABULATED = 2
-DISTRIBUTION_MULTITABLE = 3
-DISTRIBUTION_LEVEL_SCATTERING = 4
-DISTRIBUTION_EVAPORATION = 5
-DISTRIBUTION_MAXWELLIAN = 6
-DISTRIBUTION_KALBACH_MANN = 7
-DISTRIBUTION_TABULATED_ENERGY_ANGLE = 8
-DISTRIBUTION_N_BODY = 9
+# Track-length scores
+SCORE_FLUX = 0
+SCORE_DENSITY = 1
+SCORE_COLLISION = 2
+SCORE_CAPTURE = 3
+SCORE_FISSION = 4
 
-# Anguler distribution type
-ANGLE_ISOTROPIC = 0
-ANGLE_DISTRIBUTED = 1
-ANGLE_ENERGY_CORRELATED = 2
+# Surface-crossing scores
+SCORE_CURRENT_NET = 100
+SCORE_CURRENT_IN = 101
+SCORE_CURRENT_OUT = 102
 
-# Referance frame
-REFERENCE_FRAME_LAB = 0
-REFERENCE_FRAME_COM = 1
+# Collision scores
+SCORE_ENERGY_DEPOSITION = 200
 
-# Interpolation law
-INTERPOLATION_HISTOGRAM = 1
-INTERPOLATION_LINEAR = 2
-INTERPOLATION_SEMILOGX = 3
-INTERPOLATION_SEMILOGY = 4
-INTERPOLATION_LOG = 5
+# Supported scores by estimator type
+SUPPORTED_SCORES_SURFACE_CROSSING = {"current-net", "current-in", "current-out"}
+SUPPORTED_SCORES_TRACKLENGTH = {"flux", "density", "collision", "capture", "fission"}
+SUPPORTED_SCORES_COLLISION = {"energy_deposition"}
+SUPPORTED_SCORES = (
+    SUPPORTED_SCORES_SURFACE_CROSSING
+    | SUPPORTED_SCORES_TRACKLENGTH
+    | SUPPORTED_SCORES_COLLISION
+)
+
+
+# ======================================================================================
+# Techniques and diagnostics
+# ======================================================================================
 
-# Gyration raius type
+# Gyration-radius types
 GYRATION_RADIUS_ALL = 0
 GYRATION_RADIUS_INFINITE_X = 1
 GYRATION_RADIUS_INFINITE_Y = 2
@@ -163,48 +218,22 @@
 GYRATION_RADIUS_ONLY_Y = 5
 GYRATION_RADIUS_ONLY_Z = 6
 
-# Population control
+# Population-control types are currently unused.
 PCT_NONE = 0
 PCT_COMBING = 1
 PCT_COMBING_WEIGHT = 2
 PCT_SPLITTING_ROULETTE = 3
 PCT_SPLITTING_ROULETTE_WEIGHT = 4
 
-# Misc.
-TINY = 1e-10
-COINCIDENCE_TOLERANCE = TINY
-COINCIDENCE_TOLERANCE_DIRECTION = 1e-5
-COINCIDENCE_TOLERANCE_ENERGY = 1e-5
-COINCIDENCE_TOLERANCE_TIME = TINY * 1e-2
-INF = 1e10
-PI = math.pi
-PI_SQRT = math.sqrt(PI)
-PI_HALF = PI / 2.0
-BANKMAX = 100  # Default maximum active bank
-MAX_BISECTION_ITERATIONS = 48
-
-# Axes
-AXIS_X = 0
-AXIS_Y = 1
-AXIS_Z = 2
-AXIS_T = 3
-
-# Physics
-LIGHT_SPEED = 2.99792458e10  # cm/s
-NEUTRON_MASS = 939.565413e6  # eV/c^2
-ELECTRON_MASS = 510.99895069e3  # eV/c^2
-BOLTZMANN_K = 8.61733326e-5  # eV/K
-ELECTRON_CUTOFF_ENERGY = 100  # eV
-MU_CUTOFF = 0.999999
-THERMAL_THRESHOLD_FACTOR = 400
-
-# Weight Windows Methods
+# Weight-window methods are currently unused.
 WW_USER = 0
 WW_PREVIOUS = 1
-# Weight Windows Modifications
+
+# Weight-window modifications are currently unused.
 WW_MIN = 0
 WW_WOLLABER = 1
 
+
 # ======================================================================================
 # GPU settings
 # ======================================================================================
@@ -214,7 +243,7 @@
 GPU_STRATEGY_ASYNC = 0
 GPU_STRATEGY_EVENT = 1
 
-# GPU async. types
+# GPU asynchronous-operation types
 GPU_ASYNC_SIMPLE = 0
 
 # GPU storage types

From 453002377a7de4a4aecc990487bf40b25c78c6af Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 12:39:38 +0700
Subject: [PATCH 108/202] add test for annotation sizing

---
 test/unit/test_annotation_shape.py | 73 ++++++++++++++++++++++++++++++
 1 file changed, 73 insertions(+)
 create mode 100644 test/unit/test_annotation_shape.py

diff --git a/test/unit/test_annotation_shape.py b/test/unit/test_annotation_shape.py
new file mode 100644
index 000000000..f2f058de5
--- /dev/null
+++ b/test/unit/test_annotation_shape.py
@@ -0,0 +1,73 @@
+from __future__ import annotations
+
+from typing import Annotated
+
+import numpy as np
+import pytest
+from numpy.typing import NDArray
+
+from mcdc.code_factory.numba_layers_generator import (
+    _accessor_1d_all,
+    _accessor_1d_last,
+)
+from mcdc.object_.base import MCDCBase
+from mcdc.object_.util import check_type, parse_dimension_expression
+
+
+class DimensionedObject(MCDCBase):
+    label = "dimensioned_object"
+
+    G: int
+    energy: Annotated[NDArray[np.float64], ("G+1",)]
+
+    def __init__(self, G, energy):
+        self.G = G
+        self.energy = energy
+
+
+@pytest.mark.parametrize(
+    "expression, expected",
+    [
+        ("G", ("G", 0)),
+        ("G+1", ("G", 1)),
+        ("N - 2", ("N", -2)),
+    ],
+)
+def test_parse_dimension_expression(expression, expected):
+    assert parse_dimension_expression(expression) == expected
+
+
+@pytest.mark.parametrize("expression", ["1+G", "G*2", "G+1+2", "G + value"])
+def test_parse_dimension_expression_rejects_unsupported_syntax(expression):
+    with pytest.raises(ValueError, match="Invalid dimension expression"):
+        parse_dimension_expression(expression)
+
+
+def test_stringified_annotation_resolves_dimension_offset():
+    dimensioned = DimensionedObject(2, np.zeros(3))
+
+    assert dimensioned.energy.shape == (3,)
+
+
+def test_structured_annotation_resolves_dimension_offset():
+    dimensioned = DimensionedObject.__new__(DimensionedObject)
+    dimensioned.G = 2
+    hint = Annotated[NDArray[np.float64], ("G+1",)]
+
+    assert check_type(np.zeros(3), hint, DimensionedObject, dimensioned)
+    assert not check_type(np.zeros(2), hint, DimensionedObject, dimensioned)
+
+
+def test_stringified_annotation_rejects_incorrect_offset_shape(capsys):
+    with pytest.raises(SystemExit):
+        DimensionedObject(2, np.zeros(2))
+
+    assert "energy must be" in capsys.readouterr().out
+
+
+def test_generated_accessor_resolves_dimension_offset():
+    all_source = _accessor_1d_all("mgxs", "energy", "G+1")
+    last_source = _accessor_1d_last("mgxs", "energy", "N - 2")
+
+    assert 'size = mgxs["G"] + 1' in all_source
+    assert 'size = mgxs["N"] - 2' in last_source

From fd104a37aacd9c6f7da49915cc5333b9ead03687 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 13:04:08 +0700
Subject: [PATCH 109/202] add mgxs class

---
 docs/source/reference/python_api/index.rst |   4 +-
 mcdc/__init__.py                           |   1 +
 mcdc/constant.py                           |   4 +-
 mcdc/mcdc_get/__init__.py                  |   2 +
 mcdc/mcdc_get/mgxs.py                      | 414 +++++++++++++++++++++
 mcdc/mcdc_set/__init__.py                  |   2 +
 mcdc/mcdc_set/mgxs.py                      | 414 +++++++++++++++++++++
 mcdc/numba_types.py                        |  39 ++
 mcdc/object_/mgxs.py                       | 411 ++++++++++++++++++++
 test/unit/test_mgxs.py                     | 271 ++++++++++++++
 10 files changed, 1559 insertions(+), 3 deletions(-)
 create mode 100644 mcdc/mcdc_get/mgxs.py
 create mode 100644 mcdc/mcdc_set/mgxs.py
 create mode 100644 mcdc/object_/mgxs.py
 create mode 100644 test/unit/test_mgxs.py

diff --git a/docs/source/reference/python_api/index.rst b/docs/source/reference/python_api/index.rst
index 6e1584618..166f5edbc 100644
--- a/docs/source/reference/python_api/index.rst
+++ b/docs/source/reference/python_api/index.rst
@@ -45,7 +45,8 @@ Materials
 
 Materials define the interaction data used by cells. Use
 :class:`mcdc.Material` for continuous-energy transport and
-:class:`mcdc.MaterialMG` for multigroup transport.
+:class:`mcdc.MaterialMG` for multigroup transport. :class:`mcdc.MGXS` stores
+particle-agnostic groupwise interaction data for the unified material model.
 
 .. autosummary::
    :toctree: generated
@@ -54,6 +55,7 @@ Materials define the interaction data used by cells. Use
 
    mcdc.Material
    mcdc.MaterialMG
+   mcdc.MGXS
 
 
 Geometry
diff --git a/mcdc/__init__.py b/mcdc/__init__.py
index 06c5fa3c4..2f82cd348 100644
--- a/mcdc/__init__.py
+++ b/mcdc/__init__.py
@@ -11,6 +11,7 @@
 
 from mcdc.object_.cell import Cell, Universe, Lattice
 from mcdc.object_.material import Material, MaterialMG
+from mcdc.object_.mgxs import MGXS
 from mcdc.object_.mesh import MeshUniform, MeshStructured
 from mcdc.object_.simulation import Simulation
 from mcdc.object_.source import Source
diff --git a/mcdc/constant.py b/mcdc/constant.py
index c26dc6063..355035e0b 100644
--- a/mcdc/constant.py
+++ b/mcdc/constant.py
@@ -43,9 +43,9 @@
 
 # Neutron multigroup energy representation
 MULTIGROUP_NEUTRON_ENERGY_MIDPOINT = 0
-MULTIGROUP_NEUTRON_ENERGY_LOG_MIDPOINT = 1
+MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG = 1
 MULTIGROUP_NEUTRON_ENERGY_UNIFORM = 2
-MULTIGROUP_NEUTRON_ENERGY_LOG_UNIFORM = 3
+MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG = 3
 
 # Neutron reactions
 NEUTRON_REACTION_TOTAL = 0
diff --git a/mcdc/mcdc_get/__init__.py b/mcdc/mcdc_get/__init__.py
index d1d03c34c..11888cbb5 100644
--- a/mcdc/mcdc_get/__init__.py
+++ b/mcdc/mcdc_get/__init__.py
@@ -72,6 +72,8 @@
 
 import mcdc.mcdc_get.uniform_mesh as uniform_mesh
 
+import mcdc.mcdc_get.mgxs as mgxs
+
 import mcdc.mcdc_get.neutron_reaction as neutron_reaction
 
 import mcdc.mcdc_get.neutron_capture_reaction as neutron_capture_reaction
diff --git a/mcdc/mcdc_get/mgxs.py b/mcdc/mcdc_get/mgxs.py
new file mode 100644
index 000000000..226090cfb
--- /dev/null
+++ b/mcdc/mcdc_get/mgxs.py
@@ -0,0 +1,414 @@
+# The following is automatically generated by code_factory.py
+
+from numba import njit
+
+
+@njit
+def energy_grid(index, mgxs, data):
+    offset = mgxs["energy_grid_offset"]
+    return data[offset + index]
+
+
+@njit
+def energy_grid_all(mgxs, data):
+    start = mgxs["energy_grid_offset"]
+    size = mgxs["G"] + 1
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def energy_grid_last(mgxs, data):
+    start = mgxs["energy_grid_offset"]
+    size = mgxs["G"] + 1
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def energy_grid_chunk(start, length, mgxs, data):
+    start += mgxs["energy_grid_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def speed(index, mgxs, data):
+    offset = mgxs["speed_offset"]
+    return data[offset + index]
+
+
+@njit
+def speed_all(mgxs, data):
+    start = mgxs["speed_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def speed_last(mgxs, data):
+    start = mgxs["speed_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def speed_chunk(start, length, mgxs, data):
+    start += mgxs["speed_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def decay_rate(index, mgxs, data):
+    offset = mgxs["decay_rate_offset"]
+    return data[offset + index]
+
+
+@njit
+def decay_rate_all(mgxs, data):
+    start = mgxs["decay_rate_offset"]
+    size = mgxs["J"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def decay_rate_last(mgxs, data):
+    start = mgxs["decay_rate_offset"]
+    size = mgxs["J"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def decay_rate_chunk(start, length, mgxs, data):
+    start += mgxs["decay_rate_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def capture(index, mgxs, data):
+    offset = mgxs["capture_offset"]
+    return data[offset + index]
+
+
+@njit
+def capture_all(mgxs, data):
+    start = mgxs["capture_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def capture_last(mgxs, data):
+    start = mgxs["capture_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def capture_chunk(start, length, mgxs, data):
+    start += mgxs["capture_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def scatter(index, mgxs, data):
+    offset = mgxs["scatter_offset"]
+    return data[offset + index]
+
+
+@njit
+def scatter_all(mgxs, data):
+    start = mgxs["scatter_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def scatter_last(mgxs, data):
+    start = mgxs["scatter_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def scatter_chunk(start, length, mgxs, data):
+    start += mgxs["scatter_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def fission(index, mgxs, data):
+    offset = mgxs["fission_offset"]
+    return data[offset + index]
+
+
+@njit
+def fission_all(mgxs, data):
+    start = mgxs["fission_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def fission_last(mgxs, data):
+    start = mgxs["fission_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def fission_chunk(start, length, mgxs, data):
+    start += mgxs["fission_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def total(index, mgxs, data):
+    offset = mgxs["total_offset"]
+    return data[offset + index]
+
+
+@njit
+def total_all(mgxs, data):
+    start = mgxs["total_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def total_last(mgxs, data):
+    start = mgxs["total_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def total_chunk(start, length, mgxs, data):
+    start += mgxs["total_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_s(index, mgxs, data):
+    offset = mgxs["nu_s_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_s_all(mgxs, data):
+    start = mgxs["nu_s_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_s_last(mgxs, data):
+    start = mgxs["nu_s_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_s_chunk(start, length, mgxs, data):
+    start += mgxs["nu_s_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_p(index, mgxs, data):
+    offset = mgxs["nu_p_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_p_all(mgxs, data):
+    start = mgxs["nu_p_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_p_last(mgxs, data):
+    start = mgxs["nu_p_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_p_chunk(start, length, mgxs, data):
+    start += mgxs["nu_p_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_d_vector(index_1, mgxs, data):
+    offset = mgxs["nu_d_offset"]
+    stride = mgxs["J"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def nu_d(index_1, index_2, mgxs, data):
+    offset = mgxs["nu_d_offset"]
+    stride = mgxs["J"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def nu_d_chunk(start, length, mgxs, data):
+    start += mgxs["nu_d_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_d_total(index, mgxs, data):
+    offset = mgxs["nu_d_total_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_d_total_all(mgxs, data):
+    start = mgxs["nu_d_total_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_d_total_last(mgxs, data):
+    start = mgxs["nu_d_total_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_d_total_chunk(start, length, mgxs, data):
+    start += mgxs["nu_d_total_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_f(index, mgxs, data):
+    offset = mgxs["nu_f_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_f_all(mgxs, data):
+    start = mgxs["nu_f_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_f_last(mgxs, data):
+    start = mgxs["nu_f_offset"]
+    size = mgxs["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_f_chunk(start, length, mgxs, data):
+    start += mgxs["nu_f_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def chi_s_vector(index_1, mgxs, data):
+    offset = mgxs["chi_s_offset"]
+    stride = mgxs["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def chi_s(index_1, index_2, mgxs, data):
+    offset = mgxs["chi_s_offset"]
+    stride = mgxs["G"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def chi_s_chunk(start, length, mgxs, data):
+    start += mgxs["chi_s_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def chi_p_vector(index_1, mgxs, data):
+    offset = mgxs["chi_p_offset"]
+    stride = mgxs["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def chi_p(index_1, index_2, mgxs, data):
+    offset = mgxs["chi_p_offset"]
+    stride = mgxs["G"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def chi_p_chunk(start, length, mgxs, data):
+    start += mgxs["chi_p_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def chi_d_vector(index_1, mgxs, data):
+    offset = mgxs["chi_d_offset"]
+    stride = mgxs["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def chi_d(index_1, index_2, mgxs, data):
+    offset = mgxs["chi_d_offset"]
+    stride = mgxs["G"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def chi_d_chunk(start, length, mgxs, data):
+    start += mgxs["chi_d_offset"]
+    end = start + length
+    return data[start:end]
diff --git a/mcdc/mcdc_set/__init__.py b/mcdc/mcdc_set/__init__.py
index 8f771c058..0d1f4444f 100644
--- a/mcdc/mcdc_set/__init__.py
+++ b/mcdc/mcdc_set/__init__.py
@@ -72,6 +72,8 @@
 
 import mcdc.mcdc_set.uniform_mesh as uniform_mesh
 
+import mcdc.mcdc_set.mgxs as mgxs
+
 import mcdc.mcdc_set.neutron_reaction as neutron_reaction
 
 import mcdc.mcdc_set.neutron_capture_reaction as neutron_capture_reaction
diff --git a/mcdc/mcdc_set/mgxs.py b/mcdc/mcdc_set/mgxs.py
new file mode 100644
index 000000000..071e10327
--- /dev/null
+++ b/mcdc/mcdc_set/mgxs.py
@@ -0,0 +1,414 @@
+# The following is automatically generated by code_factory.py
+
+from numba import njit
+
+
+@njit
+def energy_grid(index, mgxs, data, value):
+    offset = mgxs["energy_grid_offset"]
+    data[offset + index] = value
+
+
+@njit
+def energy_grid_all(mgxs, data, value):
+    start = mgxs["energy_grid_offset"]
+    size = mgxs["G"] + 1
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def energy_grid_last(mgxs, data, value):
+    start = mgxs["energy_grid_offset"]
+    size = mgxs["G"] + 1
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def energy_grid_chunk(start, length, mgxs, data, value):
+    start += mgxs["energy_grid_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def speed(index, mgxs, data, value):
+    offset = mgxs["speed_offset"]
+    data[offset + index] = value
+
+
+@njit
+def speed_all(mgxs, data, value):
+    start = mgxs["speed_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def speed_last(mgxs, data, value):
+    start = mgxs["speed_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def speed_chunk(start, length, mgxs, data, value):
+    start += mgxs["speed_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def decay_rate(index, mgxs, data, value):
+    offset = mgxs["decay_rate_offset"]
+    data[offset + index] = value
+
+
+@njit
+def decay_rate_all(mgxs, data, value):
+    start = mgxs["decay_rate_offset"]
+    size = mgxs["J"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def decay_rate_last(mgxs, data, value):
+    start = mgxs["decay_rate_offset"]
+    size = mgxs["J"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def decay_rate_chunk(start, length, mgxs, data, value):
+    start += mgxs["decay_rate_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def capture(index, mgxs, data, value):
+    offset = mgxs["capture_offset"]
+    data[offset + index] = value
+
+
+@njit
+def capture_all(mgxs, data, value):
+    start = mgxs["capture_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def capture_last(mgxs, data, value):
+    start = mgxs["capture_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def capture_chunk(start, length, mgxs, data, value):
+    start += mgxs["capture_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def scatter(index, mgxs, data, value):
+    offset = mgxs["scatter_offset"]
+    data[offset + index] = value
+
+
+@njit
+def scatter_all(mgxs, data, value):
+    start = mgxs["scatter_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def scatter_last(mgxs, data, value):
+    start = mgxs["scatter_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def scatter_chunk(start, length, mgxs, data, value):
+    start += mgxs["scatter_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def fission(index, mgxs, data, value):
+    offset = mgxs["fission_offset"]
+    data[offset + index] = value
+
+
+@njit
+def fission_all(mgxs, data, value):
+    start = mgxs["fission_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def fission_last(mgxs, data, value):
+    start = mgxs["fission_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def fission_chunk(start, length, mgxs, data, value):
+    start += mgxs["fission_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def total(index, mgxs, data, value):
+    offset = mgxs["total_offset"]
+    data[offset + index] = value
+
+
+@njit
+def total_all(mgxs, data, value):
+    start = mgxs["total_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def total_last(mgxs, data, value):
+    start = mgxs["total_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def total_chunk(start, length, mgxs, data, value):
+    start += mgxs["total_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_s(index, mgxs, data, value):
+    offset = mgxs["nu_s_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_s_all(mgxs, data, value):
+    start = mgxs["nu_s_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_s_last(mgxs, data, value):
+    start = mgxs["nu_s_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_s_chunk(start, length, mgxs, data, value):
+    start += mgxs["nu_s_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_p(index, mgxs, data, value):
+    offset = mgxs["nu_p_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_p_all(mgxs, data, value):
+    start = mgxs["nu_p_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_p_last(mgxs, data, value):
+    start = mgxs["nu_p_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_p_chunk(start, length, mgxs, data, value):
+    start += mgxs["nu_p_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_d_vector(index_1, mgxs, data, value):
+    offset = mgxs["nu_d_offset"]
+    stride = mgxs["J"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def nu_d(index_1, index_2, mgxs, data, value):
+    offset = mgxs["nu_d_offset"]
+    stride = mgxs["J"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def nu_d_chunk(start, length, mgxs, data, value):
+    start += mgxs["nu_d_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_d_total(index, mgxs, data, value):
+    offset = mgxs["nu_d_total_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_d_total_all(mgxs, data, value):
+    start = mgxs["nu_d_total_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_d_total_last(mgxs, data, value):
+    start = mgxs["nu_d_total_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_d_total_chunk(start, length, mgxs, data, value):
+    start += mgxs["nu_d_total_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_f(index, mgxs, data, value):
+    offset = mgxs["nu_f_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_f_all(mgxs, data, value):
+    start = mgxs["nu_f_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_f_last(mgxs, data, value):
+    start = mgxs["nu_f_offset"]
+    size = mgxs["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_f_chunk(start, length, mgxs, data, value):
+    start += mgxs["nu_f_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def chi_s_vector(index_1, mgxs, data, value):
+    offset = mgxs["chi_s_offset"]
+    stride = mgxs["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def chi_s(index_1, index_2, mgxs, data, value):
+    offset = mgxs["chi_s_offset"]
+    stride = mgxs["G"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def chi_s_chunk(start, length, mgxs, data, value):
+    start += mgxs["chi_s_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def chi_p_vector(index_1, mgxs, data, value):
+    offset = mgxs["chi_p_offset"]
+    stride = mgxs["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def chi_p(index_1, index_2, mgxs, data, value):
+    offset = mgxs["chi_p_offset"]
+    stride = mgxs["G"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def chi_p_chunk(start, length, mgxs, data, value):
+    start += mgxs["chi_p_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def chi_d_vector(index_1, mgxs, data, value):
+    offset = mgxs["chi_d_offset"]
+    stride = mgxs["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def chi_d(index_1, index_2, mgxs, data, value):
+    offset = mgxs["chi_d_offset"]
+    stride = mgxs["G"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def chi_d_chunk(start, length, mgxs, data, value):
+    start += mgxs["chi_d_offset"]
+    end = start + length
+    data[start:end] = value
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index 2dd5832c2..7f0e8b9a5 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -457,6 +457,45 @@
     ('base_ID', int64),
 ])
 
+mgxs = into_dtype([
+    ('G', int64),
+    ('J', int64),
+    ('has_energy_grid', bool),
+    ('energy_grid_offset', int64),
+    ('energy_grid_length', int64),
+    ('energy_representation', int64),
+    ('speed_offset', int64),
+    ('speed_length', int64),
+    ('decay_rate_offset', int64),
+    ('decay_rate_length', int64),
+    ('capture_offset', int64),
+    ('capture_length', int64),
+    ('scatter_offset', int64),
+    ('scatter_length', int64),
+    ('fission_offset', int64),
+    ('fission_length', int64),
+    ('total_offset', int64),
+    ('total_length', int64),
+    ('nu_s_offset', int64),
+    ('nu_s_length', int64),
+    ('nu_p_offset', int64),
+    ('nu_p_length', int64),
+    ('nu_d_offset', int64),
+    ('nu_d_length', int64),
+    ('nu_d_total_offset', int64),
+    ('nu_d_total_length', int64),
+    ('nu_f_offset', int64),
+    ('nu_f_length', int64),
+    ('chi_s_offset', int64),
+    ('chi_s_length', int64),
+    ('chi_p_offset', int64),
+    ('chi_p_length', int64),
+    ('chi_d_offset', int64),
+    ('chi_d_length', int64),
+    ('fissionable', bool),
+    ('ID', int64),
+])
+
 neutron_reaction = into_dtype([
     ('MT', int64),
     ('xs_offset', int64),
diff --git a/mcdc/object_/mgxs.py b/mcdc/object_/mgxs.py
new file mode 100644
index 000000000..39af17750
--- /dev/null
+++ b/mcdc/object_/mgxs.py
@@ -0,0 +1,411 @@
+from types import NoneType
+from typing import Annotated
+
+import numpy as np
+from numpy import float64
+from numpy.typing import ArrayLike, NDArray
+
+from mcdc.constant import (
+    MULTIGROUP_NEUTRON_ENERGY_MIDPOINT,
+    MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG,
+    MULTIGROUP_NEUTRON_ENERGY_UNIFORM,
+    MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
+)
+from mcdc.object_.base import MCDCObject
+from mcdc.print_ import print_1d_array, print_error
+
+_ENERGY_REPRESENTATIONS = {
+    "midpoint": MULTIGROUP_NEUTRON_ENERGY_MIDPOINT,
+    "log_midpoint": MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG,
+    "uniform": MULTIGROUP_NEUTRON_ENERGY_UNIFORM,
+    "log_uniform": MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
+}
+_LOG_ENERGY_REPRESENTATIONS = {
+    MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG,
+    MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
+}
+
+
+class MGXS(MCDCObject):
+    """Store multigroup cross sections for one particle species.
+
+    ``MGXS`` is particle agnostic. It stores groupwise interaction data; the
+    field through which a material references it determines the transported
+    particle species.
+
+    Parameters
+    ----------
+    capture : array_like of float, optional
+        Capture cross section for each incoming energy group, with shape
+        ``(G,)``.
+    scatter : array_like of float, optional
+        Scattering-production matrix with shape ``(G, G)``, indexed as
+        ``scatter[g_out, g_in]``. Column sums define the scattering cross
+        section for each incoming group. Columns are normalized internally to
+        form the scattering spectrum.
+    fission : array_like of float, optional
+        Fission cross section for each incoming energy group, with shape
+        ``(G,)``. Supplying fission requires at least one of ``nu_p`` or
+        ``nu_d``.
+    nu_s : array_like of float, optional
+        Mean number of particles produced per scattering event in each
+        incoming group, with shape ``(G,)``. Defaults to one.
+    nu_p : array_like of float, optional
+        Mean prompt-fission yield for each incoming group, with shape
+        ``(G,)``.
+    nu_d : array_like of float, optional
+        Mean delayed-fission yield with shape ``(J, G)``, indexed as
+        ``nu_d[j, g_in]``. Its first dimension determines the number ``J`` of
+        delayed precursor groups.
+    chi_p : array_like of float, optional
+        Prompt-fission spectrum. Shape ``(G,)`` applies one outgoing spectrum
+        to every incoming group. Shape ``(G, G)`` is indexed as
+        ``chi_p[g_out, g_in]``. Required when ``nu_p`` is supplied and
+        ``G > 1``.
+    chi_d : array_like of float, optional
+        Delayed-fission spectrum with shape ``(G, J)``, indexed as
+        ``chi_d[g_out, j]``. Required when ``nu_d`` is supplied and ``G > 1``.
+    speed : array_like of float, optional
+        Particle speed in each energy group, with shape ``(G,)``. Defaults to
+        one.
+    decay_rate : array_like of float, optional
+        Decay constant for each delayed precursor group, with shape ``(J,)``.
+        Defaults to infinity.
+    energy_grid : array_like of float, optional
+        Strictly increasing energy-group boundaries with shape ``(G + 1,)``.
+        Group ``g`` spans ``energy_grid[g] <= E < energy_grid[g + 1]``. The
+        array may be omitted before compilation when a shared grid will be
+        supplied.
+    energy_representation : str or int, optional
+        Policy used to reconstruct continuous energy from a group. Midpoint
+        policies select the arithmetic or geometric midpoint; uniform policies
+        sample uniformly in energy or log-energy. The default is
+        ``"log_midpoint"``. Logarithmic policies require positive boundaries.
+        The corresponding ``MULTIGROUP_NEUTRON_ENERGY_*`` integer constants
+        are also accepted.
+
+    Notes
+    -----
+    ``G`` is inferred from ``capture``, ``scatter``, or ``fission``. Calling
+    ``MGXS()`` without any cross sections creates the reserved zero-group
+    placeholder used by materials without multigroup data. Cross sections are
+    macroscopic and use inverse-length units.
+
+    Examples
+    --------
+    Construct one-group data with capture, scattering, and prompt fission:
+
+    >>> import mcdc
+    >>> import numpy as np
+    >>> mgxs = mcdc.MGXS(
+    ...     capture=np.array([1.0 / 3.0]),
+    ...     scatter=np.array([[1.0 / 3.0]]),
+    ...     fission=np.array([1.0 / 3.0]),
+    ...     nu_p=np.array([2.3]),
+    ...     energy_grid=np.array([1.0e-5, 20.0e6]),
+    ... )
+    """
+
+    # MC/DC framework metadata
+    label = "mgxs"
+
+    G: int
+    J: int
+
+    has_energy_grid: bool
+    energy_grid: Annotated[NDArray[float64], ("G+1",)]
+    energy_representation: int
+
+    speed: Annotated[NDArray[float64], ("G",)]
+    decay_rate: Annotated[NDArray[float64], ("J",)]
+
+    capture: Annotated[NDArray[float64], ("G",)]
+    scatter: Annotated[NDArray[float64], ("G",)]
+    fission: Annotated[NDArray[float64], ("G",)]
+    total: Annotated[NDArray[float64], ("G",)]
+
+    nu_s: Annotated[NDArray[float64], ("G",)]
+    nu_p: Annotated[NDArray[float64], ("G",)]
+    nu_d: Annotated[NDArray[float64], ("G", "J")]
+    nu_d_total: Annotated[NDArray[float64], ("G",)]
+    nu_f: Annotated[NDArray[float64], ("G",)]
+
+    chi_s: Annotated[NDArray[float64], ("G", "G")]
+    chi_p: Annotated[NDArray[float64], ("G", "G")]
+    chi_d: Annotated[NDArray[float64], ("J", "G")]
+
+    fissionable: bool
+
+    def __init__(
+        self,
+        capture: ArrayLike | NoneType = None,
+        scatter: ArrayLike | NoneType = None,
+        fission: ArrayLike | NoneType = None,
+        nu_s: ArrayLike | NoneType = None,
+        nu_p: ArrayLike | NoneType = None,
+        nu_d: ArrayLike | NoneType = None,
+        chi_p: ArrayLike | NoneType = None,
+        chi_d: ArrayLike | NoneType = None,
+        speed: ArrayLike | NoneType = None,
+        decay_rate: ArrayLike | NoneType = None,
+        energy_grid: ArrayLike | NoneType = None,
+        energy_representation: str | int = "log_midpoint",
+    ) -> None:
+        super().__init__()
+
+        # Convert user inputs to the runtime array representation
+        capture = _as_array("capture", capture)
+        scatter = _as_array("scatter", scatter)
+        fission = _as_array("fission", fission)
+        nu_s = _as_array("nu_s", nu_s)
+        nu_p = _as_array("nu_p", nu_p)
+        nu_d = _as_array("nu_d", nu_d)
+        chi_p = _as_array("chi_p", chi_p)
+        chi_d = _as_array("chi_d", chi_d)
+        speed = _as_array("speed", speed)
+        decay_rate = _as_array("decay_rate", decay_rate)
+        energy_grid = _as_array("energy_grid", energy_grid)
+
+        # Infer dimensions from the defining cross sections and delayed yields
+        self.G = _infer_group_count(capture, scatter, fission)
+        self.J = _infer_delayed_group_count(nu_d, self.G)
+
+        # Validate all user-facing array shapes before deriving stored data
+        _validate_shape("capture", capture, (self.G,))
+        _validate_shape("scatter", scatter, (self.G, self.G))
+        _validate_shape("fission", fission, (self.G,))
+        _validate_shape("nu_s", nu_s, (self.G,))
+        _validate_shape("nu_p", nu_p, (self.G,))
+        _validate_shape("nu_d", nu_d, (self.J, self.G))
+        _validate_prompt_spectrum_shape(chi_p, self.G)
+        _validate_shape("chi_d", chi_d, (self.G, self.J))
+        _validate_shape("speed", speed, (self.G,))
+        _validate_shape("decay_rate", decay_rate, (self.J,))
+        _validate_shape("energy_grid", energy_grid, (self.G + 1,))
+
+        # Reject values that cannot represent physical groupwise data
+        for name, array in (
+            ("capture", capture),
+            ("scatter", scatter),
+            ("fission", fission),
+            ("nu_s", nu_s),
+            ("nu_p", nu_p),
+            ("nu_d", nu_d),
+            ("chi_p", chi_p),
+            ("chi_d", chi_d),
+        ):
+            _validate_nonnegative(name, array)
+        _validate_positive("speed", speed)
+        _validate_decay_rate(decay_rate)
+
+        # Validate relationships between fission yields and spectra
+        if fission is not None and nu_p is None and nu_d is None:
+            print_error("Fission MGXS requires nu_p or nu_d.")
+        if fission is None and (nu_p is not None or nu_d is not None):
+            print_error("MGXS fission yields require fission cross sections.")
+        if chi_p is not None and nu_p is None:
+            print_error("MGXS chi_p requires nu_p.")
+        if chi_d is not None and nu_d is None:
+            print_error("MGXS chi_d requires nu_d.")
+        if decay_rate is not None and nu_d is None:
+            print_error("MGXS decay_rate requires nu_d.")
+
+        # Resolve the energy grid and continuous-energy reconstruction policy
+        self.energy_representation = _resolve_energy_representation(
+            energy_representation
+        )
+        self.has_energy_grid = energy_grid is not None
+        if energy_grid is None:
+            self.energy_grid = np.zeros(self.G + 1, dtype=float64)
+        else:
+            if not np.all(np.isfinite(energy_grid)):
+                print_error("MGXS energy grid entries must be finite.")
+            if np.any(np.diff(energy_grid) <= 0.0):
+                print_error("MGXS energy grid must be strictly increasing.")
+            if (
+                self.energy_representation in _LOG_ENERGY_REPRESENTATIONS
+                and energy_grid[0] <= 0.0
+            ):
+                print_error(
+                    "MGXS logarithmic energy representation requires positive "
+                    "energy boundaries."
+                )
+            self.energy_grid = energy_grid
+
+        # Apply transport defaults for group speed and precursor decay
+        self.speed = np.ones(self.G, dtype=float64) if speed is None else speed
+        self.decay_rate = (
+            np.full(self.J, np.inf, dtype=float64) if decay_rate is None else decay_rate
+        )
+
+        # Build cross sections and the normalized scattering spectrum
+        self.capture = np.zeros(self.G, dtype=float64) if capture is None else capture
+        self.chi_s = np.zeros((self.G, self.G), dtype=float64)
+        if scatter is None:
+            self.scatter = np.zeros(self.G, dtype=float64)
+        else:
+            self.scatter = np.sum(scatter, axis=0)
+            self.chi_s = np.swapaxes(scatter, 0, 1).copy()
+            _normalize_rows(self.chi_s, self.scatter > 0.0, "scatter")
+
+        self.fissionable = fission is not None
+        self.fission = np.zeros(self.G, dtype=float64) if fission is None else fission
+        self.total = self.capture + self.scatter + self.fission
+
+        # Build scattering and fission yields
+        self.nu_s = np.ones(self.G, dtype=float64) if nu_s is None else nu_s
+        self.nu_p = np.zeros(self.G, dtype=float64) if nu_p is None else nu_p
+        if nu_d is None:
+            self.nu_d = np.zeros((self.G, self.J), dtype=float64)
+        else:
+            self.nu_d = np.swapaxes(nu_d, 0, 1).copy()
+        self.nu_d_total = np.sum(self.nu_d, axis=1)
+        self.nu_f = self.nu_p + self.nu_d_total
+
+        # Build normalized prompt- and delayed-fission spectra
+        self.chi_p = np.zeros((self.G, self.G), dtype=float64)
+        if nu_p is not None:
+            if self.G == 1:
+                self.chi_p[:] = 1.0
+            elif chi_p is None:
+                print_error("MGXS with nu_p and G > 1 requires chi_p.")
+            else:
+                if chi_p.ndim == 1:
+                    chi_p = np.tile(chi_p[:, np.newaxis], (1, self.G))
+                self.chi_p = np.swapaxes(chi_p, 0, 1).copy()
+                _normalize_rows(self.chi_p, self.nu_p > 0.0, "chi_p")
+
+        self.chi_d = np.zeros((self.J, self.G), dtype=float64)
+        if nu_d is not None:
+            if self.G == 1:
+                self.chi_d[:] = 1.0
+            elif chi_d is None:
+                print_error("MGXS with nu_d and G > 1 requires chi_d.")
+            else:
+                self.chi_d = np.swapaxes(chi_d, 0, 1).copy()
+                active_delayed_groups = np.any(nu_d > 0.0, axis=1)
+                _normalize_rows(self.chi_d, active_delayed_groups, "chi_d")
+
+    def __repr__(self) -> str:
+        text = super().__repr__()
+        text += f"  - G: {self.G}\n"
+        text += f"  - J: {self.J}\n"
+        if self.has_energy_grid:
+            text += f"  - Energy grid {print_1d_array(self.energy_grid)}\n"
+        text += f"  - Sigma_c {print_1d_array(self.capture)}\n"
+        text += f"  - Sigma_s {print_1d_array(self.scatter)}\n"
+        text += f"  - Sigma_f {print_1d_array(self.fission)}\n"
+        text += f"  - nu_s {print_1d_array(self.nu_s)}\n"
+        text += f"  - nu_p {print_1d_array(self.nu_p)}\n"
+        text += f"  - nu_d {print_1d_array(self.nu_d.flatten())}\n"
+        text += f"  - chi_s {print_1d_array(self.chi_s.flatten())}\n"
+        text += f"  - chi_p {print_1d_array(self.chi_p.flatten())}\n"
+        text += f"  - chi_d {print_1d_array(self.chi_d.flatten())}\n"
+        text += f"  - speed {print_1d_array(self.speed)}\n"
+        text += f"  - decay rate {print_1d_array(self.decay_rate)}\n"
+        return text
+
+
+def _as_array(name, value):
+    """Convert an optional user value to a float64 array."""
+    if value is None:
+        return None
+    try:
+        return np.asarray(value, dtype=float64)
+    except (TypeError, ValueError):
+        print_error(f"MGXS {name} must be numeric array-like data.")
+
+
+def _infer_group_count(capture, scatter, fission) -> int:
+    """Infer the energy-group count from the first supplied cross section."""
+    defining = capture if capture is not None else scatter
+    defining = fission if defining is None else defining
+    if defining is None:
+        return 0
+    if defining.ndim == 0:
+        print_error("MGXS cross sections must be arrays with an energy-group axis.")
+    if defining.shape[0] == 0:
+        print_error("MGXS cross sections must define at least one energy group.")
+    return defining.shape[0]
+
+
+def _infer_delayed_group_count(nu_d, G: int) -> int:
+    """Infer the delayed-group count from delayed-fission yields."""
+    if nu_d is None:
+        return 0
+    if nu_d.ndim != 2:
+        print_error(f"MGXS nu_d must have shape (J, G); got {nu_d.shape}.")
+    if nu_d.shape[1] != G:
+        print_error(f"MGXS nu_d must have shape (J, G) with G = {G}; got {nu_d.shape}.")
+    return nu_d.shape[0]
+
+
+def _validate_shape(name, array, expected) -> None:
+    """Require an optional array to have its declared MGXS shape."""
+    if array is not None and array.shape != expected:
+        print_error(f"MGXS {name} must have shape {expected}; got {array.shape}.")
+
+
+def _validate_prompt_spectrum_shape(chi_p, G: int) -> None:
+    """Accept either a shared vector or an incoming-group spectrum matrix."""
+    if chi_p is None:
+        return
+    if chi_p.shape not in ((G,), (G, G)):
+        print_error(
+            f"MGXS chi_p must have shape ({G},) or ({G}, {G}); got {chi_p.shape}."
+        )
+
+
+def _validate_nonnegative(name, array) -> None:
+    """Reject negative or non-finite physical data."""
+    if array is None:
+        return
+    if not np.all(np.isfinite(array)) or np.any(array < 0.0):
+        print_error(f"MGXS {name} entries must be finite and nonnegative.")
+
+
+def _validate_positive(name, array) -> None:
+    """Reject nonpositive or non-finite physical data."""
+    if array is None:
+        return
+    if not np.all(np.isfinite(array)) or np.any(array <= 0.0):
+        print_error(f"MGXS {name} entries must be finite and positive.")
+
+
+def _validate_decay_rate(array) -> None:
+    """Allow the infinite default sentinel while rejecting invalid rates."""
+    if array is None:
+        return
+    if np.any(np.isnan(array)) or np.any(array < 0.0):
+        print_error("MGXS decay_rate entries must be nonnegative.")
+
+
+def _resolve_energy_representation(policy) -> int:
+    """Resolve a public reconstruction policy name or integer code."""
+    if isinstance(policy, str):
+        if policy not in _ENERGY_REPRESENTATIONS:
+            expected = ", ".join(_ENERGY_REPRESENTATIONS)
+            print_error(
+                f"Unknown MGXS energy representation {policy!r}. "
+                f"Expected one of: {expected}."
+            )
+        return _ENERGY_REPRESENTATIONS[policy]
+
+    if (
+        not isinstance(policy, (bool, np.bool_))
+        and isinstance(policy, (int, np.integer))
+        and policy in _ENERGY_REPRESENTATIONS.values()
+    ):
+        return int(policy)
+
+    print_error(f"Unknown MGXS energy representation {policy!r}.")
+
+
+def _normalize_rows(array, required, name) -> None:
+    """Normalize spectra over outgoing groups and validate active rows."""
+    for index in range(len(array)):
+        norm = np.sum(array[index])
+        if required[index] and norm <= 0.0:
+            print_error(f"MGXS {name} spectrum {index} must have positive mass.")
+        if norm > 0.0:
+            array[index] /= norm
diff --git a/test/unit/test_mgxs.py b/test/unit/test_mgxs.py
new file mode 100644
index 000000000..8dd2d9d01
--- /dev/null
+++ b/test/unit/test_mgxs.py
@@ -0,0 +1,271 @@
+import numpy as np
+import pytest
+
+import mcdc
+from mcdc.constant import (
+    MULTIGROUP_NEUTRON_ENERGY_MIDPOINT,
+    MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG,
+    MULTIGROUP_NEUTRON_ENERGY_UNIFORM,
+    MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
+)
+from mcdc.object_.base import MCDCObject, MCDCPolymorphic
+from mcdc.object_.mgxs import MGXS
+
+
+def test_mgxs_is_public():
+    assert mcdc.MGXS is MGXS
+    assert issubclass(MGXS, MCDCObject)
+    assert not issubclass(MGXS, MCDCPolymorphic)
+
+
+def test_zero_group_placeholder():
+    mgxs = MGXS()
+
+    assert mgxs.G == 0
+    assert mgxs.J == 0
+    assert not mgxs.fissionable
+    assert not mgxs.has_energy_grid
+    assert mgxs.energy_representation == MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG
+
+    np.testing.assert_array_equal(mgxs.energy_grid, [0.0])
+    np.testing.assert_array_equal(mgxs.speed, [])
+    np.testing.assert_array_equal(mgxs.decay_rate, [])
+    np.testing.assert_array_equal(mgxs.capture, [])
+    np.testing.assert_array_equal(mgxs.scatter, [])
+    np.testing.assert_array_equal(mgxs.fission, [])
+    np.testing.assert_array_equal(mgxs.total, [])
+    np.testing.assert_array_equal(mgxs.nu_s, [])
+    np.testing.assert_array_equal(mgxs.nu_p, [])
+    np.testing.assert_array_equal(mgxs.nu_d, np.empty((0, 0)))
+    np.testing.assert_array_equal(mgxs.nu_d_total, [])
+    np.testing.assert_array_equal(mgxs.nu_f, [])
+    np.testing.assert_array_equal(mgxs.chi_s, np.empty((0, 0)))
+    np.testing.assert_array_equal(mgxs.chi_p, np.empty((0, 0)))
+    np.testing.assert_array_equal(mgxs.chi_d, np.empty((0, 0)))
+
+
+def test_capture_only_defaults():
+    mgxs = MGXS(capture=[0.1, 0.2])
+
+    assert mgxs.G == 2
+    assert mgxs.J == 0
+    assert not mgxs.fissionable
+    assert not mgxs.has_energy_grid
+
+    np.testing.assert_array_equal(mgxs.energy_grid, [0.0, 0.0, 0.0])
+    np.testing.assert_array_equal(mgxs.speed, [1.0, 1.0])
+    np.testing.assert_array_equal(mgxs.capture, [0.1, 0.2])
+    np.testing.assert_array_equal(mgxs.scatter, [0.0, 0.0])
+    np.testing.assert_array_equal(mgxs.fission, [0.0, 0.0])
+    np.testing.assert_array_equal(mgxs.total, [0.1, 0.2])
+    np.testing.assert_array_equal(mgxs.nu_s, [1.0, 1.0])
+    np.testing.assert_array_equal(mgxs.nu_f, [0.0, 0.0])
+    assert mgxs.capture.dtype == np.float64
+
+
+def test_scatter_matrix_is_reoriented_and_normalized():
+    mgxs = MGXS(
+        scatter=[
+            [1.0, 2.0],
+            [3.0, 0.0],
+        ],
+        nu_s=[1.1, 1.2],
+    )
+
+    np.testing.assert_array_equal(mgxs.scatter, [4.0, 2.0])
+    np.testing.assert_allclose(
+        mgxs.chi_s,
+        [
+            [0.25, 0.75],
+            [1.0, 0.0],
+        ],
+    )
+    np.testing.assert_array_equal(mgxs.total, [4.0, 2.0])
+    np.testing.assert_array_equal(mgxs.nu_s, [1.1, 1.2])
+
+
+def test_prompt_fission_spectrum_is_shared_and_normalized():
+    mgxs = MGXS(
+        fission=[0.2, 0.3],
+        nu_p=[2.4, 2.5],
+        chi_p=[1.0, 3.0],
+    )
+
+    assert mgxs.fissionable
+    np.testing.assert_array_equal(mgxs.nu_f, [2.4, 2.5])
+    np.testing.assert_allclose(
+        mgxs.chi_p,
+        [
+            [0.25, 0.75],
+            [0.25, 0.75],
+        ],
+    )
+
+
+def test_delayed_fission_data_is_reoriented_and_normalized():
+    mgxs = MGXS(
+        fission=[0.2, 0.3],
+        nu_d=[
+            [0.1, 0.2],
+            [0.3, 0.4],
+        ],
+        chi_d=[
+            [1.0, 3.0],
+            [3.0, 1.0],
+        ],
+        decay_rate=[0.01, 0.02],
+    )
+
+    assert mgxs.J == 2
+    np.testing.assert_array_equal(
+        mgxs.nu_d,
+        [
+            [0.1, 0.3],
+            [0.2, 0.4],
+        ],
+    )
+    np.testing.assert_allclose(mgxs.nu_d_total, [0.4, 0.6])
+    np.testing.assert_allclose(mgxs.nu_f, [0.4, 0.6])
+    np.testing.assert_allclose(
+        mgxs.chi_d,
+        [
+            [0.25, 0.75],
+            [0.75, 0.25],
+        ],
+    )
+    np.testing.assert_array_equal(mgxs.decay_rate, [0.01, 0.02])
+
+
+def test_one_group_fission_spectra_default_to_one():
+    mgxs = MGXS(
+        fission=[0.2],
+        nu_p=[2.4],
+        nu_d=[[0.1], [0.2]],
+    )
+
+    np.testing.assert_array_equal(mgxs.chi_p, [[1.0]])
+    np.testing.assert_array_equal(mgxs.chi_d, [[1.0], [1.0]])
+    np.testing.assert_array_equal(mgxs.nu_f, [2.7])
+    np.testing.assert_array_equal(mgxs.decay_rate, [np.inf, np.inf])
+
+
+@pytest.mark.parametrize(
+    "policy, expected",
+    [
+        ("midpoint", MULTIGROUP_NEUTRON_ENERGY_MIDPOINT),
+        ("log_midpoint", MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG),
+        ("uniform", MULTIGROUP_NEUTRON_ENERGY_UNIFORM),
+        ("log_uniform", MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG),
+        (MULTIGROUP_NEUTRON_ENERGY_MIDPOINT, MULTIGROUP_NEUTRON_ENERGY_MIDPOINT),
+        (
+            np.int64(MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG),
+            MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
+        ),
+    ],
+)
+def test_energy_grid_and_representation(policy, expected):
+    mgxs = MGXS(
+        capture=[0.1, 0.2],
+        energy_grid=[1.0e-5, 1.0, 20.0e6],
+        energy_representation=policy,
+    )
+
+    assert mgxs.has_energy_grid
+    assert mgxs.energy_representation == expected
+    np.testing.assert_array_equal(mgxs.energy_grid, [1.0e-5, 1.0, 20.0e6])
+
+
+@pytest.mark.parametrize(
+    "kwargs, expected_message",
+    [
+        (
+            {"capture": [0.1, 0.2], "energy_grid": [1.0, 2.0]},
+            "energy_grid must have shape (3,)",
+        ),
+        (
+            {"capture": [0.1, 0.2], "energy_grid": [1.0, 2.0, 2.0]},
+            "energy grid must be strictly increasing",
+        ),
+        (
+            {"capture": [0.1], "energy_grid": [0.0, 1.0]},
+            "logarithmic energy representation requires positive",
+        ),
+        (
+            {"capture": [0.1], "energy_representation": "average"},
+            "Unknown MGXS energy representation",
+        ),
+        (
+            {"fission": [0.1]},
+            "Fission MGXS requires nu_p or nu_d",
+        ),
+        (
+            {"nu_p": [2.4]},
+            "nu_p must have shape (0,)",
+        ),
+        (
+            {"fission": [0.1, 0.2], "nu_p": [2.4, 2.5]},
+            "MGXS with nu_p and G > 1 requires chi_p",
+        ),
+        (
+            {"fission": [0.1, 0.2], "nu_d": [[0.1, 0.2]]},
+            "MGXS with nu_d and G > 1 requires chi_d",
+        ),
+        (
+            {"capture": [-0.1]},
+            "capture entries must be finite and nonnegative",
+        ),
+        (
+            {"capture": [0.1], "speed": [0.0]},
+            "speed entries must be finite and positive",
+        ),
+        (
+            {
+                "fission": [0.1, 0.2],
+                "nu_p": [2.4, 2.5],
+                "chi_p": [0.0, 0.0],
+            },
+            "chi_p spectrum 0 must have positive mass",
+        ),
+    ],
+)
+def test_invalid_inputs_are_rejected(kwargs, expected_message, capsys):
+    with pytest.raises(SystemExit):
+        MGXS(**kwargs)
+
+    assert expected_message in capsys.readouterr().out
+
+
+@pytest.mark.parametrize(
+    "kwargs, expected_message",
+    [
+        (
+            {"capture": [0.1, 0.2], "fission": [0.3], "nu_p": [2.4, 2.5]},
+            "fission must have shape (2,)",
+        ),
+        (
+            {"scatter": [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]]},
+            "scatter must have shape (2, 2)",
+        ),
+        (
+            {"capture": [0.1, 0.2], "speed": [1.0]},
+            "speed must have shape (2,)",
+        ),
+        (
+            {
+                "fission": [0.1, 0.2],
+                "nu_p": [2.4],
+                "chi_p": [0.5, 0.5],
+            },
+            "nu_p must have shape (2,)",
+        ),
+        (
+            {"fission": [0.1, 0.2], "nu_d": [[0.1]]},
+            "nu_d must have shape (J, G) with G = 2",
+        ),
+    ],
+)
+def test_inconsistent_shapes_are_rejected(kwargs, expected_message, capsys):
+    with pytest.raises(SystemExit):
+        MGXS(**kwargs)
+
+    assert expected_message in capsys.readouterr().out

From 23deff52f90fa9536da49f4bca908a0b99f5eb67 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 13:16:57 +0700
Subject: [PATCH 110/202] MGXS registration and packing

---
 mcdc/code_factory/numba_layers_generator.py  |  2 ++
 mcdc/code_factory/python_objects_compiler.py |  7 +++-
 mcdc/numba_types.py                          |  2 ++
 mcdc/object_/simulation.py                   |  3 ++
 test/unit/test_mgxs.py                       | 34 ++++++++++++++++++++
 test/unit/test_object_compilation.py         | 13 ++++++++
 6 files changed, 60 insertions(+), 1 deletion(-)

diff --git a/mcdc/code_factory/numba_layers_generator.py b/mcdc/code_factory/numba_layers_generator.py
index de60f263f..a87a7449b 100644
--- a/mcdc/code_factory/numba_layers_generator.py
+++ b/mcdc/code_factory/numba_layers_generator.py
@@ -1315,6 +1315,7 @@ def plural_to_singular(word: str) -> str:
         "matrices": "matrix",
         "criteria": "criterion",
         "data": "data",  # invariant
+        "mgxs": "mgxs",  # invariant
         "spectra": "spectrum",
     }
 
@@ -1356,6 +1357,7 @@ def singular_to_plural(word: str) -> str:
         "matrix": "matrices",
         "criterion": "criteria",
         "data": "data",  # invariant
+        "mgxs": "mgxs",  # invariant
         "spectrum": "spectra",
     }
 
diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index 52703f22a..ec033f68a 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -5,6 +5,7 @@
 from mcdc.object_.electron_reaction import ElectronReactionBase
 from mcdc.object_.element import Element
 from mcdc.object_.material import MaterialBase
+from mcdc.object_.mgxs import MGXS
 from mcdc.object_.mesh import MeshBase
 from mcdc.object_.neutron_reaction import NeutronReactionBase
 from mcdc.object_.nuclide import Nuclide
@@ -36,13 +37,15 @@ def compile_simulation(simulation: Simulation):
     simulation.sources = []
     simulation.tallies = []
 
-    # Reserved ojects
+    # Reserved objects
     none_data = DataNone()
     none_distribution = DistributionNone()
+    none_mgxs = MGXS()
 
     # Compile reserved objects
     none_data._compile_into_simulation(simulation)
     none_distribution._compile_into_simulation(simulation)
+    none_mgxs._compile_into_simulation(simulation)
 
     # Compile model
     root_universe = simulation.root_universe
@@ -80,6 +83,8 @@ def register_object(object_: MCDCObject, simulation: Simulation) -> bool:
         object_list = simulation.lattices
     elif isinstance(object_, MaterialBase):
         object_list = simulation.materials
+    elif isinstance(object_, MGXS):
+        object_list = simulation.mgxs
     elif isinstance(object_, MeshBase):
         object_list = simulation.meshes
     elif isinstance(object_, Element):
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index 7f0e8b9a5..cf019c1ff 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -847,6 +847,8 @@ def set_simulation(N: dict):
         ('N_native_material', int64),
         ('multigroup_materials', multigroup_material, (N['multigroup_material'])),
         ('N_multigroup_material', int64),
+        ('mgxs', mgxs, (N['mgxs'])),
+        ('N_mgxs', int64),
         ('sources', source, (N['source'])),
         ('N_source', int64),
         ('surfaces', surface, (N['surface'])),
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 669477bc3..c2f051dce 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -6,6 +6,7 @@
     from mcdc.object_.element import Element
     from mcdc.object_.electron_reaction import ElectronReactionBase
     from mcdc.object_.material import MaterialBase
+    from mcdc.object_.mgxs import MGXS
     from mcdc.object_.nuclide import Nuclide
     from mcdc.object_.neutron_reaction import NeutronReactionBase
     from mcdc.object_.source import Source
@@ -115,6 +116,7 @@ class Simulation(MCDCBase):
     nuclides: list[Nuclide]
     elements: list[Element]
     materials: list[MaterialBase]
+    mgxs: list[MGXS]
     sources: list[Source]
 
     # Geometry
@@ -293,6 +295,7 @@ def _reset_model(self) -> None:
         self.nuclides = []
         self.elements = []
         self.materials = []
+        self.mgxs = []
 
         # Geometry
         self.surfaces = []
diff --git a/test/unit/test_mgxs.py b/test/unit/test_mgxs.py
index 8dd2d9d01..58044ab76 100644
--- a/test/unit/test_mgxs.py
+++ b/test/unit/test_mgxs.py
@@ -8,6 +8,7 @@
     MULTIGROUP_NEUTRON_ENERGY_UNIFORM,
     MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
 )
+from mcdc.mcdc_get import mgxs as get_mgxs
 from mcdc.object_.base import MCDCObject, MCDCPolymorphic
 from mcdc.object_.mgxs import MGXS
 
@@ -149,6 +150,39 @@ def test_one_group_fission_spectra_default_to_one():
     np.testing.assert_array_equal(mgxs.decay_rate, [np.inf, np.inf])
 
 
+def test_standalone_mgxs_registration_and_packing(prepare_simulation):
+    mgxs = MGXS(
+        capture=[0.1, 0.2],
+        scatter=[[1.0, 2.0], [3.0, 0.0]],
+        energy_grid=[1.0e-5, 1.0, 20.0e6],
+    )
+
+    simulation_container, data = prepare_simulation(objects=[mgxs])
+    simulation = simulation_container[0]
+    reserved = simulation["mgxs"][0]
+    packed = simulation["mgxs"][1]
+
+    assert simulation["N_mgxs"] == 2
+    assert reserved["ID"] == 0
+    assert reserved["G"] == 0
+    assert mgxs.ID == 1
+    assert packed["ID"] == 1
+    assert packed["G"] == 2
+    assert packed["has_energy_grid"]
+
+    np.testing.assert_array_equal(get_mgxs.energy_grid_all(reserved, data), [0.0])
+    np.testing.assert_array_equal(
+        get_mgxs.energy_grid_all(packed, data),
+        [1.0e-5, 1.0, 20.0e6],
+    )
+    np.testing.assert_array_equal(get_mgxs.capture_all(packed, data), [0.1, 0.2])
+    np.testing.assert_array_equal(get_mgxs.scatter_all(packed, data), [4.0, 2.0])
+    np.testing.assert_allclose(
+        get_mgxs.chi_s_vector(0, packed, data),
+        [0.25, 0.75],
+    )
+
+
 @pytest.mark.parametrize(
     "policy, expected",
     [
diff --git a/test/unit/test_object_compilation.py b/test/unit/test_object_compilation.py
index b36f6666b..d5ff3b543 100644
--- a/test/unit/test_object_compilation.py
+++ b/test/unit/test_object_compilation.py
@@ -4,6 +4,7 @@
 
 from mcdc.object_.base import MCDCBase, MCDCObject
 from mcdc.object_.data import DataPolynomial
+from mcdc.object_.mgxs import MGXS
 from mcdc.object_.nuclide import Nuclide
 from mcdc.object_.universe import Universe
 
@@ -29,6 +30,18 @@ def __init__(self):
         self.member = None
 
 
+def test_simulation_reserves_zero_group_mgxs_as_id_zero():
+    simulation = mcdc.Simulation()
+
+    simulation.compile()
+
+    assert len(simulation.mgxs) == 1
+    assert isinstance(simulation.mgxs[0], MGXS)
+    assert simulation.mgxs[0].ID == 0
+    assert simulation.mgxs[0].G == 0
+    assert simulation.mgxs[0].compile_ID == simulation.compile_ID
+
+
 def test_mcdc_object_compiles_object_members_and_lists():
     child = DataPolynomial(np.array([1.0]))
     children = [

From ffa1f0f04710bc4e795768163e481da7ee15dd1a Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 14:50:26 +0700
Subject: [PATCH 111/202] unified material

---
 mcdc/__init__.py                             |   4 +-
 mcdc/code_factory/python_objects_compiler.py |  14 +-
 mcdc/constant.py                             |  17 +-
 mcdc/mcdc_get/__init__.py                    |   6 +-
 mcdc/mcdc_get/material.py                    | 117 ++++
 mcdc/mcdc_get/mgxs.py                        | 414 --------------
 mcdc/mcdc_get/multigroup_material.py         | 385 -------------
 mcdc/mcdc_get/native_material.py             | 120 -----
 mcdc/mcdc_get/neutron_multigroup.py          | 414 ++++++++++++++
 mcdc/mcdc_set/__init__.py                    |   6 +-
 mcdc/mcdc_set/material.py                    | 116 ++++
 mcdc/mcdc_set/mgxs.py                        | 414 --------------
 mcdc/mcdc_set/multigroup_material.py         | 385 -------------
 mcdc/mcdc_set/native_material.py             | 119 ----
 mcdc/mcdc_set/neutron_multigroup.py          | 414 ++++++++++++++
 mcdc/numba_types.py                          | 137 ++---
 mcdc/object_/cell.py                         |  14 +-
 mcdc/object_/material.py                     | 537 +++++--------------
 mcdc/object_/simulation.py                   |  39 +-
 mcdc/object_/tally.py                        |   6 +-
 mcdc/object_/{mgxs.py => transport_model.py} | 153 ++++--
 mcdc/object_/universe.py                     |  14 +-
 22 files changed, 1415 insertions(+), 2430 deletions(-)
 delete mode 100644 mcdc/mcdc_get/mgxs.py
 delete mode 100644 mcdc/mcdc_get/multigroup_material.py
 delete mode 100644 mcdc/mcdc_get/native_material.py
 create mode 100644 mcdc/mcdc_get/neutron_multigroup.py
 delete mode 100644 mcdc/mcdc_set/mgxs.py
 delete mode 100644 mcdc/mcdc_set/multigroup_material.py
 delete mode 100644 mcdc/mcdc_set/native_material.py
 create mode 100644 mcdc/mcdc_set/neutron_multigroup.py
 rename mcdc/object_/{mgxs.py => transport_model.py} (73%)

diff --git a/mcdc/__init__.py b/mcdc/__init__.py
index 2f82cd348..4db32c8b2 100644
--- a/mcdc/__init__.py
+++ b/mcdc/__init__.py
@@ -10,8 +10,8 @@
 # ======================================================================================
 
 from mcdc.object_.cell import Cell, Universe, Lattice
-from mcdc.object_.material import Material, MaterialMG
-from mcdc.object_.mgxs import MGXS
+from mcdc.object_.material import Material
+from mcdc.object_.transport_model import NeutronMultigroup
 from mcdc.object_.mesh import MeshUniform, MeshStructured
 from mcdc.object_.simulation import Simulation
 from mcdc.object_.source import Source
diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index ec033f68a..82b53d789 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -4,8 +4,8 @@
 from mcdc.object_.distribution import DistributionBase, DistributionNone
 from mcdc.object_.electron_reaction import ElectronReactionBase
 from mcdc.object_.element import Element
-from mcdc.object_.material import MaterialBase
-from mcdc.object_.mgxs import MGXS
+from mcdc.object_.material import Material
+from mcdc.object_.transport_model import NeutronMultigroup
 from mcdc.object_.mesh import MeshBase
 from mcdc.object_.neutron_reaction import NeutronReactionBase
 from mcdc.object_.nuclide import Nuclide
@@ -40,12 +40,12 @@ def compile_simulation(simulation: Simulation):
     # Reserved objects
     none_data = DataNone()
     none_distribution = DistributionNone()
-    none_mgxs = MGXS()
+    none_neutron_multigroup = NeutronMultigroup()
 
     # Compile reserved objects
     none_data._compile_into_simulation(simulation)
     none_distribution._compile_into_simulation(simulation)
-    none_mgxs._compile_into_simulation(simulation)
+    none_neutron_multigroup._compile_into_simulation(simulation)
 
     # Compile model
     root_universe = simulation.root_universe
@@ -81,10 +81,10 @@ def register_object(object_: MCDCObject, simulation: Simulation) -> bool:
         object_list = simulation.distributions
     elif isinstance(object_, Lattice):
         object_list = simulation.lattices
-    elif isinstance(object_, MaterialBase):
+    elif isinstance(object_, Material):
         object_list = simulation.materials
-    elif isinstance(object_, MGXS):
-        object_list = simulation.mgxs
+    elif isinstance(object_, NeutronMultigroup):
+        object_list = simulation.neutron_multigroup
     elif isinstance(object_, MeshBase):
         object_list = simulation.meshes
     elif isinstance(object_, Element):
diff --git a/mcdc/constant.py b/mcdc/constant.py
index 355035e0b..0235724ef 100644
--- a/mcdc/constant.py
+++ b/mcdc/constant.py
@@ -32,20 +32,15 @@
 PARTICLE_ELECTRON = 1
 PARTICLE_PROTON = 2
 
-# Material types
-# TODO: Remove these after Material no longer uses polymorphic type IDs.
-MATERIAL = 0
-MATERIAL_MG = 1
-
 # Neutron multigroup energy-grid organization
-MULTIGROUP_NEUTRON_GRID_SHARED = 0
-MULTIGROUP_NEUTRON_GRID_LOCAL = 1
+NEUTRON_MULTIGROUP_GRID_SHARED = 0
+NEUTRON_MULTIGROUP_GRID_LOCAL = 1
 
 # Neutron multigroup energy representation
-MULTIGROUP_NEUTRON_ENERGY_MIDPOINT = 0
-MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG = 1
-MULTIGROUP_NEUTRON_ENERGY_UNIFORM = 2
-MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG = 3
+NEUTRON_MULTIGROUP_ENERGY_MIDPOINT = 0
+NEUTRON_MULTIGROUP_ENERGY_MIDPOINT_LOG = 1
+NEUTRON_MULTIGROUP_ENERGY_UNIFORM = 2
+NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG = 3
 
 # Neutron reactions
 NEUTRON_REACTION_TOTAL = 0
diff --git a/mcdc/mcdc_get/__init__.py b/mcdc/mcdc_get/__init__.py
index 11888cbb5..af9a342e2 100644
--- a/mcdc/mcdc_get/__init__.py
+++ b/mcdc/mcdc_get/__init__.py
@@ -60,9 +60,7 @@
 
 import mcdc.mcdc_get.gpu_meta as gpu_meta
 
-import mcdc.mcdc_get.native_material as native_material
-
-import mcdc.mcdc_get.multigroup_material as multigroup_material
+import mcdc.mcdc_get.neutron_multigroup as neutron_multigroup
 
 import mcdc.mcdc_get.nuclide as nuclide
 
@@ -72,8 +70,6 @@
 
 import mcdc.mcdc_get.uniform_mesh as uniform_mesh
 
-import mcdc.mcdc_get.mgxs as mgxs
-
 import mcdc.mcdc_get.neutron_reaction as neutron_reaction
 
 import mcdc.mcdc_get.neutron_capture_reaction as neutron_capture_reaction
diff --git a/mcdc/mcdc_get/material.py b/mcdc/mcdc_get/material.py
index fdbf8e750..1c4539002 100644
--- a/mcdc/mcdc_get/material.py
+++ b/mcdc/mcdc_get/material.py
@@ -1,3 +1,120 @@
 # The following is automatically generated by code_factory.py
 
+from numpy import int64
 from numba import njit
+
+
+@njit
+def nuclide_IDs(index, material, data):
+    offset = material["nuclide_IDs_offset"]
+    return int64(data[offset + index])
+
+
+@njit
+def nuclide_IDs_all(material, data):
+    start = material["nuclide_IDs_offset"]
+    size = material["N_nuclide"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nuclide_IDs_last(material, data):
+    start = material["nuclide_IDs_offset"]
+    size = material["N_nuclide"]
+    end = start + size
+    return int64(data[end - 1])
+
+
+@njit
+def nuclide_IDs_chunk(start, length, material, data):
+    start += material["nuclide_IDs_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def element_IDs(index, material, data):
+    offset = material["element_IDs_offset"]
+    return int64(data[offset + index])
+
+
+@njit
+def element_IDs_all(material, data):
+    start = material["element_IDs_offset"]
+    size = material["N_element"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def element_IDs_last(material, data):
+    start = material["element_IDs_offset"]
+    size = material["N_element"]
+    end = start + size
+    return int64(data[end - 1])
+
+
+@njit
+def element_IDs_chunk(start, length, material, data):
+    start += material["element_IDs_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nuclide_densities(index, material, data):
+    offset = material["nuclide_densities_offset"]
+    return data[offset + index]
+
+
+@njit
+def nuclide_densities_all(material, data):
+    start = material["nuclide_densities_offset"]
+    size = material["nuclide_densities_length"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nuclide_densities_last(material, data):
+    start = material["nuclide_densities_offset"]
+    size = material["nuclide_densities_length"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nuclide_densities_chunk(start, length, material, data):
+    start += material["nuclide_densities_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def element_densities(index, material, data):
+    offset = material["element_densities_offset"]
+    return data[offset + index]
+
+
+@njit
+def element_densities_all(material, data):
+    start = material["element_densities_offset"]
+    size = material["element_densities_length"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def element_densities_last(material, data):
+    start = material["element_densities_offset"]
+    size = material["element_densities_length"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def element_densities_chunk(start, length, material, data):
+    start += material["element_densities_offset"]
+    end = start + length
+    return data[start:end]
diff --git a/mcdc/mcdc_get/mgxs.py b/mcdc/mcdc_get/mgxs.py
deleted file mode 100644
index 226090cfb..000000000
--- a/mcdc/mcdc_get/mgxs.py
+++ /dev/null
@@ -1,414 +0,0 @@
-# The following is automatically generated by code_factory.py
-
-from numba import njit
-
-
-@njit
-def energy_grid(index, mgxs, data):
-    offset = mgxs["energy_grid_offset"]
-    return data[offset + index]
-
-
-@njit
-def energy_grid_all(mgxs, data):
-    start = mgxs["energy_grid_offset"]
-    size = mgxs["G"] + 1
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def energy_grid_last(mgxs, data):
-    start = mgxs["energy_grid_offset"]
-    size = mgxs["G"] + 1
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def energy_grid_chunk(start, length, mgxs, data):
-    start += mgxs["energy_grid_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def speed(index, mgxs, data):
-    offset = mgxs["speed_offset"]
-    return data[offset + index]
-
-
-@njit
-def speed_all(mgxs, data):
-    start = mgxs["speed_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def speed_last(mgxs, data):
-    start = mgxs["speed_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def speed_chunk(start, length, mgxs, data):
-    start += mgxs["speed_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def decay_rate(index, mgxs, data):
-    offset = mgxs["decay_rate_offset"]
-    return data[offset + index]
-
-
-@njit
-def decay_rate_all(mgxs, data):
-    start = mgxs["decay_rate_offset"]
-    size = mgxs["J"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def decay_rate_last(mgxs, data):
-    start = mgxs["decay_rate_offset"]
-    size = mgxs["J"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def decay_rate_chunk(start, length, mgxs, data):
-    start += mgxs["decay_rate_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def capture(index, mgxs, data):
-    offset = mgxs["capture_offset"]
-    return data[offset + index]
-
-
-@njit
-def capture_all(mgxs, data):
-    start = mgxs["capture_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def capture_last(mgxs, data):
-    start = mgxs["capture_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def capture_chunk(start, length, mgxs, data):
-    start += mgxs["capture_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def scatter(index, mgxs, data):
-    offset = mgxs["scatter_offset"]
-    return data[offset + index]
-
-
-@njit
-def scatter_all(mgxs, data):
-    start = mgxs["scatter_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def scatter_last(mgxs, data):
-    start = mgxs["scatter_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def scatter_chunk(start, length, mgxs, data):
-    start += mgxs["scatter_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def fission(index, mgxs, data):
-    offset = mgxs["fission_offset"]
-    return data[offset + index]
-
-
-@njit
-def fission_all(mgxs, data):
-    start = mgxs["fission_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def fission_last(mgxs, data):
-    start = mgxs["fission_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def fission_chunk(start, length, mgxs, data):
-    start += mgxs["fission_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def total(index, mgxs, data):
-    offset = mgxs["total_offset"]
-    return data[offset + index]
-
-
-@njit
-def total_all(mgxs, data):
-    start = mgxs["total_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def total_last(mgxs, data):
-    start = mgxs["total_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def total_chunk(start, length, mgxs, data):
-    start += mgxs["total_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nu_s(index, mgxs, data):
-    offset = mgxs["nu_s_offset"]
-    return data[offset + index]
-
-
-@njit
-def nu_s_all(mgxs, data):
-    start = mgxs["nu_s_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def nu_s_last(mgxs, data):
-    start = mgxs["nu_s_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def nu_s_chunk(start, length, mgxs, data):
-    start += mgxs["nu_s_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nu_p(index, mgxs, data):
-    offset = mgxs["nu_p_offset"]
-    return data[offset + index]
-
-
-@njit
-def nu_p_all(mgxs, data):
-    start = mgxs["nu_p_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def nu_p_last(mgxs, data):
-    start = mgxs["nu_p_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def nu_p_chunk(start, length, mgxs, data):
-    start += mgxs["nu_p_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nu_d_vector(index_1, mgxs, data):
-    offset = mgxs["nu_d_offset"]
-    stride = mgxs["J"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def nu_d(index_1, index_2, mgxs, data):
-    offset = mgxs["nu_d_offset"]
-    stride = mgxs["J"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def nu_d_chunk(start, length, mgxs, data):
-    start += mgxs["nu_d_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nu_d_total(index, mgxs, data):
-    offset = mgxs["nu_d_total_offset"]
-    return data[offset + index]
-
-
-@njit
-def nu_d_total_all(mgxs, data):
-    start = mgxs["nu_d_total_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def nu_d_total_last(mgxs, data):
-    start = mgxs["nu_d_total_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def nu_d_total_chunk(start, length, mgxs, data):
-    start += mgxs["nu_d_total_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nu_f(index, mgxs, data):
-    offset = mgxs["nu_f_offset"]
-    return data[offset + index]
-
-
-@njit
-def nu_f_all(mgxs, data):
-    start = mgxs["nu_f_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def nu_f_last(mgxs, data):
-    start = mgxs["nu_f_offset"]
-    size = mgxs["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def nu_f_chunk(start, length, mgxs, data):
-    start += mgxs["nu_f_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def chi_s_vector(index_1, mgxs, data):
-    offset = mgxs["chi_s_offset"]
-    stride = mgxs["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def chi_s(index_1, index_2, mgxs, data):
-    offset = mgxs["chi_s_offset"]
-    stride = mgxs["G"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def chi_s_chunk(start, length, mgxs, data):
-    start += mgxs["chi_s_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def chi_p_vector(index_1, mgxs, data):
-    offset = mgxs["chi_p_offset"]
-    stride = mgxs["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def chi_p(index_1, index_2, mgxs, data):
-    offset = mgxs["chi_p_offset"]
-    stride = mgxs["G"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def chi_p_chunk(start, length, mgxs, data):
-    start += mgxs["chi_p_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def chi_d_vector(index_1, mgxs, data):
-    offset = mgxs["chi_d_offset"]
-    stride = mgxs["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def chi_d(index_1, index_2, mgxs, data):
-    offset = mgxs["chi_d_offset"]
-    stride = mgxs["G"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def chi_d_chunk(start, length, mgxs, data):
-    start += mgxs["chi_d_offset"]
-    end = start + length
-    return data[start:end]
diff --git a/mcdc/mcdc_get/multigroup_material.py b/mcdc/mcdc_get/multigroup_material.py
deleted file mode 100644
index 12f63912c..000000000
--- a/mcdc/mcdc_get/multigroup_material.py
+++ /dev/null
@@ -1,385 +0,0 @@
-# The following is automatically generated by code_factory.py
-
-from numba import njit
-
-
-@njit
-def mgxs_speed(index, multigroup_material, data):
-    offset = multigroup_material["mgxs_speed_offset"]
-    return data[offset + index]
-
-
-@njit
-def mgxs_speed_all(multigroup_material, data):
-    start = multigroup_material["mgxs_speed_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def mgxs_speed_last(multigroup_material, data):
-    start = multigroup_material["mgxs_speed_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def mgxs_speed_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_speed_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_decay_rate(index, multigroup_material, data):
-    offset = multigroup_material["mgxs_decay_rate_offset"]
-    return data[offset + index]
-
-
-@njit
-def mgxs_decay_rate_all(multigroup_material, data):
-    start = multigroup_material["mgxs_decay_rate_offset"]
-    size = multigroup_material["J"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def mgxs_decay_rate_last(multigroup_material, data):
-    start = multigroup_material["mgxs_decay_rate_offset"]
-    size = multigroup_material["J"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def mgxs_decay_rate_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_decay_rate_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_capture(index, multigroup_material, data):
-    offset = multigroup_material["mgxs_capture_offset"]
-    return data[offset + index]
-
-
-@njit
-def mgxs_capture_all(multigroup_material, data):
-    start = multigroup_material["mgxs_capture_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def mgxs_capture_last(multigroup_material, data):
-    start = multigroup_material["mgxs_capture_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def mgxs_capture_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_capture_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_scatter(index, multigroup_material, data):
-    offset = multigroup_material["mgxs_scatter_offset"]
-    return data[offset + index]
-
-
-@njit
-def mgxs_scatter_all(multigroup_material, data):
-    start = multigroup_material["mgxs_scatter_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def mgxs_scatter_last(multigroup_material, data):
-    start = multigroup_material["mgxs_scatter_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def mgxs_scatter_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_scatter_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_fission(index, multigroup_material, data):
-    offset = multigroup_material["mgxs_fission_offset"]
-    return data[offset + index]
-
-
-@njit
-def mgxs_fission_all(multigroup_material, data):
-    start = multigroup_material["mgxs_fission_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def mgxs_fission_last(multigroup_material, data):
-    start = multigroup_material["mgxs_fission_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def mgxs_fission_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_fission_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_total(index, multigroup_material, data):
-    offset = multigroup_material["mgxs_total_offset"]
-    return data[offset + index]
-
-
-@njit
-def mgxs_total_all(multigroup_material, data):
-    start = multigroup_material["mgxs_total_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def mgxs_total_last(multigroup_material, data):
-    start = multigroup_material["mgxs_total_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def mgxs_total_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_total_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_nu_s(index, multigroup_material, data):
-    offset = multigroup_material["mgxs_nu_s_offset"]
-    return data[offset + index]
-
-
-@njit
-def mgxs_nu_s_all(multigroup_material, data):
-    start = multigroup_material["mgxs_nu_s_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def mgxs_nu_s_last(multigroup_material, data):
-    start = multigroup_material["mgxs_nu_s_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def mgxs_nu_s_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_nu_s_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_nu_p(index, multigroup_material, data):
-    offset = multigroup_material["mgxs_nu_p_offset"]
-    return data[offset + index]
-
-
-@njit
-def mgxs_nu_p_all(multigroup_material, data):
-    start = multigroup_material["mgxs_nu_p_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def mgxs_nu_p_last(multigroup_material, data):
-    start = multigroup_material["mgxs_nu_p_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def mgxs_nu_p_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_nu_p_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_nu_d_vector(index_1, multigroup_material, data):
-    offset = multigroup_material["mgxs_nu_d_offset"]
-    stride = multigroup_material["J"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def mgxs_nu_d(index_1, index_2, multigroup_material, data):
-    offset = multigroup_material["mgxs_nu_d_offset"]
-    stride = multigroup_material["J"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def mgxs_nu_d_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_nu_d_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_nu_d_total(index, multigroup_material, data):
-    offset = multigroup_material["mgxs_nu_d_total_offset"]
-    return data[offset + index]
-
-
-@njit
-def mgxs_nu_d_total_all(multigroup_material, data):
-    start = multigroup_material["mgxs_nu_d_total_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def mgxs_nu_d_total_last(multigroup_material, data):
-    start = multigroup_material["mgxs_nu_d_total_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def mgxs_nu_d_total_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_nu_d_total_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_nu_f(index, multigroup_material, data):
-    offset = multigroup_material["mgxs_nu_f_offset"]
-    return data[offset + index]
-
-
-@njit
-def mgxs_nu_f_all(multigroup_material, data):
-    start = multigroup_material["mgxs_nu_f_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def mgxs_nu_f_last(multigroup_material, data):
-    start = multigroup_material["mgxs_nu_f_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def mgxs_nu_f_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_nu_f_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_chi_s_vector(index_1, multigroup_material, data):
-    offset = multigroup_material["mgxs_chi_s_offset"]
-    stride = multigroup_material["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def mgxs_chi_s(index_1, index_2, multigroup_material, data):
-    offset = multigroup_material["mgxs_chi_s_offset"]
-    stride = multigroup_material["G"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def mgxs_chi_s_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_chi_s_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_chi_p_vector(index_1, multigroup_material, data):
-    offset = multigroup_material["mgxs_chi_p_offset"]
-    stride = multigroup_material["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def mgxs_chi_p(index_1, index_2, multigroup_material, data):
-    offset = multigroup_material["mgxs_chi_p_offset"]
-    stride = multigroup_material["G"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def mgxs_chi_p_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_chi_p_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def mgxs_chi_d_vector(index_1, multigroup_material, data):
-    offset = multigroup_material["mgxs_chi_d_offset"]
-    stride = multigroup_material["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def mgxs_chi_d(index_1, index_2, multigroup_material, data):
-    offset = multigroup_material["mgxs_chi_d_offset"]
-    stride = multigroup_material["G"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def mgxs_chi_d_chunk(start, length, multigroup_material, data):
-    start += multigroup_material["mgxs_chi_d_offset"]
-    end = start + length
-    return data[start:end]
diff --git a/mcdc/mcdc_get/native_material.py b/mcdc/mcdc_get/native_material.py
deleted file mode 100644
index f07966d30..000000000
--- a/mcdc/mcdc_get/native_material.py
+++ /dev/null
@@ -1,120 +0,0 @@
-# The following is automatically generated by code_factory.py
-
-from numpy import int64
-from numba import njit
-
-
-@njit
-def nuclide_IDs(index, native_material, data):
-    offset = native_material["nuclide_IDs_offset"]
-    return int64(data[offset + index])
-
-
-@njit
-def nuclide_IDs_all(native_material, data):
-    start = native_material["nuclide_IDs_offset"]
-    size = native_material["N_nuclide"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def nuclide_IDs_last(native_material, data):
-    start = native_material["nuclide_IDs_offset"]
-    size = native_material["N_nuclide"]
-    end = start + size
-    return int64(data[end - 1])
-
-
-@njit
-def nuclide_IDs_chunk(start, length, native_material, data):
-    start += native_material["nuclide_IDs_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def element_IDs(index, native_material, data):
-    offset = native_material["element_IDs_offset"]
-    return int64(data[offset + index])
-
-
-@njit
-def element_IDs_all(native_material, data):
-    start = native_material["element_IDs_offset"]
-    size = native_material["N_element"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def element_IDs_last(native_material, data):
-    start = native_material["element_IDs_offset"]
-    size = native_material["N_element"]
-    end = start + size
-    return int64(data[end - 1])
-
-
-@njit
-def element_IDs_chunk(start, length, native_material, data):
-    start += native_material["element_IDs_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nuclide_densities(index, native_material, data):
-    offset = native_material["nuclide_densities_offset"]
-    return data[offset + index]
-
-
-@njit
-def nuclide_densities_all(native_material, data):
-    start = native_material["nuclide_densities_offset"]
-    size = native_material["nuclide_densities_length"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def nuclide_densities_last(native_material, data):
-    start = native_material["nuclide_densities_offset"]
-    size = native_material["nuclide_densities_length"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def nuclide_densities_chunk(start, length, native_material, data):
-    start += native_material["nuclide_densities_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def element_densities(index, native_material, data):
-    offset = native_material["element_densities_offset"]
-    return data[offset + index]
-
-
-@njit
-def element_densities_all(native_material, data):
-    start = native_material["element_densities_offset"]
-    size = native_material["element_densities_length"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def element_densities_last(native_material, data):
-    start = native_material["element_densities_offset"]
-    size = native_material["element_densities_length"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def element_densities_chunk(start, length, native_material, data):
-    start += native_material["element_densities_offset"]
-    end = start + length
-    return data[start:end]
diff --git a/mcdc/mcdc_get/neutron_multigroup.py b/mcdc/mcdc_get/neutron_multigroup.py
new file mode 100644
index 000000000..cd551ac8d
--- /dev/null
+++ b/mcdc/mcdc_get/neutron_multigroup.py
@@ -0,0 +1,414 @@
+# The following is automatically generated by code_factory.py
+
+from numba import njit
+
+
+@njit
+def energy_grid(index, neutron_multigroup, data):
+    offset = neutron_multigroup["energy_grid_offset"]
+    return data[offset + index]
+
+
+@njit
+def energy_grid_all(neutron_multigroup, data):
+    start = neutron_multigroup["energy_grid_offset"]
+    size = neutron_multigroup["G"] + 1
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def energy_grid_last(neutron_multigroup, data):
+    start = neutron_multigroup["energy_grid_offset"]
+    size = neutron_multigroup["G"] + 1
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def energy_grid_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["energy_grid_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def speed(index, neutron_multigroup, data):
+    offset = neutron_multigroup["speed_offset"]
+    return data[offset + index]
+
+
+@njit
+def speed_all(neutron_multigroup, data):
+    start = neutron_multigroup["speed_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def speed_last(neutron_multigroup, data):
+    start = neutron_multigroup["speed_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def speed_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["speed_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def decay_rate(index, neutron_multigroup, data):
+    offset = neutron_multigroup["decay_rate_offset"]
+    return data[offset + index]
+
+
+@njit
+def decay_rate_all(neutron_multigroup, data):
+    start = neutron_multigroup["decay_rate_offset"]
+    size = neutron_multigroup["J"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def decay_rate_last(neutron_multigroup, data):
+    start = neutron_multigroup["decay_rate_offset"]
+    size = neutron_multigroup["J"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def decay_rate_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["decay_rate_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def capture(index, neutron_multigroup, data):
+    offset = neutron_multigroup["capture_offset"]
+    return data[offset + index]
+
+
+@njit
+def capture_all(neutron_multigroup, data):
+    start = neutron_multigroup["capture_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def capture_last(neutron_multigroup, data):
+    start = neutron_multigroup["capture_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def capture_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["capture_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def scatter(index, neutron_multigroup, data):
+    offset = neutron_multigroup["scatter_offset"]
+    return data[offset + index]
+
+
+@njit
+def scatter_all(neutron_multigroup, data):
+    start = neutron_multigroup["scatter_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def scatter_last(neutron_multigroup, data):
+    start = neutron_multigroup["scatter_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def scatter_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["scatter_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def fission(index, neutron_multigroup, data):
+    offset = neutron_multigroup["fission_offset"]
+    return data[offset + index]
+
+
+@njit
+def fission_all(neutron_multigroup, data):
+    start = neutron_multigroup["fission_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def fission_last(neutron_multigroup, data):
+    start = neutron_multigroup["fission_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def fission_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["fission_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def total(index, neutron_multigroup, data):
+    offset = neutron_multigroup["total_offset"]
+    return data[offset + index]
+
+
+@njit
+def total_all(neutron_multigroup, data):
+    start = neutron_multigroup["total_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def total_last(neutron_multigroup, data):
+    start = neutron_multigroup["total_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def total_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["total_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_s(index, neutron_multigroup, data):
+    offset = neutron_multigroup["nu_s_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_s_all(neutron_multigroup, data):
+    start = neutron_multigroup["nu_s_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_s_last(neutron_multigroup, data):
+    start = neutron_multigroup["nu_s_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_s_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["nu_s_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_p(index, neutron_multigroup, data):
+    offset = neutron_multigroup["nu_p_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_p_all(neutron_multigroup, data):
+    start = neutron_multigroup["nu_p_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_p_last(neutron_multigroup, data):
+    start = neutron_multigroup["nu_p_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_p_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["nu_p_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_d_vector(index_1, neutron_multigroup, data):
+    offset = neutron_multigroup["nu_d_offset"]
+    stride = neutron_multigroup["J"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def nu_d(index_1, index_2, neutron_multigroup, data):
+    offset = neutron_multigroup["nu_d_offset"]
+    stride = neutron_multigroup["J"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def nu_d_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["nu_d_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_d_total(index, neutron_multigroup, data):
+    offset = neutron_multigroup["nu_d_total_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_d_total_all(neutron_multigroup, data):
+    start = neutron_multigroup["nu_d_total_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_d_total_last(neutron_multigroup, data):
+    start = neutron_multigroup["nu_d_total_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_d_total_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["nu_d_total_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_f(index, neutron_multigroup, data):
+    offset = neutron_multigroup["nu_f_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_f_all(neutron_multigroup, data):
+    start = neutron_multigroup["nu_f_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_f_last(neutron_multigroup, data):
+    start = neutron_multigroup["nu_f_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_f_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["nu_f_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def chi_s_vector(index_1, neutron_multigroup, data):
+    offset = neutron_multigroup["chi_s_offset"]
+    stride = neutron_multigroup["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def chi_s(index_1, index_2, neutron_multigroup, data):
+    offset = neutron_multigroup["chi_s_offset"]
+    stride = neutron_multigroup["G"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def chi_s_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["chi_s_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def chi_p_vector(index_1, neutron_multigroup, data):
+    offset = neutron_multigroup["chi_p_offset"]
+    stride = neutron_multigroup["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def chi_p(index_1, index_2, neutron_multigroup, data):
+    offset = neutron_multigroup["chi_p_offset"]
+    stride = neutron_multigroup["G"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def chi_p_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["chi_p_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def chi_d_vector(index_1, neutron_multigroup, data):
+    offset = neutron_multigroup["chi_d_offset"]
+    stride = neutron_multigroup["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def chi_d(index_1, index_2, neutron_multigroup, data):
+    offset = neutron_multigroup["chi_d_offset"]
+    stride = neutron_multigroup["G"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def chi_d_chunk(start, length, neutron_multigroup, data):
+    start += neutron_multigroup["chi_d_offset"]
+    end = start + length
+    return data[start:end]
diff --git a/mcdc/mcdc_set/__init__.py b/mcdc/mcdc_set/__init__.py
index 0d1f4444f..7fdc53d3c 100644
--- a/mcdc/mcdc_set/__init__.py
+++ b/mcdc/mcdc_set/__init__.py
@@ -60,9 +60,7 @@
 
 import mcdc.mcdc_set.gpu_meta as gpu_meta
 
-import mcdc.mcdc_set.native_material as native_material
-
-import mcdc.mcdc_set.multigroup_material as multigroup_material
+import mcdc.mcdc_set.neutron_multigroup as neutron_multigroup
 
 import mcdc.mcdc_set.nuclide as nuclide
 
@@ -72,8 +70,6 @@
 
 import mcdc.mcdc_set.uniform_mesh as uniform_mesh
 
-import mcdc.mcdc_set.mgxs as mgxs
-
 import mcdc.mcdc_set.neutron_reaction as neutron_reaction
 
 import mcdc.mcdc_set.neutron_capture_reaction as neutron_capture_reaction
diff --git a/mcdc/mcdc_set/material.py b/mcdc/mcdc_set/material.py
index fdbf8e750..f006985cb 100644
--- a/mcdc/mcdc_set/material.py
+++ b/mcdc/mcdc_set/material.py
@@ -1,3 +1,119 @@
 # The following is automatically generated by code_factory.py
 
 from numba import njit
+
+
+@njit
+def nuclide_IDs(index, material, data, value):
+    offset = material["nuclide_IDs_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nuclide_IDs_all(material, data, value):
+    start = material["nuclide_IDs_offset"]
+    size = material["N_nuclide"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nuclide_IDs_last(material, data, value):
+    start = material["nuclide_IDs_offset"]
+    size = material["N_nuclide"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nuclide_IDs_chunk(start, length, material, data, value):
+    start += material["nuclide_IDs_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def element_IDs(index, material, data, value):
+    offset = material["element_IDs_offset"]
+    data[offset + index] = value
+
+
+@njit
+def element_IDs_all(material, data, value):
+    start = material["element_IDs_offset"]
+    size = material["N_element"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def element_IDs_last(material, data, value):
+    start = material["element_IDs_offset"]
+    size = material["N_element"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def element_IDs_chunk(start, length, material, data, value):
+    start += material["element_IDs_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nuclide_densities(index, material, data, value):
+    offset = material["nuclide_densities_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nuclide_densities_all(material, data, value):
+    start = material["nuclide_densities_offset"]
+    size = material["nuclide_densities_length"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nuclide_densities_last(material, data, value):
+    start = material["nuclide_densities_offset"]
+    size = material["nuclide_densities_length"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nuclide_densities_chunk(start, length, material, data, value):
+    start += material["nuclide_densities_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def element_densities(index, material, data, value):
+    offset = material["element_densities_offset"]
+    data[offset + index] = value
+
+
+@njit
+def element_densities_all(material, data, value):
+    start = material["element_densities_offset"]
+    size = material["element_densities_length"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def element_densities_last(material, data, value):
+    start = material["element_densities_offset"]
+    size = material["element_densities_length"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def element_densities_chunk(start, length, material, data, value):
+    start += material["element_densities_offset"]
+    end = start + length
+    data[start:end] = value
diff --git a/mcdc/mcdc_set/mgxs.py b/mcdc/mcdc_set/mgxs.py
deleted file mode 100644
index 071e10327..000000000
--- a/mcdc/mcdc_set/mgxs.py
+++ /dev/null
@@ -1,414 +0,0 @@
-# The following is automatically generated by code_factory.py
-
-from numba import njit
-
-
-@njit
-def energy_grid(index, mgxs, data, value):
-    offset = mgxs["energy_grid_offset"]
-    data[offset + index] = value
-
-
-@njit
-def energy_grid_all(mgxs, data, value):
-    start = mgxs["energy_grid_offset"]
-    size = mgxs["G"] + 1
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def energy_grid_last(mgxs, data, value):
-    start = mgxs["energy_grid_offset"]
-    size = mgxs["G"] + 1
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def energy_grid_chunk(start, length, mgxs, data, value):
-    start += mgxs["energy_grid_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def speed(index, mgxs, data, value):
-    offset = mgxs["speed_offset"]
-    data[offset + index] = value
-
-
-@njit
-def speed_all(mgxs, data, value):
-    start = mgxs["speed_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def speed_last(mgxs, data, value):
-    start = mgxs["speed_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def speed_chunk(start, length, mgxs, data, value):
-    start += mgxs["speed_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def decay_rate(index, mgxs, data, value):
-    offset = mgxs["decay_rate_offset"]
-    data[offset + index] = value
-
-
-@njit
-def decay_rate_all(mgxs, data, value):
-    start = mgxs["decay_rate_offset"]
-    size = mgxs["J"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def decay_rate_last(mgxs, data, value):
-    start = mgxs["decay_rate_offset"]
-    size = mgxs["J"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def decay_rate_chunk(start, length, mgxs, data, value):
-    start += mgxs["decay_rate_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def capture(index, mgxs, data, value):
-    offset = mgxs["capture_offset"]
-    data[offset + index] = value
-
-
-@njit
-def capture_all(mgxs, data, value):
-    start = mgxs["capture_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def capture_last(mgxs, data, value):
-    start = mgxs["capture_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def capture_chunk(start, length, mgxs, data, value):
-    start += mgxs["capture_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def scatter(index, mgxs, data, value):
-    offset = mgxs["scatter_offset"]
-    data[offset + index] = value
-
-
-@njit
-def scatter_all(mgxs, data, value):
-    start = mgxs["scatter_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def scatter_last(mgxs, data, value):
-    start = mgxs["scatter_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def scatter_chunk(start, length, mgxs, data, value):
-    start += mgxs["scatter_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def fission(index, mgxs, data, value):
-    offset = mgxs["fission_offset"]
-    data[offset + index] = value
-
-
-@njit
-def fission_all(mgxs, data, value):
-    start = mgxs["fission_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def fission_last(mgxs, data, value):
-    start = mgxs["fission_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def fission_chunk(start, length, mgxs, data, value):
-    start += mgxs["fission_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def total(index, mgxs, data, value):
-    offset = mgxs["total_offset"]
-    data[offset + index] = value
-
-
-@njit
-def total_all(mgxs, data, value):
-    start = mgxs["total_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def total_last(mgxs, data, value):
-    start = mgxs["total_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def total_chunk(start, length, mgxs, data, value):
-    start += mgxs["total_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nu_s(index, mgxs, data, value):
-    offset = mgxs["nu_s_offset"]
-    data[offset + index] = value
-
-
-@njit
-def nu_s_all(mgxs, data, value):
-    start = mgxs["nu_s_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def nu_s_last(mgxs, data, value):
-    start = mgxs["nu_s_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def nu_s_chunk(start, length, mgxs, data, value):
-    start += mgxs["nu_s_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nu_p(index, mgxs, data, value):
-    offset = mgxs["nu_p_offset"]
-    data[offset + index] = value
-
-
-@njit
-def nu_p_all(mgxs, data, value):
-    start = mgxs["nu_p_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def nu_p_last(mgxs, data, value):
-    start = mgxs["nu_p_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def nu_p_chunk(start, length, mgxs, data, value):
-    start += mgxs["nu_p_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nu_d_vector(index_1, mgxs, data, value):
-    offset = mgxs["nu_d_offset"]
-    stride = mgxs["J"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def nu_d(index_1, index_2, mgxs, data, value):
-    offset = mgxs["nu_d_offset"]
-    stride = mgxs["J"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def nu_d_chunk(start, length, mgxs, data, value):
-    start += mgxs["nu_d_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nu_d_total(index, mgxs, data, value):
-    offset = mgxs["nu_d_total_offset"]
-    data[offset + index] = value
-
-
-@njit
-def nu_d_total_all(mgxs, data, value):
-    start = mgxs["nu_d_total_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def nu_d_total_last(mgxs, data, value):
-    start = mgxs["nu_d_total_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def nu_d_total_chunk(start, length, mgxs, data, value):
-    start += mgxs["nu_d_total_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nu_f(index, mgxs, data, value):
-    offset = mgxs["nu_f_offset"]
-    data[offset + index] = value
-
-
-@njit
-def nu_f_all(mgxs, data, value):
-    start = mgxs["nu_f_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def nu_f_last(mgxs, data, value):
-    start = mgxs["nu_f_offset"]
-    size = mgxs["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def nu_f_chunk(start, length, mgxs, data, value):
-    start += mgxs["nu_f_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def chi_s_vector(index_1, mgxs, data, value):
-    offset = mgxs["chi_s_offset"]
-    stride = mgxs["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def chi_s(index_1, index_2, mgxs, data, value):
-    offset = mgxs["chi_s_offset"]
-    stride = mgxs["G"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def chi_s_chunk(start, length, mgxs, data, value):
-    start += mgxs["chi_s_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def chi_p_vector(index_1, mgxs, data, value):
-    offset = mgxs["chi_p_offset"]
-    stride = mgxs["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def chi_p(index_1, index_2, mgxs, data, value):
-    offset = mgxs["chi_p_offset"]
-    stride = mgxs["G"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def chi_p_chunk(start, length, mgxs, data, value):
-    start += mgxs["chi_p_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def chi_d_vector(index_1, mgxs, data, value):
-    offset = mgxs["chi_d_offset"]
-    stride = mgxs["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def chi_d(index_1, index_2, mgxs, data, value):
-    offset = mgxs["chi_d_offset"]
-    stride = mgxs["G"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def chi_d_chunk(start, length, mgxs, data, value):
-    start += mgxs["chi_d_offset"]
-    end = start + length
-    data[start:end] = value
diff --git a/mcdc/mcdc_set/multigroup_material.py b/mcdc/mcdc_set/multigroup_material.py
deleted file mode 100644
index c345a8662..000000000
--- a/mcdc/mcdc_set/multigroup_material.py
+++ /dev/null
@@ -1,385 +0,0 @@
-# The following is automatically generated by code_factory.py
-
-from numba import njit
-
-
-@njit
-def mgxs_speed(index, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_speed_offset"]
-    data[offset + index] = value
-
-
-@njit
-def mgxs_speed_all(multigroup_material, data, value):
-    start = multigroup_material["mgxs_speed_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def mgxs_speed_last(multigroup_material, data, value):
-    start = multigroup_material["mgxs_speed_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def mgxs_speed_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_speed_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_decay_rate(index, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_decay_rate_offset"]
-    data[offset + index] = value
-
-
-@njit
-def mgxs_decay_rate_all(multigroup_material, data, value):
-    start = multigroup_material["mgxs_decay_rate_offset"]
-    size = multigroup_material["J"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def mgxs_decay_rate_last(multigroup_material, data, value):
-    start = multigroup_material["mgxs_decay_rate_offset"]
-    size = multigroup_material["J"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def mgxs_decay_rate_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_decay_rate_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_capture(index, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_capture_offset"]
-    data[offset + index] = value
-
-
-@njit
-def mgxs_capture_all(multigroup_material, data, value):
-    start = multigroup_material["mgxs_capture_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def mgxs_capture_last(multigroup_material, data, value):
-    start = multigroup_material["mgxs_capture_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def mgxs_capture_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_capture_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_scatter(index, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_scatter_offset"]
-    data[offset + index] = value
-
-
-@njit
-def mgxs_scatter_all(multigroup_material, data, value):
-    start = multigroup_material["mgxs_scatter_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def mgxs_scatter_last(multigroup_material, data, value):
-    start = multigroup_material["mgxs_scatter_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def mgxs_scatter_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_scatter_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_fission(index, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_fission_offset"]
-    data[offset + index] = value
-
-
-@njit
-def mgxs_fission_all(multigroup_material, data, value):
-    start = multigroup_material["mgxs_fission_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def mgxs_fission_last(multigroup_material, data, value):
-    start = multigroup_material["mgxs_fission_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def mgxs_fission_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_fission_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_total(index, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_total_offset"]
-    data[offset + index] = value
-
-
-@njit
-def mgxs_total_all(multigroup_material, data, value):
-    start = multigroup_material["mgxs_total_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def mgxs_total_last(multigroup_material, data, value):
-    start = multigroup_material["mgxs_total_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def mgxs_total_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_total_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_nu_s(index, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_nu_s_offset"]
-    data[offset + index] = value
-
-
-@njit
-def mgxs_nu_s_all(multigroup_material, data, value):
-    start = multigroup_material["mgxs_nu_s_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def mgxs_nu_s_last(multigroup_material, data, value):
-    start = multigroup_material["mgxs_nu_s_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def mgxs_nu_s_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_nu_s_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_nu_p(index, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_nu_p_offset"]
-    data[offset + index] = value
-
-
-@njit
-def mgxs_nu_p_all(multigroup_material, data, value):
-    start = multigroup_material["mgxs_nu_p_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def mgxs_nu_p_last(multigroup_material, data, value):
-    start = multigroup_material["mgxs_nu_p_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def mgxs_nu_p_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_nu_p_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_nu_d_vector(index_1, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_nu_d_offset"]
-    stride = multigroup_material["J"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def mgxs_nu_d(index_1, index_2, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_nu_d_offset"]
-    stride = multigroup_material["J"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def mgxs_nu_d_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_nu_d_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_nu_d_total(index, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_nu_d_total_offset"]
-    data[offset + index] = value
-
-
-@njit
-def mgxs_nu_d_total_all(multigroup_material, data, value):
-    start = multigroup_material["mgxs_nu_d_total_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def mgxs_nu_d_total_last(multigroup_material, data, value):
-    start = multigroup_material["mgxs_nu_d_total_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def mgxs_nu_d_total_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_nu_d_total_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_nu_f(index, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_nu_f_offset"]
-    data[offset + index] = value
-
-
-@njit
-def mgxs_nu_f_all(multigroup_material, data, value):
-    start = multigroup_material["mgxs_nu_f_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def mgxs_nu_f_last(multigroup_material, data, value):
-    start = multigroup_material["mgxs_nu_f_offset"]
-    size = multigroup_material["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def mgxs_nu_f_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_nu_f_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_chi_s_vector(index_1, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_chi_s_offset"]
-    stride = multigroup_material["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def mgxs_chi_s(index_1, index_2, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_chi_s_offset"]
-    stride = multigroup_material["G"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def mgxs_chi_s_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_chi_s_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_chi_p_vector(index_1, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_chi_p_offset"]
-    stride = multigroup_material["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def mgxs_chi_p(index_1, index_2, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_chi_p_offset"]
-    stride = multigroup_material["G"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def mgxs_chi_p_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_chi_p_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def mgxs_chi_d_vector(index_1, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_chi_d_offset"]
-    stride = multigroup_material["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def mgxs_chi_d(index_1, index_2, multigroup_material, data, value):
-    offset = multigroup_material["mgxs_chi_d_offset"]
-    stride = multigroup_material["G"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def mgxs_chi_d_chunk(start, length, multigroup_material, data, value):
-    start += multigroup_material["mgxs_chi_d_offset"]
-    end = start + length
-    data[start:end] = value
diff --git a/mcdc/mcdc_set/native_material.py b/mcdc/mcdc_set/native_material.py
deleted file mode 100644
index 303ffb474..000000000
--- a/mcdc/mcdc_set/native_material.py
+++ /dev/null
@@ -1,119 +0,0 @@
-# The following is automatically generated by code_factory.py
-
-from numba import njit
-
-
-@njit
-def nuclide_IDs(index, native_material, data, value):
-    offset = native_material["nuclide_IDs_offset"]
-    data[offset + index] = value
-
-
-@njit
-def nuclide_IDs_all(native_material, data, value):
-    start = native_material["nuclide_IDs_offset"]
-    size = native_material["N_nuclide"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def nuclide_IDs_last(native_material, data, value):
-    start = native_material["nuclide_IDs_offset"]
-    size = native_material["N_nuclide"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def nuclide_IDs_chunk(start, length, native_material, data, value):
-    start += native_material["nuclide_IDs_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def element_IDs(index, native_material, data, value):
-    offset = native_material["element_IDs_offset"]
-    data[offset + index] = value
-
-
-@njit
-def element_IDs_all(native_material, data, value):
-    start = native_material["element_IDs_offset"]
-    size = native_material["N_element"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def element_IDs_last(native_material, data, value):
-    start = native_material["element_IDs_offset"]
-    size = native_material["N_element"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def element_IDs_chunk(start, length, native_material, data, value):
-    start += native_material["element_IDs_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nuclide_densities(index, native_material, data, value):
-    offset = native_material["nuclide_densities_offset"]
-    data[offset + index] = value
-
-
-@njit
-def nuclide_densities_all(native_material, data, value):
-    start = native_material["nuclide_densities_offset"]
-    size = native_material["nuclide_densities_length"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def nuclide_densities_last(native_material, data, value):
-    start = native_material["nuclide_densities_offset"]
-    size = native_material["nuclide_densities_length"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def nuclide_densities_chunk(start, length, native_material, data, value):
-    start += native_material["nuclide_densities_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def element_densities(index, native_material, data, value):
-    offset = native_material["element_densities_offset"]
-    data[offset + index] = value
-
-
-@njit
-def element_densities_all(native_material, data, value):
-    start = native_material["element_densities_offset"]
-    size = native_material["element_densities_length"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def element_densities_last(native_material, data, value):
-    start = native_material["element_densities_offset"]
-    size = native_material["element_densities_length"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def element_densities_chunk(start, length, native_material, data, value):
-    start += native_material["element_densities_offset"]
-    end = start + length
-    data[start:end] = value
diff --git a/mcdc/mcdc_set/neutron_multigroup.py b/mcdc/mcdc_set/neutron_multigroup.py
new file mode 100644
index 000000000..03ed012af
--- /dev/null
+++ b/mcdc/mcdc_set/neutron_multigroup.py
@@ -0,0 +1,414 @@
+# The following is automatically generated by code_factory.py
+
+from numba import njit
+
+
+@njit
+def energy_grid(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["energy_grid_offset"]
+    data[offset + index] = value
+
+
+@njit
+def energy_grid_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["energy_grid_offset"]
+    size = neutron_multigroup["G"] + 1
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def energy_grid_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["energy_grid_offset"]
+    size = neutron_multigroup["G"] + 1
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def energy_grid_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["energy_grid_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def speed(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["speed_offset"]
+    data[offset + index] = value
+
+
+@njit
+def speed_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["speed_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def speed_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["speed_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def speed_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["speed_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def decay_rate(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["decay_rate_offset"]
+    data[offset + index] = value
+
+
+@njit
+def decay_rate_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["decay_rate_offset"]
+    size = neutron_multigroup["J"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def decay_rate_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["decay_rate_offset"]
+    size = neutron_multigroup["J"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def decay_rate_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["decay_rate_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def capture(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["capture_offset"]
+    data[offset + index] = value
+
+
+@njit
+def capture_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["capture_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def capture_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["capture_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def capture_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["capture_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def scatter(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["scatter_offset"]
+    data[offset + index] = value
+
+
+@njit
+def scatter_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["scatter_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def scatter_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["scatter_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def scatter_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["scatter_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def fission(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["fission_offset"]
+    data[offset + index] = value
+
+
+@njit
+def fission_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["fission_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def fission_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["fission_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def fission_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["fission_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def total(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["total_offset"]
+    data[offset + index] = value
+
+
+@njit
+def total_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["total_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def total_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["total_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def total_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["total_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_s(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["nu_s_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_s_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["nu_s_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_s_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["nu_s_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_s_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["nu_s_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_p(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["nu_p_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_p_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["nu_p_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_p_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["nu_p_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_p_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["nu_p_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_d_vector(index_1, neutron_multigroup, data, value):
+    offset = neutron_multigroup["nu_d_offset"]
+    stride = neutron_multigroup["J"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def nu_d(index_1, index_2, neutron_multigroup, data, value):
+    offset = neutron_multigroup["nu_d_offset"]
+    stride = neutron_multigroup["J"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def nu_d_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["nu_d_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_d_total(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["nu_d_total_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_d_total_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["nu_d_total_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_d_total_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["nu_d_total_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_d_total_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["nu_d_total_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_f(index, neutron_multigroup, data, value):
+    offset = neutron_multigroup["nu_f_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_f_all(neutron_multigroup, data, value):
+    start = neutron_multigroup["nu_f_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_f_last(neutron_multigroup, data, value):
+    start = neutron_multigroup["nu_f_offset"]
+    size = neutron_multigroup["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_f_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["nu_f_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def chi_s_vector(index_1, neutron_multigroup, data, value):
+    offset = neutron_multigroup["chi_s_offset"]
+    stride = neutron_multigroup["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def chi_s(index_1, index_2, neutron_multigroup, data, value):
+    offset = neutron_multigroup["chi_s_offset"]
+    stride = neutron_multigroup["G"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def chi_s_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["chi_s_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def chi_p_vector(index_1, neutron_multigroup, data, value):
+    offset = neutron_multigroup["chi_p_offset"]
+    stride = neutron_multigroup["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def chi_p(index_1, index_2, neutron_multigroup, data, value):
+    offset = neutron_multigroup["chi_p_offset"]
+    stride = neutron_multigroup["G"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def chi_p_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["chi_p_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def chi_d_vector(index_1, neutron_multigroup, data, value):
+    offset = neutron_multigroup["chi_d_offset"]
+    stride = neutron_multigroup["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def chi_d(index_1, index_2, neutron_multigroup, data, value):
+    offset = neutron_multigroup["chi_d_offset"]
+    stride = neutron_multigroup["G"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def chi_d_chunk(start, length, neutron_multigroup, data, value):
+    start += neutron_multigroup["chi_d_offset"]
+    end = start + length
+    data[start:end] = value
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index cf019c1ff..7ffe8fb19 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -83,10 +83,19 @@
 
 material = into_dtype([
     ('name', 'U32'),
+    ('temperature', float64),
     ('fissionable', bool),
+    ('has_neutron_multigroup', bool),
+    ('neutron_multigroup_ID', int64),
+    ('N_nuclide', int64),
+    ('nuclide_IDs_offset', int64),
+    ('N_element', int64),
+    ('element_IDs_offset', int64),
+    ('nuclide_densities_offset', int64),
+    ('nuclide_densities_length', int64),
+    ('element_densities_offset', int64),
+    ('element_densities_length', int64),
     ('ID', int64),
-    ('sub_type', int64),
-    ('sub_ID', int64),
 ])
 
 collision_tally = into_dtype([
@@ -333,52 +342,43 @@
     ('ID', int64),
 ])
 
-native_material = into_dtype([
-    ('N_nuclide', int64),
-    ('nuclide_IDs_offset', int64),
-    ('N_element', int64),
-    ('element_IDs_offset', int64),
-    ('nuclide_densities_offset', int64),
-    ('nuclide_densities_length', int64),
-    ('element_densities_offset', int64),
-    ('element_densities_length', int64),
-    ('ID', int64),
-    ('base_ID', int64),
-])
-
-multigroup_material = into_dtype([
+neutron_multigroup = into_dtype([
     ('G', int64),
     ('J', int64),
-    ('mgxs_speed_offset', int64),
-    ('mgxs_speed_length', int64),
-    ('mgxs_decay_rate_offset', int64),
-    ('mgxs_decay_rate_length', int64),
-    ('mgxs_capture_offset', int64),
-    ('mgxs_capture_length', int64),
-    ('mgxs_scatter_offset', int64),
-    ('mgxs_scatter_length', int64),
-    ('mgxs_fission_offset', int64),
-    ('mgxs_fission_length', int64),
-    ('mgxs_total_offset', int64),
-    ('mgxs_total_length', int64),
-    ('mgxs_nu_s_offset', int64),
-    ('mgxs_nu_s_length', int64),
-    ('mgxs_nu_p_offset', int64),
-    ('mgxs_nu_p_length', int64),
-    ('mgxs_nu_d_offset', int64),
-    ('mgxs_nu_d_length', int64),
-    ('mgxs_nu_d_total_offset', int64),
-    ('mgxs_nu_d_total_length', int64),
-    ('mgxs_nu_f_offset', int64),
-    ('mgxs_nu_f_length', int64),
-    ('mgxs_chi_s_offset', int64),
-    ('mgxs_chi_s_length', int64),
-    ('mgxs_chi_p_offset', int64),
-    ('mgxs_chi_p_length', int64),
-    ('mgxs_chi_d_offset', int64),
-    ('mgxs_chi_d_length', int64),
+    ('has_energy_grid', bool),
+    ('energy_grid_offset', int64),
+    ('energy_grid_length', int64),
+    ('energy_representation', int64),
+    ('speed_offset', int64),
+    ('speed_length', int64),
+    ('decay_rate_offset', int64),
+    ('decay_rate_length', int64),
+    ('capture_offset', int64),
+    ('capture_length', int64),
+    ('scatter_offset', int64),
+    ('scatter_length', int64),
+    ('fission_offset', int64),
+    ('fission_length', int64),
+    ('total_offset', int64),
+    ('total_length', int64),
+    ('nu_s_offset', int64),
+    ('nu_s_length', int64),
+    ('nu_p_offset', int64),
+    ('nu_p_length', int64),
+    ('nu_d_offset', int64),
+    ('nu_d_length', int64),
+    ('nu_d_total_offset', int64),
+    ('nu_d_total_length', int64),
+    ('nu_f_offset', int64),
+    ('nu_f_length', int64),
+    ('chi_s_offset', int64),
+    ('chi_s_length', int64),
+    ('chi_p_offset', int64),
+    ('chi_p_length', int64),
+    ('chi_d_offset', int64),
+    ('chi_d_length', int64),
+    ('fissionable', bool),
     ('ID', int64),
-    ('base_ID', int64),
 ])
 
 nuclide = into_dtype([
@@ -457,45 +457,6 @@
     ('base_ID', int64),
 ])
 
-mgxs = into_dtype([
-    ('G', int64),
-    ('J', int64),
-    ('has_energy_grid', bool),
-    ('energy_grid_offset', int64),
-    ('energy_grid_length', int64),
-    ('energy_representation', int64),
-    ('speed_offset', int64),
-    ('speed_length', int64),
-    ('decay_rate_offset', int64),
-    ('decay_rate_length', int64),
-    ('capture_offset', int64),
-    ('capture_length', int64),
-    ('scatter_offset', int64),
-    ('scatter_length', int64),
-    ('fission_offset', int64),
-    ('fission_length', int64),
-    ('total_offset', int64),
-    ('total_length', int64),
-    ('nu_s_offset', int64),
-    ('nu_s_length', int64),
-    ('nu_p_offset', int64),
-    ('nu_p_length', int64),
-    ('nu_d_offset', int64),
-    ('nu_d_length', int64),
-    ('nu_d_total_offset', int64),
-    ('nu_d_total_length', int64),
-    ('nu_f_offset', int64),
-    ('nu_f_length', int64),
-    ('chi_s_offset', int64),
-    ('chi_s_length', int64),
-    ('chi_p_offset', int64),
-    ('chi_p_length', int64),
-    ('chi_d_offset', int64),
-    ('chi_d_length', int64),
-    ('fissionable', bool),
-    ('ID', int64),
-])
-
 neutron_reaction = into_dtype([
     ('MT', int64),
     ('xs_offset', int64),
@@ -843,12 +804,8 @@ def set_simulation(N: dict):
         ('N_element', int64),
         ('materials', material, (N['material'])),
         ('N_material', int64),
-        ('native_materials', native_material, (N['native_material'])),
-        ('N_native_material', int64),
-        ('multigroup_materials', multigroup_material, (N['multigroup_material'])),
-        ('N_multigroup_material', int64),
-        ('mgxs', mgxs, (N['mgxs'])),
-        ('N_mgxs', int64),
+        ('neutron_multigroup', neutron_multigroup, (N['neutron_multigroup'])),
+        ('N_neutron_multigroup', int64),
         ('sources', source, (N['source'])),
         ('N_source', int64),
         ('surfaces', surface, (N['surface'])),
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index a27027ac6..e0942f79d 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -29,7 +29,7 @@
     PI,
 )
 from mcdc.object_.base import MCDCObject
-from mcdc.object_.material import MaterialBase
+from mcdc.object_.material import Material
 from mcdc.object_.tally import TallyCollision, TallyTracklength
 from mcdc.object_.universe import Universe, Lattice
 from mcdc.print_ import print_error
@@ -102,7 +102,7 @@ class Cell(MCDCObject):
     ----------
     region : Region, optional
         Boolean region expression. If omitted, the cell covers all space.
-    fill : MaterialBase, Universe, Lattice, or None, optional
+    fill : Material, Universe, Lattice, or None, optional
         Material or nested geometry placed in the cell. ``None`` creates a void
         cell.
     name : str, optional
@@ -125,7 +125,9 @@ class Cell(MCDCObject):
 
     >>> import numpy as np
     >>> import mcdc
-    >>> material = mcdc.MaterialMG(capture=np.array([1.0]))
+    >>> material = mcdc.Material(
+    ...     neutron_multigroup=mcdc.NeutronMultigroup(capture=np.array([1.0]))
+    ... )
     >>> lower = mcdc.Surface.PlaneZ(z=0.0)
     >>> upper = mcdc.Surface.PlaneZ(z=2.0)
     >>> cell = mcdc.Cell(region=+lower & -upper, fill=material)
@@ -173,7 +175,7 @@ class Cell(MCDCObject):
     surfaces: list[Surface]
 
     # Fill definition
-    fill: MaterialBase | Universe | Lattice | NoneType  # Non-numba
+    fill: Material | Universe | Lattice | NoneType  # Non-numba
     fill_type: int
     fill_ID: int
     fill_translated: bool
@@ -188,7 +190,7 @@ class Cell(MCDCObject):
     def __init__(
         self,
         region: Region | NoneType = None,
-        fill: MaterialBase | Universe | Lattice | NoneType = None,
+        fill: Material | Universe | Lattice | NoneType = None,
         name: str = "",
         translation: Sequence[float] = [0.0, 0.0, 0.0],
         rotation: Sequence[float] = [0.0, 0.0, 0.0],
@@ -226,7 +228,7 @@ def _compile_into_simulation(self, simulation) -> bool:
             fill._compile_into_simulation(simulation)
 
         # Numba representation of the cell fill
-        if isinstance(fill, MaterialBase):
+        if isinstance(fill, Material):
             self.fill_type = FILL_MATERIAL
             self.fill_ID = fill.ID
         elif isinstance(fill, Universe):
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index dda0762b5..b2116ec3b 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -1,61 +1,23 @@
-import numpy as np
+from types import NoneType
 
+import numpy as np
 from numpy import float64
 from numpy.typing import NDArray
-from types import NoneType
-from typing import Annotated
 
-####
-
-from mcdc.constant import MATERIAL, MATERIAL_MG
-from mcdc.object_.base import MCDCPolymorphic
+from mcdc.object_.base import MCDCObject
 from mcdc.object_.element import Element
+from mcdc.object_.transport_model import NeutronMultigroup
 from mcdc.object_.nuclide import Nuclide
 from mcdc.object_.util import ISOTOPIC_ABUNDANCE
-from mcdc.print_ import print_1d_array, print_error
+from mcdc.print_ import print_error
 
 # ======================================================================================
-# Material base class
+# Material
 # ======================================================================================
 
 
-class MaterialBase(MCDCPolymorphic):
-    """Base class shared by continuous-energy and multigroup materials.
-
-    Parameters
-    ----------
-    name : str
-        User-facing material name.
-    """
-
-    # MC/DC framework metadata
-    label = "material"
-    sub_type = -1  # Polymorphic base
-
-    name: str
-    fissionable: bool
-
-    def __init__(self, name: str) -> None:
-        super().__init__()
-
-        self.name = name or "(Unnamed material)"
-        self.fissionable = False
-
-    def __repr__(self):
-        text = super().__repr__()
-
-        text += f"  - Name: {self.name}\n"
-        text += f"  - Fissionable: {self.fissionable}\n"
-        return text
-
-
-# ======================================================================================
-# Native material
-# ======================================================================================
-
-
-class Material(MaterialBase):
-    """Define a continuous-energy material from a data-library composition.
+class Material(MCDCObject):
+    """Define a material from native compositions and/or multigroup data.
 
     Parameters
     ----------
@@ -68,15 +30,24 @@ class Material(MaterialBase):
     temperature : float, optional
         Material temperature in kelvin. Each nuclide uses the closest
         temperature available in the data library.
+    neutron_multigroup : NeutronMultigroup, optional
+        Multigroup cross sections for neutron transport. When supplied with a
+        native composition, its ``energy_grid`` is required and defines the
+        energy range over which multigroup physics applies.
 
     Notes
     -----
-    Exactly one of ``nuclide_composition`` or ``element_composition`` must be
-    supplied. Nuclide and element objects are created immediately; their
-    data-library properties are loaded when the material is compiled into a
-    simulation. Construction therefore does not access the data library.
-    Before compiling, visualizing, or running the model, ``MCDC_LIB`` must
-    identify the directory containing the required HDF5 files.
+    At least one native composition or multigroup dataset must be supplied.
+    Nuclide and element compositions cannot both be specified because they are
+    alternative native representations of the same material. A native
+    composition may be supplied together with ``neutron_multigroup`` for hybrid
+    neutron physics. Hybrid materials require an explicit ``NeutronMultigroup``
+    energy grid so collision physics can select between native and multigroup
+    data.
+
+    Nuclide and element objects are created immediately; their data-library
+    properties are loaded when the material is compiled into a simulation.
+    Construction therefore does not access the data library.
 
     Examples
     --------
@@ -89,30 +60,40 @@ class Material(MaterialBase):
     ...     temperature=293.6,
     ... )
 
-    Define a material from natural elemental compositions:
+    Define a one-group multigroup material:
 
-    >>> steel = mcdc.Material(
-    ...     name="Steel",
-    ...     element_composition={"Fe": 8.0e-2, "C": 8.0e-4},
-    ...     temperature=600.0,
+    >>> import numpy as np
+    >>> absorber = mcdc.Material(
+    ...     name="Absorber",
+    ...     neutron_multigroup=mcdc.NeutronMultigroup(capture=np.array([1.0])),
     ... )
 
-    Define a single-isotope material at another supported temperature:
-
-    >>> moderator = mcdc.Material(
-    ...     name="Hydrogen",
-    ...     nuclide_composition={"H1": 6.7e-2},
-    ...     temperature=273.15,
+    Attach native and multigroup neutron data to the same material:
+
+    >>> hybrid_fuel = mcdc.Material(
+    ...     name="Hybrid fuel",
+    ...     nuclide_composition={"U235": 5.0e-4, "U238": 2.2e-2},
+    ...     neutron_multigroup=mcdc.NeutronMultigroup(
+    ...         capture=np.array([0.10]),
+    ...         fission=np.array([0.20]),
+    ...         nu_p=np.array([2.50]),
+    ...         energy_grid=np.array([1.0e-5, 20.0e6]),
+    ...     ),
     ... )
     """
 
     # MC/DC framework metadata
-    label = "native_material"
-    sub_type = MATERIAL
+    label = "material"
     non_numba = ["nuclide_composition", "element_composition"]
 
-    nuclide_composition: dict[Nuclide, float]  # Non-numba
-    element_composition: dict[Element, float]  # Non-numba
+    name: str
+    temperature: float
+    fissionable: bool
+    has_neutron_multigroup: bool
+
+    nuclide_composition: dict[Nuclide, float]  # Non-Numba
+    element_composition: dict[Element, float]  # Non-Numba
+    neutron_multigroup: NeutronMultigroup
 
     nuclides: list[Nuclide]
     elements: list[Element]
@@ -122,107 +103,148 @@ class Material(MaterialBase):
     def __init__(
         self,
         name: str = "",
-        nuclide_composition: dict[str, float] = {},
-        element_composition: dict[str, float] = {},
+        nuclide_composition: dict[str, float] | NoneType = None,
+        element_composition: dict[str, float] | NoneType = None,
         temperature: float = 293.6,
-    ):
-        super().__init__(name)
+        neutron_multigroup: NeutronMultigroup | NoneType = None,
+    ) -> None:
+        super().__init__()
 
-        # Temperature
-        self.temperature = temperature
+        # Normalize optional compositions without mutable argument defaults
+        nuclide_composition = nuclide_composition or {}
+        element_composition = element_composition or {}
 
-        # Check that only one composition is supplied
-        if len(nuclide_composition) > 0 and len(element_composition) > 0:
+        # Require one valid material-data representation
+        if nuclide_composition and element_composition:
             print_error(
-                "Cannot specify both nuclide_composition and element_composition"
+                "Cannot specify both nuclide_composition and element_composition."
             )
-
-        if len(nuclide_composition) == 0 and len(element_composition) == 0:
+        if (
+            not nuclide_composition
+            and not element_composition
+            and neutron_multigroup is None
+        ):
+            print_error(
+                "Material requires nuclide_composition, element_composition, "
+                "or neutron_multigroup."
+            )
+        if neutron_multigroup is not None and not isinstance(
+            neutron_multigroup, NeutronMultigroup
+        ):
+            print_error("neutron_multigroup must be a NeutronMultigroup object.")
+        native_composition_supplied = bool(nuclide_composition or element_composition)
+        if (
+            native_composition_supplied
+            and neutron_multigroup is not None
+            and neutron_multigroup.G > 0
+            and not neutron_multigroup.has_energy_grid
+        ):
             print_error(
-                "Must specify either nuclide_composition or element_composition"
+                "Material with both a native composition and neutron_multigroup "
+                "requires neutron_multigroup.energy_grid."
             )
 
-        # Create lightweight composition objects. Library data and simulation
-        # registration are deferred to each object's compilation.
+        # Initialize shared material state
+        self.name = name or "(Unnamed material)"
+        self.temperature = float(temperature)
+
+        # Use a zero-group placeholder until compilation can select ID 0
+        self.neutron_multigroup = (
+            neutron_multigroup
+            if neutron_multigroup is not None
+            else NeutronMultigroup()
+        )
+        self.has_neutron_multigroup = self.neutron_multigroup.G > 0
+        self.fissionable = self.neutron_multigroup.fissionable
+
+        # Create lightweight native-composition objects without loading data
         nearest_temperature = _get_supported_temperature(self.temperature)
         self.nuclide_composition = {
-            Nuclide(name, nearest_temperature): density
+            Nuclide(name, nearest_temperature): float(density)
             for name, density in nuclide_composition.items()
         }
         self.element_composition = {
-            Element(name): density for name, density in element_composition.items()
+            Element(name): float(density)
+            for name, density in element_composition.items()
         }
 
-        # Numba representations of the compositions
+        # Initialize the packed native-composition representation
         self.nuclides = list(self.nuclide_composition)
         self.elements = list(self.element_composition)
         self.nuclide_densities = np.asarray(
-            list(self.nuclide_composition.values()), dtype=float
+            list(self.nuclide_composition.values()), dtype=float64
         )
         self.element_densities = np.asarray(
-            list(self.element_composition.values()), dtype=float
+            list(self.element_composition.values()), dtype=float64
         )
 
     def _compile_into_simulation(self, simulation) -> bool:
-        """Canonicalize the composition and register it with the simulation."""
-        # Skip composition work when this material is already compiled
+        """Canonicalize owned data and register the unified material."""
+        # Skip canonicalization when this material is already compiled
         if self.compile_ID == simulation.compile_ID:
             return False
 
-        # Resolve composition objects before generic member traversal so only
-        # canonical simulation objects are registered.
+        # Resolve native composition objects before generic member traversal
         nuclide_composition = {}
         element_composition = {}
 
-        # Replace locally created elements with canonical simulation objects
         for element, density in self.element_composition.items():
             element = _get_or_create_element(element.name, simulation, element)
             element_composition[element] = density
 
-        # Replace locally created nuclides with canonical simulation objects
         for nuclide, density in self.nuclide_composition.items():
             nuclide = _get_or_create_nuclide(
                 nuclide.name, nuclide.temperature, simulation, nuclide
             )
             nuclide_composition[nuclide] = density
 
-        # Synchronize the packed composition fields with the canonical objects
+        # Synchronize packed fields with canonical native objects
         self.nuclide_composition = nuclide_composition
         self.element_composition = element_composition
         self.nuclides = list(nuclide_composition)
         self.elements = list(element_composition)
         self.nuclide_densities = np.asarray(
-            list(nuclide_composition.values()), dtype=float
+            list(nuclide_composition.values()), dtype=float64
         )
         self.element_densities = np.asarray(
-            list(element_composition.values()), dtype=float
+            list(element_composition.values()), dtype=float64
         )
 
-        # Register the material and compile its canonical composition members
+        # Point absent multigroup data to the reserved neutron model
+        if self.neutron_multigroup.G == 0:
+            self.neutron_multigroup = simulation.neutron_multigroup[0]
+        self.has_neutron_multigroup = self.neutron_multigroup.G > 0
+
+        # Register the material, then compile only canonical owned members
         if not super()._compile_into_simulation(simulation):
             return False
 
-        # Resolve derived properties after nuclide library data has been loaded
-        self.fissionable = any(nuclide.fissionable for nuclide in self.nuclides)
-
+        # Resolve fissionability from every available neutron representation
+        self.fissionable = self.neutron_multigroup.fissionable or any(
+            nuclide.fissionable for nuclide in self.nuclides
+        )
         return True
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
-
+        text += f"  - Name: {self.name}\n"
+        text += f"  - Fissionable: {self.fissionable}\n"
         text += f"  - Temperature: {self.temperature} K\n"
-        if len(self.nuclide_composition) > 0:
-            text += f"  - Nuclide composition [atoms/barn-cm]\n"
-            for nuclide in self.nuclide_composition.keys():
-                text += (
-                    f"    - {nuclide.name:<5} | {self.nuclide_composition[nuclide]}\n"
-                )
-        if len(self.element_composition) > 0:
-            text += f"  - Element composition [atoms/barn-cm]\n"
-            for element in self.element_composition.keys():
-                text += (
-                    f"    - {element.name:<5} | {self.element_composition[element]}\n"
-                )
+
+        if self.nuclide_composition:
+            text += "  - Nuclide composition [atoms/barn-cm]\n"
+            for nuclide, density in self.nuclide_composition.items():
+                text += f"    - {nuclide.name:<5} | {density}\n"
+
+        if self.element_composition:
+            text += "  - Element composition [atoms/barn-cm]\n"
+            for element, density in self.element_composition.items():
+                text += f"    - {element.name:<5} | {density}\n"
+
+        if self.neutron_multigroup.G > 0:
+            text += "  - Neutron multigroup model\n"
+            text += f"    - G: {self.neutron_multigroup.G}\n"
+            text += f"    - J: {self.neutron_multigroup.J}\n"
         return text
 
 
@@ -231,299 +253,43 @@ def __repr__(self):
 
 
 # ======================================================================================
-# Multigroup material
+# Native-composition helpers
 # ======================================================================================
 
 
-class MaterialMG(MaterialBase):
-    """Define a material with multigroup neutron data.
-
-    Parameters
-    ----------
-    name : str, optional
-        User-facing material name.
-    capture : ndarray, optional
-        Capture macroscopic cross section by incident group.
-    scatter : ndarray, optional
-        Scattering production matrix in ``[outgoing_group, incident_group]``
-        order. Column sums define the scattering cross section.
-    fission : ndarray, optional
-        Fission macroscopic cross section by incident group.
-    nu_s : ndarray, optional
-        Mean number of neutrons emitted per scattering event by incident group.
-    nu_p : ndarray, optional
-        Prompt-fission neutron yield by incident group.
-    nu_d : ndarray, optional
-        Delayed-fission neutron yield in
-        ``[delayed_group, incident_group]`` order.
-    chi_p : ndarray, optional
-        Prompt-fission spectrum. A one-dimensional spectrum is shared by all
-        incident groups; a matrix uses
-        ``[outgoing_group, incident_group]`` order.
-    chi_d : ndarray, optional
-        Delayed-fission spectrum in ``[outgoing_group, delayed_group]`` order.
-    speed : ndarray, optional
-        Particle speed by energy group.
-    decay_rate : ndarray, optional
-        Delayed-neutron precursor decay rate by delayed group.
-
-    Notes
-    -----
-    At least one of ``capture``, ``scatter``, or ``fission`` is required and
-    determines the number of energy groups. Cross sections are expected in
-    inverse centimetres.
-
-    Examples
-    --------
-    Define a one-group purely absorbing material:
-
-    >>> import numpy as np
-    >>> import mcdc
-    >>> absorber = mcdc.MaterialMG(
-    ...     name="Absorber",
-    ...     capture=np.array([1.0]),
-    ... )
-
-    Define a two-group scattering material:
-
-    >>> scatterer = mcdc.MaterialMG(
-    ...     name="Scatterer",
-    ...     capture=np.array([0.05, 0.10]),
-    ...     scatter=np.array([
-    ...         [0.70, 0.10],
-    ...         [0.20, 0.50],
-    ...     ]),
-    ...     nu_s=np.array([1.0, 1.0]),
-    ... )
-
-    Define a one-group prompt-fission material:
-
-    >>> fuel = mcdc.MaterialMG(
-    ...     name="Fuel",
-    ...     capture=np.array([0.10]),
-    ...     fission=np.array([0.20]),
-    ...     nu_p=np.array([2.50]),
-    ... )
-    """
-
-    # MC/DC framework metadata
-    label = "multigroup_material"
-    sub_type = MATERIAL_MG
-
-    G: int
-    J: int
-    mgxs_speed: Annotated[NDArray[float64], ("G",)]
-    mgxs_decay_rate: Annotated[NDArray[float64], ("J",)]
-    mgxs_capture: Annotated[NDArray[float64], ("G",)]
-    mgxs_scatter: Annotated[NDArray[float64], ("G",)]
-    mgxs_fission: Annotated[NDArray[float64], ("G",)]
-    mgxs_total: Annotated[NDArray[float64], ("G",)]
-    mgxs_nu_s: Annotated[NDArray[float64], ("G",)]
-    mgxs_nu_p: Annotated[NDArray[float64], ("G",)]
-    mgxs_nu_d: Annotated[NDArray[float64], ("G", "J")]
-    mgxs_nu_d_total: Annotated[NDArray[float64], ("G",)]
-    mgxs_nu_f: Annotated[NDArray[float64], ("G",)]
-    mgxs_chi_s: Annotated[NDArray[float64], ("G", "G")]
-    mgxs_chi_p: Annotated[NDArray[float64], ("G", "G")]
-    mgxs_chi_d: Annotated[NDArray[float64], ("J", "G")]
-
-    def __init__(
-        self,
-        name: str = "",
-        capture: NDArray[float64] | NoneType = None,
-        scatter: NDArray[float64] | NoneType = None,
-        fission: NDArray[float64] | NoneType = None,
-        nu_s: NDArray[float64] | NoneType = None,
-        nu_p: NDArray[float64] | NoneType = None,
-        nu_d: NDArray[float64] | NoneType = None,
-        chi_p: NDArray[float64] | NoneType = None,
-        chi_d: NDArray[float64] | NoneType = None,
-        speed: NDArray[float64] | NoneType = None,
-        decay_rate: NDArray[float64] | NoneType = None,
-    ):
-        super().__init__(name)
-
-        # Energy group size
-        if capture is not None:
-            G = len(capture)
-        elif scatter is not None:
-            G = len(scatter)
-        elif fission is not None:
-            G = len(fission)
-        else:
-            G = 0
-            print_error("Need to supply capture, scatter, or fission for MaterialMG")
-        self.G = G
-
-        # Delayed group size
-        J = 0
-        if nu_d is not None:
-            J = len(nu_d)
-        self.J = J
-
-        # Allocate the attributes
-        self.mgxs_speed = np.ones(G)
-        self.mgxs_decay_rate = np.ones(J) * np.inf
-        self.mgxs_capture = np.zeros(G)
-        self.mgxs_scatter = np.zeros(G)
-        self.mgxs_fission = np.zeros(G)
-        self.mgxs_total = np.zeros(G)
-        self.mgxs_nu_s = np.ones(G)
-        self.mgxs_nu_p = np.zeros(G)
-        self.mgxs_nu_d = np.zeros([G, J])
-        self.mgxs_nu_d_total = np.zeros([G])
-        self.mgxs_nu_f = np.zeros(G)
-        self.mgxs_chi_s = np.zeros([G, G])
-        self.mgxs_chi_p = np.zeros([G, G])
-        self.mgxs_chi_d = np.zeros([J, G])
-
-        # Speed (vector of size G)
-        if speed is not None:
-            self.mgxs_speed = speed
-
-        # Decay constant (vector of size J)
-        if decay_rate is not None:
-            self.mgxs_decay_rate = decay_rate
-
-        # Cross-sections (vector of size G)
-        if capture is not None:
-            self.mgxs_capture = capture
-        if scatter is not None:
-            self.mgxs_scatter = np.sum(scatter, 0)
-        if fission is not None:
-            self.mgxs_fission = fission
-            self.fissionable = True
-        self.mgxs_total = self.mgxs_capture + self.mgxs_scatter + self.mgxs_fission
-
-        # Scattering multiplication (vector of size G)
-        if nu_s is not None:
-            self.mgxs_nu_s = nu_s
-
-        # Check if nu_p or nu_d is not provided, give fission
-        if fission is not None:
-            if nu_p is None and nu_d is None:
-                print_error("Need to supply nu_p or nu_d for fissionable MaterialMG")
-
-        # Prompt fission production (vector of size G)
-        if nu_p is not None:
-            self.mgxs_nu_p = nu_p
-
-        # Delayed fission production (matrix of size GxJ)
-        if nu_d is not None:
-            # Transpose: [dg, gin] -> [gin, dg]
-            self.mgxs_nu_d = np.swapaxes(nu_d, 0, 1)[:, :]
-        self.mgxs_nu_d_total = np.sum(self.mgxs_nu_d, axis=1)
-
-        # Total fission production (vector of size G)
-        self.mgxs_nu_f = np.zeros_like(self.mgxs_nu_p)
-        self.mgxs_nu_f += self.mgxs_nu_p
-        for j in range(J):
-            self.mgxs_nu_f += self.mgxs_nu_d[:, j]
-
-        # Scattering spectrum (matrix of size GxG)
-        if scatter is not None:
-            # Transpose: [gout, gin] -> [gin, gout]
-            self.mgxs_chi_s = np.swapaxes(scatter, 0, 1)[:, :]
-            for g in range(G):
-                if self.mgxs_scatter[g] > 0.0:
-                    self.mgxs_chi_s[g, :] /= self.mgxs_scatter[g]
-
-        # Prompt fission spectrum (matrix of size GxG)
-        if nu_p is not None:
-            if G == 1:
-                self.mgxs_chi_p[:, :] = np.array([[1.0]])
-            elif chi_p is None:
-                print_error("Need to supply chi_p if nu_p is provided and G > 1")
-            else:
-                # Convert 1D spectrum to 2D
-                if chi_p.ndim == 1:
-                    tmp = np.zeros((G, G))
-                    for g in range(G):
-                        tmp[:, g] = chi_p
-                    chi_p = tmp
-                # Transpose: [gout, gin] -> [gin, gout]
-                self.mgxs_chi_p[:, :] = np.swapaxes(chi_p, 0, 1)[:, :]
-                # Normalize
-                for g in range(G):
-                    if np.sum(self.mgxs_chi_p[g, :]) > 0.0:
-                        self.mgxs_chi_p[g, :] /= np.sum(self.mgxs_chi_p[g, :])
-
-        # Delayed fission spectrum (matrix of size JxG)
-        if nu_d is not None:
-            if G == 1:
-                self.mgxs_chi_d = np.ones([J, G])
-            else:
-                if chi_d is None:
-                    print_error("Need to supply chi_d if nu_d is provided and G > 1")
-                else:
-                    # Transpose: [gout, dg] -> [dg, gout]
-                    self.mgxs_chi_d = np.swapaxes(chi_d, 0, 1)[:, :]
-            # Normalize
-            for dg in range(J):
-                if np.sum(self.mgxs_chi_d[dg, :]) > 0.0:
-                    self.mgxs_chi_d[dg, :] /= np.sum(self.mgxs_chi_d[dg, :])
-
-    def __repr__(self):
-        text = super().__repr__()
-
-        text += f"  - Multigroup data\n"
-        text += f"    - G: {self.G}\n"
-        text += f"    - J: {self.J}\n"
-        text += f"    - Sigma_c {print_1d_array(self.mgxs_capture)}\n"
-        text += f"    - Sigma_s {print_1d_array(self.mgxs_scatter)}\n"
-        text += f"    - Sigma_f {print_1d_array(self.mgxs_fission)}\n"
-        text += f"    - nu_s {print_1d_array(self.mgxs_nu_s)}\n"
-        text += f"    - nu_p {print_1d_array(self.mgxs_nu_p)}\n"
-        text += f"    - nu_d {print_1d_array(self.mgxs_nu_d.flatten())}\n"
-        text += f"    - chi_s {print_1d_array(self.mgxs_chi_s.flatten())}\n"
-        text += f"    - chi_fp {print_1d_array(self.mgxs_chi_p.flatten())}\n"
-        text += f"    - chi_fd {print_1d_array(self.mgxs_chi_d.flatten())}\n"
-        text += f"    - speed {print_1d_array(self.mgxs_speed)}\n"
-        text += f"    - lambda {print_1d_array(self.mgxs_decay_rate)}\n"
-        return text
-
-
 def set_nuclides_from_elements(material, simulation):
     """Expand an elemental composition and register its natural isotopes."""
-
     material.nuclides = []
     material.nuclide_composition = {}
     nuclide_densities = []
 
-    # Get supported temperature
+    # Select the nearest supported native-data temperature
     nearest_temperature = _get_supported_temperature(material.temperature)
 
+    # Expand each natural element into its normalized isotopic composition
     for element, element_density in material.element_composition.items():
-        # To make sure that the abundance is normalized
-        norm = 0.0
-        for abundance in ISOTOPIC_ABUNDANCE[element.name].values():
-            norm += abundance
+        norm = sum(ISOTOPIC_ABUNDANCE[element.name].values())
 
-        # Loop over the nuclide composition
         for nuclide_name, abundance in ISOTOPIC_ABUNDANCE[element.name].items():
             nuclide = _get_or_create_nuclide(
                 nuclide_name, nearest_temperature, simulation
             )
             nuclide._compile_into_simulation(simulation)
 
-            # Calculate nuclide density
             nuclide_density = element_density * abundance / norm
-
-            # Register the nuclide composition
             material.nuclides.append(nuclide)
             nuclide_densities.append(nuclide_density)
             material.nuclide_composition[nuclide] = nuclide_density
 
-    material.nuclide_densities = np.array(nuclide_densities)
+    material.nuclide_densities = np.asarray(nuclide_densities, dtype=float64)
 
 
 def set_elements_from_nuclides(material, simulation):
     """Collapse a nuclide composition and register its elements."""
-
     material.elements = []
     material.element_composition = {}
 
-    # Get the list of the element names
+    # Gather the unique element names represented by the nuclides
     element_names = []
     for nuclide in material.nuclides:
         element_name = nuclide.name[:2]
@@ -531,23 +297,18 @@ def set_elements_from_nuclides(material, simulation):
             element_name = element_name[0]
         if element_name not in element_names:
             element_names.append(element_name)
-    element_densities = np.zeros(len(element_names))
+    element_densities = np.zeros(len(element_names), dtype=float64)
 
-    # Iterate over all named elements
+    # Accumulate each element's density and register its canonical object
     for i, element_name in enumerate(element_names):
         element = _get_or_create_element(element_name, simulation)
         element._compile_into_simulation(simulation)
-
         material.elements.append(element)
 
-        # Iterate over all nuclides to get the total density
         density = 0.0
         for nuclide, nuclide_density in material.nuclide_composition.items():
-            # Skip if non-isotope
             if nuclide.name[: len(element_name)] != element_name:
                 continue
-
-            # Accumulate density
             density += nuclide_density
 
         element_densities[i] = density
@@ -571,15 +332,11 @@ def _get_or_create_nuclide(nuclide_name, temperature, simulation, candidate=None
     for nuclide in simulation.nuclides:
         if nuclide.name == nuclide_name and nuclide.temperature == temperature:
             return nuclide
-
     return candidate or Nuclide(nuclide_name, temperature)
 
 
 def update_fissionable_from_nuclides(material):
-    """Update a material's fissionable flag from its constituent nuclides."""
-
-    material.fissionable = False
-    for nuclide in material.nuclides:
-        if nuclide.fissionable:
-            material.fissionable = True
-            break
+    """Update fissionability from native and multigroup neutron data."""
+    material.fissionable = material.neutron_multigroup.fissionable or any(
+        nuclide.fissionable for nuclide in material.nuclides
+    )
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index c2f051dce..1fc88f88b 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -5,8 +5,8 @@
     from mcdc.object_.cell import Cell, Region
     from mcdc.object_.element import Element
     from mcdc.object_.electron_reaction import ElectronReactionBase
-    from mcdc.object_.material import MaterialBase
-    from mcdc.object_.mgxs import MGXS
+    from mcdc.object_.material import Material
+    from mcdc.object_.transport_model import NeutronMultigroup
     from mcdc.object_.nuclide import Nuclide
     from mcdc.object_.neutron_reaction import NeutronReactionBase
     from mcdc.object_.source import Source
@@ -115,8 +115,8 @@ class Simulation(MCDCBase):
     electron_reactions: list[ElectronReactionBase]
     nuclides: list[Nuclide]
     elements: list[Element]
-    materials: list[MaterialBase]
-    mgxs: list[MGXS]
+    materials: list[Material]
+    neutron_multigroup: list[NeutronMultigroup]
     sources: list[Source]
 
     # Geometry
@@ -295,7 +295,7 @@ def _reset_model(self) -> None:
         self.nuclides = []
         self.elements = []
         self.materials = []
-        self.mgxs = []
+        self.neutron_multigroup = []
 
         # Geometry
         self.surfaces = []
@@ -316,8 +316,6 @@ def _finalize_compilation(self) -> None:
         has already completed.
         """
         from mcdc.object_.material import (
-            Material,
-            MaterialMG,
             set_elements_from_nuclides,
             set_nuclides_from_elements,
             update_fissionable_from_nuclides,
@@ -332,11 +330,17 @@ def _finalize_compilation(self) -> None:
 
         # Complete native-material compositions for the transported particles
         for material in self.materials:
-            if not isinstance(material, Material):
-                continue
-            if settings.neutron_transport and len(material.nuclides) == 0:
+            if (
+                settings.neutron_transport
+                and material.element_composition
+                and len(material.nuclides) == 0
+            ):
                 set_nuclides_from_elements(material, self)
-            if settings.electron_transport and len(material.elements) == 0:
+            if (
+                settings.electron_transport
+                and material.nuclide_composition
+                and len(material.elements) == 0
+            ):
                 set_elements_from_nuclides(material, self)
 
         # Load the physics data required by the completed material model
@@ -344,18 +348,17 @@ def _finalize_compilation(self) -> None:
             for nuclide in self.nuclides:
                 nuclide.set_neutron_data(self)
             for material in self.materials:
-                if isinstance(material, Material):
-                    update_fissionable_from_nuclides(material)
+                update_fissionable_from_nuclides(material)
 
         if settings.electron_transport:
             for element in self.elements:
                 element.set_electron_data(self)
 
-        # Determine the neutron physics representation
-        if len(self.materials) == 0:
-            settings.neutron_multigroup_mode = True
-        else:
-            settings.neutron_multigroup_mode = isinstance(self.materials[0], MaterialMG)
+        # Preserve the current full-MG transport switch until collision-level
+        # dispatch can select neutron multigroup physics by material and energy.
+        settings.neutron_multigroup_mode = len(self.materials) == 0 or all(
+            material.neutron_multigroup.G > 0 for material in self.materials
+        )
 
         # Derive tally shapes that depend on simulation-wide settings
         if settings.use_census_based_tally:
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index d7f89a4e9..1f1adafe9 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -102,7 +102,9 @@ class Tally(MCDCPolymorphic):
 
     Filter a track-length tally by cell, angle, and time:
 
-    >>> material = mcdc.MaterialMG(capture=np.array([1.0]))
+    >>> material = mcdc.Material(
+    ...     neutron_multigroup=mcdc.NeutronMultigroup(capture=np.array([1.0]))
+    ... )
     >>> lower = mcdc.Surface.PlaneZ(z=0.0)
     >>> upper = mcdc.Surface.PlaneZ(z=10.0)
     >>> cell = mcdc.Cell(region=+lower & -upper, fill=material)
@@ -395,7 +397,7 @@ def _compile_into_simulation(self, simulation) -> bool:
 
         # Resolve the "all_groups" energy filter and resize its tally bins.
         if self.energy_all_groups:
-            G = simulation.materials[0].G
+            G = simulation.materials[0].neutron_multigroup.G
             self.energy = np.linspace(0, G, G + 1) - 0.5
             shape = list(self.bin_shape)
             shape[2] = G
diff --git a/mcdc/object_/mgxs.py b/mcdc/object_/transport_model.py
similarity index 73%
rename from mcdc/object_/mgxs.py
rename to mcdc/object_/transport_model.py
index 39af17750..b73d0cc9b 100644
--- a/mcdc/object_/mgxs.py
+++ b/mcdc/object_/transport_model.py
@@ -6,32 +6,32 @@
 from numpy.typing import ArrayLike, NDArray
 
 from mcdc.constant import (
-    MULTIGROUP_NEUTRON_ENERGY_MIDPOINT,
-    MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG,
-    MULTIGROUP_NEUTRON_ENERGY_UNIFORM,
-    MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
+    NEUTRON_MULTIGROUP_ENERGY_MIDPOINT,
+    NEUTRON_MULTIGROUP_ENERGY_MIDPOINT_LOG,
+    NEUTRON_MULTIGROUP_ENERGY_UNIFORM,
+    NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG,
 )
 from mcdc.object_.base import MCDCObject
 from mcdc.print_ import print_1d_array, print_error
 
-_ENERGY_REPRESENTATIONS = {
-    "midpoint": MULTIGROUP_NEUTRON_ENERGY_MIDPOINT,
-    "log_midpoint": MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG,
-    "uniform": MULTIGROUP_NEUTRON_ENERGY_UNIFORM,
-    "log_uniform": MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
+_NEUTRON_MULTIGROUP_ENERGY_REPRESENTATIONS = {
+    "midpoint": NEUTRON_MULTIGROUP_ENERGY_MIDPOINT,
+    "log_midpoint": NEUTRON_MULTIGROUP_ENERGY_MIDPOINT_LOG,
+    "uniform": NEUTRON_MULTIGROUP_ENERGY_UNIFORM,
+    "log_uniform": NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG,
 }
-_LOG_ENERGY_REPRESENTATIONS = {
-    MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG,
-    MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
+_NEUTRON_MULTIGROUP_LOG_ENERGY_REPRESENTATIONS = {
+    NEUTRON_MULTIGROUP_ENERGY_MIDPOINT_LOG,
+    NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG,
 }
 
 
-class MGXS(MCDCObject):
-    """Store multigroup cross sections for one particle species.
+class NeutronMultigroup(MCDCObject):
+    """Define a multigroup transport model for neutrons.
 
-    ``MGXS`` is particle agnostic. It stores groupwise interaction data; the
-    field through which a material references it determines the transported
-    particle species.
+    Materials may use ``NeutronMultigroup`` alone for multigroup transport or
+    alongside a native composition over the energy range defined by
+    ``energy_grid``.
 
     Parameters
     ----------
@@ -48,7 +48,7 @@ class MGXS(MCDCObject):
         ``(G,)``. Supplying fission requires at least one of ``nu_p`` or
         ``nu_d``.
     nu_s : array_like of float, optional
-        Mean number of particles produced per scattering event in each
+        Mean number of neutrons produced per scattering event in each
         incoming group, with shape ``(G,)``. Defaults to one.
     nu_p : array_like of float, optional
         Mean prompt-fission yield for each incoming group, with shape
@@ -66,7 +66,7 @@ class MGXS(MCDCObject):
         Delayed-fission spectrum with shape ``(G, J)``, indexed as
         ``chi_d[g_out, j]``. Required when ``nu_d`` is supplied and ``G > 1``.
     speed : array_like of float, optional
-        Particle speed in each energy group, with shape ``(G,)``. Defaults to
+        Neutron speed in each energy group, with shape ``(G,)``. Defaults to
         one.
     decay_rate : array_like of float, optional
         Decay constant for each delayed precursor group, with shape ``(J,)``.
@@ -81,15 +81,15 @@ class MGXS(MCDCObject):
         policies select the arithmetic or geometric midpoint; uniform policies
         sample uniformly in energy or log-energy. The default is
         ``"log_midpoint"``. Logarithmic policies require positive boundaries.
-        The corresponding ``MULTIGROUP_NEUTRON_ENERGY_*`` integer constants
+        The corresponding ``NEUTRON_MULTIGROUP_ENERGY_*`` integer constants
         are also accepted.
 
     Notes
     -----
     ``G`` is inferred from ``capture``, ``scatter``, or ``fission``. Calling
-    ``MGXS()`` without any cross sections creates the reserved zero-group
-    placeholder used by materials without multigroup data. Cross sections are
-    macroscopic and use inverse-length units.
+    ``NeutronMultigroup()`` without any cross sections creates the reserved
+    zero-group placeholder used by materials without multigroup data. Cross
+    sections are macroscopic and use inverse-length units.
 
     Examples
     --------
@@ -97,17 +97,47 @@ class MGXS(MCDCObject):
 
     >>> import mcdc
     >>> import numpy as np
-    >>> mgxs = mcdc.MGXS(
+    >>> neutron_multigroup = mcdc.NeutronMultigroup(
     ...     capture=np.array([1.0 / 3.0]),
     ...     scatter=np.array([[1.0 / 3.0]]),
     ...     fission=np.array([1.0 / 3.0]),
     ...     nu_p=np.array([2.3]),
     ...     energy_grid=np.array([1.0e-5, 20.0e6]),
     ... )
+
+    Construct data with two energy groups. Scattering is indexed by outgoing
+    then incoming group:
+
+    >>> two_group = mcdc.NeutronMultigroup(
+    ...     capture=np.array([0.1, 0.2]),
+    ...     scatter=np.array([
+    ...         [1.0, 2.0],
+    ...         [3.0, 0.0],
+    ...     ]),
+    ...     nu_s=np.array([1.1, 1.2]),
+    ...     energy_grid=np.array([1.0e-5, 1.0, 20.0e6]),
+    ... )
+
+    Construct two-group fission data with two delayed precursor groups. The
+    delayed yield is indexed by precursor then incoming energy group, while
+    the delayed spectrum is indexed by outgoing energy then precursor group:
+
+    >>> multiple_precursors = mcdc.NeutronMultigroup(
+    ...     fission=np.array([0.2, 0.3]),
+    ...     nu_d=np.array([
+    ...         [0.1, 0.2],
+    ...         [0.3, 0.4],
+    ...     ]),
+    ...     chi_d=np.array([
+    ...         [1.0, 3.0],
+    ...         [3.0, 1.0],
+    ...     ]),
+    ...     decay_rate=np.array([0.01, 0.02]),
+    ... )
     """
 
     # MC/DC framework metadata
-    label = "mgxs"
+    label = "neutron_multigroup"
 
     G: int
     J: int
@@ -200,15 +230,17 @@ def __init__(
 
         # Validate relationships between fission yields and spectra
         if fission is not None and nu_p is None and nu_d is None:
-            print_error("Fission MGXS requires nu_p or nu_d.")
+            print_error("NeutronMultigroup fission data requires nu_p or nu_d.")
         if fission is None and (nu_p is not None or nu_d is not None):
-            print_error("MGXS fission yields require fission cross sections.")
+            print_error(
+                "NeutronMultigroup fission yields require fission cross sections."
+            )
         if chi_p is not None and nu_p is None:
-            print_error("MGXS chi_p requires nu_p.")
+            print_error("NeutronMultigroup chi_p requires nu_p.")
         if chi_d is not None and nu_d is None:
-            print_error("MGXS chi_d requires nu_d.")
+            print_error("NeutronMultigroup chi_d requires nu_d.")
         if decay_rate is not None and nu_d is None:
-            print_error("MGXS decay_rate requires nu_d.")
+            print_error("NeutronMultigroup decay_rate requires nu_d.")
 
         # Resolve the energy grid and continuous-energy reconstruction policy
         self.energy_representation = _resolve_energy_representation(
@@ -219,15 +251,18 @@ def __init__(
             self.energy_grid = np.zeros(self.G + 1, dtype=float64)
         else:
             if not np.all(np.isfinite(energy_grid)):
-                print_error("MGXS energy grid entries must be finite.")
+                print_error("NeutronMultigroup energy grid entries must be finite.")
             if np.any(np.diff(energy_grid) <= 0.0):
-                print_error("MGXS energy grid must be strictly increasing.")
+                print_error(
+                    "NeutronMultigroup energy grid must be strictly increasing."
+                )
             if (
-                self.energy_representation in _LOG_ENERGY_REPRESENTATIONS
+                self.energy_representation
+                in _NEUTRON_MULTIGROUP_LOG_ENERGY_REPRESENTATIONS
                 and energy_grid[0] <= 0.0
             ):
                 print_error(
-                    "MGXS logarithmic energy representation requires positive "
+                    "NeutronMultigroup logarithmic energy representation requires positive "
                     "energy boundaries."
                 )
             self.energy_grid = energy_grid
@@ -268,7 +303,7 @@ def __init__(
             if self.G == 1:
                 self.chi_p[:] = 1.0
             elif chi_p is None:
-                print_error("MGXS with nu_p and G > 1 requires chi_p.")
+                print_error("NeutronMultigroup with nu_p and G > 1 requires chi_p.")
             else:
                 if chi_p.ndim == 1:
                     chi_p = np.tile(chi_p[:, np.newaxis], (1, self.G))
@@ -280,7 +315,7 @@ def __init__(
             if self.G == 1:
                 self.chi_d[:] = 1.0
             elif chi_d is None:
-                print_error("MGXS with nu_d and G > 1 requires chi_d.")
+                print_error("NeutronMultigroup with nu_d and G > 1 requires chi_d.")
             else:
                 self.chi_d = np.swapaxes(chi_d, 0, 1).copy()
                 active_delayed_groups = np.any(nu_d > 0.0, axis=1)
@@ -313,7 +348,7 @@ def _as_array(name, value):
     try:
         return np.asarray(value, dtype=float64)
     except (TypeError, ValueError):
-        print_error(f"MGXS {name} must be numeric array-like data.")
+        print_error(f"NeutronMultigroup {name} must be numeric array-like data.")
 
 
 def _infer_group_count(capture, scatter, fission) -> int:
@@ -323,9 +358,13 @@ def _infer_group_count(capture, scatter, fission) -> int:
     if defining is None:
         return 0
     if defining.ndim == 0:
-        print_error("MGXS cross sections must be arrays with an energy-group axis.")
+        print_error(
+            "NeutronMultigroup cross sections must be arrays with an energy-group axis."
+        )
     if defining.shape[0] == 0:
-        print_error("MGXS cross sections must define at least one energy group.")
+        print_error(
+            "NeutronMultigroup cross sections must define at least one energy group."
+        )
     return defining.shape[0]
 
 
@@ -334,16 +373,20 @@ def _infer_delayed_group_count(nu_d, G: int) -> int:
     if nu_d is None:
         return 0
     if nu_d.ndim != 2:
-        print_error(f"MGXS nu_d must have shape (J, G); got {nu_d.shape}.")
+        print_error(f"NeutronMultigroup nu_d must have shape (J, G); got {nu_d.shape}.")
     if nu_d.shape[1] != G:
-        print_error(f"MGXS nu_d must have shape (J, G) with G = {G}; got {nu_d.shape}.")
+        print_error(
+            f"NeutronMultigroup nu_d must have shape (J, G) with G = {G}; got {nu_d.shape}."
+        )
     return nu_d.shape[0]
 
 
 def _validate_shape(name, array, expected) -> None:
-    """Require an optional array to have its declared MGXS shape."""
+    """Require an optional array to have its declared NeutronMultigroup shape."""
     if array is not None and array.shape != expected:
-        print_error(f"MGXS {name} must have shape {expected}; got {array.shape}.")
+        print_error(
+            f"NeutronMultigroup {name} must have shape {expected}; got {array.shape}."
+        )
 
 
 def _validate_prompt_spectrum_shape(chi_p, G: int) -> None:
@@ -352,7 +395,7 @@ def _validate_prompt_spectrum_shape(chi_p, G: int) -> None:
         return
     if chi_p.shape not in ((G,), (G, G)):
         print_error(
-            f"MGXS chi_p must have shape ({G},) or ({G}, {G}); got {chi_p.shape}."
+            f"NeutronMultigroup chi_p must have shape ({G},) or ({G}, {G}); got {chi_p.shape}."
         )
 
 
@@ -361,7 +404,7 @@ def _validate_nonnegative(name, array) -> None:
     if array is None:
         return
     if not np.all(np.isfinite(array)) or np.any(array < 0.0):
-        print_error(f"MGXS {name} entries must be finite and nonnegative.")
+        print_error(f"NeutronMultigroup {name} entries must be finite and nonnegative.")
 
 
 def _validate_positive(name, array) -> None:
@@ -369,7 +412,7 @@ def _validate_positive(name, array) -> None:
     if array is None:
         return
     if not np.all(np.isfinite(array)) or np.any(array <= 0.0):
-        print_error(f"MGXS {name} entries must be finite and positive.")
+        print_error(f"NeutronMultigroup {name} entries must be finite and positive.")
 
 
 def _validate_decay_rate(array) -> None:
@@ -377,28 +420,28 @@ def _validate_decay_rate(array) -> None:
     if array is None:
         return
     if np.any(np.isnan(array)) or np.any(array < 0.0):
-        print_error("MGXS decay_rate entries must be nonnegative.")
+        print_error("NeutronMultigroup decay_rate entries must be nonnegative.")
 
 
 def _resolve_energy_representation(policy) -> int:
     """Resolve a public reconstruction policy name or integer code."""
     if isinstance(policy, str):
-        if policy not in _ENERGY_REPRESENTATIONS:
-            expected = ", ".join(_ENERGY_REPRESENTATIONS)
+        if policy not in _NEUTRON_MULTIGROUP_ENERGY_REPRESENTATIONS:
+            expected = ", ".join(_NEUTRON_MULTIGROUP_ENERGY_REPRESENTATIONS)
             print_error(
-                f"Unknown MGXS energy representation {policy!r}. "
+                f"Unknown NeutronMultigroup energy representation {policy!r}. "
                 f"Expected one of: {expected}."
             )
-        return _ENERGY_REPRESENTATIONS[policy]
+        return _NEUTRON_MULTIGROUP_ENERGY_REPRESENTATIONS[policy]
 
     if (
         not isinstance(policy, (bool, np.bool_))
         and isinstance(policy, (int, np.integer))
-        and policy in _ENERGY_REPRESENTATIONS.values()
+        and policy in _NEUTRON_MULTIGROUP_ENERGY_REPRESENTATIONS.values()
     ):
         return int(policy)
 
-    print_error(f"Unknown MGXS energy representation {policy!r}.")
+    print_error(f"Unknown NeutronMultigroup energy representation {policy!r}.")
 
 
 def _normalize_rows(array, required, name) -> None:
@@ -406,6 +449,8 @@ def _normalize_rows(array, required, name) -> None:
     for index in range(len(array)):
         norm = np.sum(array[index])
         if required[index] and norm <= 0.0:
-            print_error(f"MGXS {name} spectrum {index} must have positive mass.")
+            print_error(
+                f"NeutronMultigroup {name} spectrum {index} must have positive mass."
+            )
         if norm > 0.0:
             array[index] /= norm
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index 0252af10c..6f71589a7 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -43,7 +43,9 @@ class Universe(MCDCObject):
     >>> left = mcdc.Surface.PlaneX(x=-1.0)
     >>> middle = mcdc.Surface.PlaneX(x=0.0)
     >>> right = mcdc.Surface.PlaneX(x=1.0)
-    >>> material = mcdc.MaterialMG(capture=np.array([1.0]))
+    >>> material = mcdc.Material(
+    ...     neutron_multigroup=mcdc.NeutronMultigroup(capture=np.array([1.0]))
+    ... )
     >>> cells = [
     ...     mcdc.Cell(region=+left & -middle, fill=material),
     ...     mcdc.Cell(region=+middle & -right, fill=material),
@@ -53,8 +55,14 @@ class Universe(MCDCObject):
     Create a universe for a spherical inclusion and its surrounding material:
 
     >>> sphere = mcdc.Surface.Sphere(radius=0.5)
-    >>> fuel = mcdc.MaterialMG(fission=np.array([0.2]), nu_p=np.array([2.5]))
-    >>> water = mcdc.MaterialMG(capture=np.array([0.01]))
+    >>> fuel = mcdc.Material(
+    ...     neutron_multigroup=mcdc.NeutronMultigroup(
+    ...         fission=np.array([0.2]), nu_p=np.array([2.5])
+    ...     )
+    ... )
+    >>> water = mcdc.Material(
+    ...     neutron_multigroup=mcdc.NeutronMultigroup(capture=np.array([0.01]))
+    ... )
     >>> pin = mcdc.Universe(
     ...     name="Pin",
     ...     cells=[

From 99d934eb492af171e40b6b1636188207fc35cb13 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 15:07:38 +0700
Subject: [PATCH 112/202] add material multigroup creation helper

---
 mcdc/object_/cell.py     |  4 +---
 mcdc/object_/material.py | 49 ++++++++++++++++++++++++++++++++++++----
 mcdc/object_/tally.py    |  4 +---
 mcdc/object_/universe.py | 14 ++++--------
 4 files changed, 51 insertions(+), 20 deletions(-)

diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index e0942f79d..8a598d88e 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -125,9 +125,7 @@ class Cell(MCDCObject):
 
     >>> import numpy as np
     >>> import mcdc
-    >>> material = mcdc.Material(
-    ...     neutron_multigroup=mcdc.NeutronMultigroup(capture=np.array([1.0]))
-    ... )
+    >>> material = mcdc.Material.multigroup(capture=np.array([1.0]))
     >>> lower = mcdc.Surface.PlaneZ(z=0.0)
     >>> upper = mcdc.Surface.PlaneZ(z=2.0)
     >>> cell = mcdc.Cell(region=+lower & -upper, fill=material)
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index b2116ec3b..8cf70f5cf 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -1,8 +1,9 @@
 from types import NoneType
+from typing import Self
 
 import numpy as np
 from numpy import float64
-from numpy.typing import NDArray
+from numpy.typing import ArrayLike, NDArray
 
 from mcdc.object_.base import MCDCObject
 from mcdc.object_.element import Element
@@ -63,9 +64,8 @@ class Material(MCDCObject):
     Define a one-group multigroup material:
 
     >>> import numpy as np
-    >>> absorber = mcdc.Material(
-    ...     name="Absorber",
-    ...     neutron_multigroup=mcdc.NeutronMultigroup(capture=np.array([1.0])),
+    >>> absorber = mcdc.Material.multigroup(
+    ...     name="Absorber", capture=np.array([1.0])
     ... )
 
     Attach native and multigroup neutron data to the same material:
@@ -178,6 +178,47 @@ def __init__(
             list(self.element_composition.values()), dtype=float64
         )
 
+    @classmethod
+    def multigroup(
+        cls,
+        *,
+        name: str = "",
+        capture: ArrayLike | NoneType = None,
+        scatter: ArrayLike | NoneType = None,
+        fission: ArrayLike | NoneType = None,
+        nu_s: ArrayLike | NoneType = None,
+        nu_p: ArrayLike | NoneType = None,
+        nu_d: ArrayLike | NoneType = None,
+        chi_p: ArrayLike | NoneType = None,
+        chi_d: ArrayLike | NoneType = None,
+        speed: ArrayLike | NoneType = None,
+        decay_rate: ArrayLike | NoneType = None,
+        energy_grid: ArrayLike | NoneType = None,
+        energy_representation: str | int = "log_midpoint",
+    ) -> Self:
+        """Construct a material containing only multigroup neutron data.
+
+        The transport arguments are forwarded to :class:`NeutronMultigroup`.
+        Use the regular constructor when combining multigroup data with a
+        native nuclide or element composition.
+        """
+        # Build the transport model while preserving Material as the sole type
+        neutron_multigroup = NeutronMultigroup(
+            capture=capture,
+            scatter=scatter,
+            fission=fission,
+            nu_s=nu_s,
+            nu_p=nu_p,
+            nu_d=nu_d,
+            chi_p=chi_p,
+            chi_d=chi_d,
+            speed=speed,
+            decay_rate=decay_rate,
+            energy_grid=energy_grid,
+            energy_representation=energy_representation,
+        )
+        return cls(name=name, neutron_multigroup=neutron_multigroup)
+
     def _compile_into_simulation(self, simulation) -> bool:
         """Canonicalize owned data and register the unified material."""
         # Skip canonicalization when this material is already compiled
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 1f1adafe9..4697ff3dd 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -102,9 +102,7 @@ class Tally(MCDCPolymorphic):
 
     Filter a track-length tally by cell, angle, and time:
 
-    >>> material = mcdc.Material(
-    ...     neutron_multigroup=mcdc.NeutronMultigroup(capture=np.array([1.0]))
-    ... )
+    >>> material = mcdc.Material.multigroup(capture=np.array([1.0]))
     >>> lower = mcdc.Surface.PlaneZ(z=0.0)
     >>> upper = mcdc.Surface.PlaneZ(z=10.0)
     >>> cell = mcdc.Cell(region=+lower & -upper, fill=material)
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index 6f71589a7..c838fa8c1 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -43,9 +43,7 @@ class Universe(MCDCObject):
     >>> left = mcdc.Surface.PlaneX(x=-1.0)
     >>> middle = mcdc.Surface.PlaneX(x=0.0)
     >>> right = mcdc.Surface.PlaneX(x=1.0)
-    >>> material = mcdc.Material(
-    ...     neutron_multigroup=mcdc.NeutronMultigroup(capture=np.array([1.0]))
-    ... )
+    >>> material = mcdc.Material.multigroup(capture=np.array([1.0]))
     >>> cells = [
     ...     mcdc.Cell(region=+left & -middle, fill=material),
     ...     mcdc.Cell(region=+middle & -right, fill=material),
@@ -55,14 +53,10 @@ class Universe(MCDCObject):
     Create a universe for a spherical inclusion and its surrounding material:
 
     >>> sphere = mcdc.Surface.Sphere(radius=0.5)
-    >>> fuel = mcdc.Material(
-    ...     neutron_multigroup=mcdc.NeutronMultigroup(
-    ...         fission=np.array([0.2]), nu_p=np.array([2.5])
-    ...     )
-    ... )
-    >>> water = mcdc.Material(
-    ...     neutron_multigroup=mcdc.NeutronMultigroup(capture=np.array([0.01]))
+    >>> fuel = mcdc.Material.multigroup(
+    ...     fission=np.array([0.2]), nu_p=np.array([2.5])
     ... )
+    >>> water = mcdc.Material.multigroup(capture=np.array([0.01]))
     >>> pin = mcdc.Universe(
     ...     name="Pin",
     ...     cells=[

From 6c209a6112fa25383937b1f363aeec70d10efe34 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 15:08:26 +0700
Subject: [PATCH 113/202] update examples

---
 examples/c5g7/k-eigenvalue/input.py            | 2 +-
 examples/c5g7/transient/input.py               | 2 +-
 examples/fuel_array_packaged/input.py          | 6 +++---
 examples/iterative_source_reweighting/input.py | 2 +-
 examples/kobayashi-TD/input.py                 | 4 ++--
 examples/kobayashi/input.py                    | 4 ++--
 examples/moving_pellet/input.py                | 4 ++--
 examples/moving_source/input.py                | 2 +-
 examples/slab_shielding/input.py               | 4 ++--
 examples/sphere_in_cube/input.py               | 4 ++--
 10 files changed, 17 insertions(+), 17 deletions(-)

diff --git a/examples/c5g7/k-eigenvalue/input.py b/examples/c5g7/k-eigenvalue/input.py
index 9d69f9e11..393a70161 100644
--- a/examples/c5g7/k-eigenvalue/input.py
+++ b/examples/c5g7/k-eigenvalue/input.py
@@ -15,7 +15,7 @@
 
 # Setter
 def set_mat(mat):
-    return mcdc.MaterialMG(
+    return mcdc.Material.multigroup(
         capture=mat["capture"][:],
         scatter=mat["scatter"][:],
         fission=mat["fission"][:],
diff --git a/examples/c5g7/transient/input.py b/examples/c5g7/transient/input.py
index 06e398c2d..55462d474 100644
--- a/examples/c5g7/transient/input.py
+++ b/examples/c5g7/transient/input.py
@@ -15,7 +15,7 @@
 
 # Setter
 def set_mat(mat):
-    return mcdc.MaterialMG(
+    return mcdc.Material.multigroup(
         capture=mat["capture"][:],
         scatter=mat["scatter"][:],
         fission=mat["fission"][:],
diff --git a/examples/fuel_array_packaged/input.py b/examples/fuel_array_packaged/input.py
index b8c7f9dfe..3a1039189 100644
--- a/examples/fuel_array_packaged/input.py
+++ b/examples/fuel_array_packaged/input.py
@@ -7,18 +7,18 @@
 # Materials
 # ======================================================================================
 
-fuel = mcdc.MaterialMG(
+fuel = mcdc.Material.multigroup(
     capture=np.array([0.45]),
     fission=np.array([0.55]),
     nu_p=np.array([2.5]),
 )
 
-cover = mcdc.MaterialMG(
+cover = mcdc.Material.multigroup(
     capture=np.array([0.05]),
     scatter=np.array([[0.95]]),
 )
 
-water = mcdc.MaterialMG(
+water = mcdc.Material.multigroup(
     capture=np.array([0.02]),
     scatter=np.array([[0.08]]),
 )
diff --git a/examples/iterative_source_reweighting/input.py b/examples/iterative_source_reweighting/input.py
index d9ff586f0..a0ac53d0f 100644
--- a/examples/iterative_source_reweighting/input.py
+++ b/examples/iterative_source_reweighting/input.py
@@ -5,7 +5,7 @@
 simulation = mcdc.Simulation("Iterative source reweighting")
 
 # Homogeneous one-group slab
-material = mcdc.MaterialMG(
+material = mcdc.Material.multigroup(
     capture=np.array([0.2]),
     scatter=np.array([[0.8]]),
 )
diff --git a/examples/kobayashi-TD/input.py b/examples/kobayashi-TD/input.py
index dc939d8d6..61fb41ce7 100644
--- a/examples/kobayashi-TD/input.py
+++ b/examples/kobayashi-TD/input.py
@@ -10,8 +10,8 @@
 # (PNE 2001, https://doi.org/10.1016/S0149-1970(01)00007-5)
 
 # Set materials
-m = mcdc.MaterialMG(capture=np.array([0.05]), scatter=np.array([[0.05]]))
-m_void = mcdc.MaterialMG(capture=np.array([5e-5]), scatter=np.array([[5e-5]]))
+m = mcdc.Material.multigroup(capture=np.array([0.05]), scatter=np.array([[0.05]]))
+m_void = mcdc.Material.multigroup(capture=np.array([5e-5]), scatter=np.array([[5e-5]]))
 
 # Set surfaces
 sx1 = mcdc.Surface.PlaneX(x=0.0, boundary_condition="reflective")
diff --git a/examples/kobayashi/input.py b/examples/kobayashi/input.py
index b34d40b9d..9b5762927 100644
--- a/examples/kobayashi/input.py
+++ b/examples/kobayashi/input.py
@@ -10,8 +10,8 @@
 # (PNE 2001, https://doi.org/10.1016/S0149-1970(01)00007-5)
 
 # Set materials
-m = mcdc.MaterialMG(capture=np.array([0.05]), scatter=np.array([[0.05]]))
-m_void = mcdc.MaterialMG(capture=np.array([5e-5]), scatter=np.array([[5e-5]]))
+m = mcdc.Material.multigroup(capture=np.array([0.05]), scatter=np.array([[0.05]]))
+m_void = mcdc.Material.multigroup(capture=np.array([5e-5]), scatter=np.array([[5e-5]]))
 
 # Set surfaces
 sx1 = mcdc.Surface.PlaneX(x=0.0, boundary_condition="reflective")
diff --git a/examples/moving_pellet/input.py b/examples/moving_pellet/input.py
index e1c5c6e33..677d89973 100644
--- a/examples/moving_pellet/input.py
+++ b/examples/moving_pellet/input.py
@@ -9,13 +9,13 @@
 # ======================================================================================
 
 # Set materials
-fuel = mcdc.MaterialMG(
+fuel = mcdc.Material.multigroup(
     capture=np.array([0.5]),
     fission=np.array([0.25]),
     nu_p=np.array([1.5]),
     speed=np.array([200000.0]),
 )
-air = mcdc.MaterialMG(
+air = mcdc.Material.multigroup(
     capture=np.array([0.002]),
     scatter=np.array([[0.008]]),
     speed=np.array([200000.0]),
diff --git a/examples/moving_source/input.py b/examples/moving_source/input.py
index a739c542d..a013a036f 100644
--- a/examples/moving_source/input.py
+++ b/examples/moving_source/input.py
@@ -9,7 +9,7 @@
 # ======================================================================================
 
 # Set materials
-air = mcdc.MaterialMG(
+air = mcdc.Material.multigroup(
     capture=np.array([0.002]),
     scatter=np.array([[0.008]]),
     speed=np.array([200000.0]),
diff --git a/examples/slab_shielding/input.py b/examples/slab_shielding/input.py
index 3d5fec72c..43a25beb2 100644
--- a/examples/slab_shielding/input.py
+++ b/examples/slab_shielding/input.py
@@ -5,11 +5,11 @@
 simulation = mcdc.Simulation("One-group slab shielding")
 
 # Materials
-source_region_material = mcdc.MaterialMG(
+source_region_material = mcdc.Material.multigroup(
     capture=np.array([0.1]),
     scatter=np.array([[0.9]]),
 )
-shield_material = mcdc.MaterialMG(
+shield_material = mcdc.Material.multigroup(
     capture=np.array([0.7]),
     scatter=np.array([[0.3]]),
 )
diff --git a/examples/sphere_in_cube/input.py b/examples/sphere_in_cube/input.py
index d047062b4..55aee8c28 100644
--- a/examples/sphere_in_cube/input.py
+++ b/examples/sphere_in_cube/input.py
@@ -9,8 +9,8 @@
 # Homogeneous pure-fission sphere inside a pure-scattering cube
 
 # Set materials
-pure_f = mcdc.MaterialMG(fission=np.array([1.0]), nu_p=np.array([1.2]))
-pure_s = mcdc.MaterialMG(scatter=np.array([[1.0]]))
+pure_f = mcdc.Material.multigroup(fission=np.array([1.0]), nu_p=np.array([1.2]))
+pure_s = mcdc.Material.multigroup(scatter=np.array([[1.0]]))
 
 # Set surfaces
 sx1 = mcdc.Surface.PlaneX(x=0.0, boundary_condition="vacuum")

From a6c477cf82d1875080e9c6fa0345b74dffbfb725 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 15:09:28 +0700
Subject: [PATCH 114/202] update regresstion tests

---
 test/regression/azurv1/input.py                   | 2 +-
 test/regression/azurv1_census/input.py            | 2 +-
 test/regression/azurv1_census_tally/input.py      | 2 +-
 test/regression/c5g7_2d_k_eigenvalue/input.py     | 2 +-
 test/regression/cooper2/input.py                  | 6 ++++--
 test/regression/fuel_array_packaged/input.py      | 6 +++---
 test/regression/inf_shem361/input.py              | 2 +-
 test/regression/inf_shem361_k_eigenvalue/input.py | 2 +-
 test/regression/inf_shem361_td/input.py           | 2 +-
 test/regression/inf_shem361_td_census/input.py    | 2 +-
 test/regression/kobayashi3-TD/input.py            | 4 ++--
 test/regression/kornreich/input.py                | 4 ++--
 test/regression/moving_pellet/input.py            | 4 ++--
 test/regression/moving_source/input.py            | 2 +-
 test/regression/slab_absorbium/input.py           | 6 +++---
 test/regression/slab_isobeam_td/input.py          | 2 +-
 test/regression/slab_isobeam_td_census/input.py   | 2 +-
 test/regression/slab_reed/input.py                | 8 ++++----
 test/regression/sphere_in_cube/input.py           | 4 ++--
 19 files changed, 33 insertions(+), 31 deletions(-)

diff --git a/test/regression/azurv1/input.py b/test/regression/azurv1/input.py
index e3a229449..dd9f21ac8 100644
--- a/test/regression/azurv1/input.py
+++ b/test/regression/azurv1/input.py
@@ -12,7 +12,7 @@
 # Effective scattering ratio c = 1.1
 
 # Materials
-m = mcdc.MaterialMG(
+m = mcdc.Material.multigroup(
     capture=np.array([1.0 / 3.0]),
     scatter=np.array([[1.0 / 3.0]]),
     fission=np.array([1.0 / 3.0]),
diff --git a/test/regression/azurv1_census/input.py b/test/regression/azurv1_census/input.py
index c7d2e7122..a0d0ddab7 100644
--- a/test/regression/azurv1_census/input.py
+++ b/test/regression/azurv1_census/input.py
@@ -12,7 +12,7 @@
 # Effective scattering ratio c = 1.1
 
 # Set materials
-m = mcdc.MaterialMG(
+m = mcdc.Material.multigroup(
     capture=np.array([1.0 / 3.0]),
     scatter=np.array([[1.0 / 3.0]]),
     fission=np.array([1.0 / 3.0]),
diff --git a/test/regression/azurv1_census_tally/input.py b/test/regression/azurv1_census_tally/input.py
index 358cf705d..a739a93e6 100644
--- a/test/regression/azurv1_census_tally/input.py
+++ b/test/regression/azurv1_census_tally/input.py
@@ -12,7 +12,7 @@
 # Effective scattering ratio c = 1.1
 
 # Set materials
-m = mcdc.MaterialMG(
+m = mcdc.Material.multigroup(
     capture=np.array([1.0 / 3.0]),
     scatter=np.array([[1.0 / 3.0]]),
     fission=np.array([1.0 / 3.0]),
diff --git a/test/regression/c5g7_2d_k_eigenvalue/input.py b/test/regression/c5g7_2d_k_eigenvalue/input.py
index 11cb111e9..dea106e72 100644
--- a/test/regression/c5g7_2d_k_eigenvalue/input.py
+++ b/test/regression/c5g7_2d_k_eigenvalue/input.py
@@ -16,7 +16,7 @@
 
 # Materials
 def set_mat(mat):
-    return mcdc.MaterialMG(
+    return mcdc.Material.multigroup(
         capture=mat["capture"][:],
         scatter=mat["scatter"][:],
         fission=mat["fission"][:],
diff --git a/test/regression/cooper2/input.py b/test/regression/cooper2/input.py
index b2b5b0809..6da73d24b 100644
--- a/test/regression/cooper2/input.py
+++ b/test/regression/cooper2/input.py
@@ -13,11 +13,13 @@
 # Set materials
 SigmaT = 5.0
 c = 0.8
-m_barrier = mcdc.MaterialMG(
+m_barrier = mcdc.Material.multigroup(
     capture=np.array([SigmaT]), scatter=np.array([[SigmaT * c]])
 )
 SigmaT = 1.0
-m_room = mcdc.MaterialMG(capture=np.array([SigmaT]), scatter=np.array([[SigmaT * c]]))
+m_room = mcdc.Material.multigroup(
+    capture=np.array([SigmaT]), scatter=np.array([[SigmaT * c]])
+)
 
 # Set surfaces
 sx1 = mcdc.Surface.PlaneX(x=0.0, boundary_condition="reflective")
diff --git a/test/regression/fuel_array_packaged/input.py b/test/regression/fuel_array_packaged/input.py
index 8bf04d9a0..54618e733 100644
--- a/test/regression/fuel_array_packaged/input.py
+++ b/test/regression/fuel_array_packaged/input.py
@@ -8,18 +8,18 @@
 # Materials
 # ======================================================================================
 
-fuel = mcdc.MaterialMG(
+fuel = mcdc.Material.multigroup(
     capture=np.array([0.45]),
     fission=np.array([0.55]),
     nu_p=np.array([2.5]),
 )
 
-cover = mcdc.MaterialMG(
+cover = mcdc.Material.multigroup(
     capture=np.array([0.05]),
     scatter=np.array([[0.95]]),
 )
 
-water = mcdc.MaterialMG(
+water = mcdc.Material.multigroup(
     capture=np.array([0.02]),
     scatter=np.array([[0.08]]),
 )
diff --git a/test/regression/inf_shem361/input.py b/test/regression/inf_shem361/input.py
index 4d7b45c71..93643a317 100644
--- a/test/regression/inf_shem361/input.py
+++ b/test/regression/inf_shem361/input.py
@@ -23,7 +23,7 @@
     lamd = data["lamd"]
 
 # Set material
-m = mcdc.MaterialMG(
+m = mcdc.Material.multigroup(
     capture=SigmaC,
     scatter=SigmaS,
     fission=SigmaF,
diff --git a/test/regression/inf_shem361_k_eigenvalue/input.py b/test/regression/inf_shem361_k_eigenvalue/input.py
index cf7df499a..7cb168d81 100644
--- a/test/regression/inf_shem361_k_eigenvalue/input.py
+++ b/test/regression/inf_shem361_k_eigenvalue/input.py
@@ -22,7 +22,7 @@
     G = data["G"]
 
 # Set material
-m = mcdc.MaterialMG(
+m = mcdc.Material.multigroup(
     capture=SigmaC,
     scatter=SigmaS,
     fission=SigmaF,
diff --git a/test/regression/inf_shem361_td/input.py b/test/regression/inf_shem361_td/input.py
index bb7bf1090..8cb10c049 100644
--- a/test/regression/inf_shem361_td/input.py
+++ b/test/regression/inf_shem361_td/input.py
@@ -23,7 +23,7 @@
     lamd = data["lamd"]
 
 # Set material
-m = mcdc.MaterialMG(
+m = mcdc.Material.multigroup(
     capture=SigmaC,
     scatter=SigmaS,
     fission=SigmaF,
diff --git a/test/regression/inf_shem361_td_census/input.py b/test/regression/inf_shem361_td_census/input.py
index 06f685419..11e9d487b 100644
--- a/test/regression/inf_shem361_td_census/input.py
+++ b/test/regression/inf_shem361_td_census/input.py
@@ -23,7 +23,7 @@
     lamd = data["lamd"]
 
 # Set material
-m = mcdc.MaterialMG(
+m = mcdc.Material.multigroup(
     capture=SigmaC,
     scatter=SigmaS,
     fission=SigmaF,
diff --git a/test/regression/kobayashi3-TD/input.py b/test/regression/kobayashi3-TD/input.py
index 418c6f819..3a92fa9ce 100644
--- a/test/regression/kobayashi3-TD/input.py
+++ b/test/regression/kobayashi3-TD/input.py
@@ -11,8 +11,8 @@
 # (PNE 2001, https://doi.org/10.1016/S0149-1970(01)00007-5)
 
 # Set materials
-m = mcdc.MaterialMG(capture=np.array([0.05]), scatter=np.array([[0.05]]))
-m_void = mcdc.MaterialMG(capture=np.array([5e-5]), scatter=np.array([[5e-5]]))
+m = mcdc.Material.multigroup(capture=np.array([0.05]), scatter=np.array([[0.05]]))
+m_void = mcdc.Material.multigroup(capture=np.array([5e-5]), scatter=np.array([[5e-5]]))
 
 # Set surfaces
 sx1 = mcdc.Surface.PlaneX(x=0.0, boundary_condition="reflective")
diff --git a/test/regression/kornreich/input.py b/test/regression/kornreich/input.py
index 248ecb548..2a9962a2f 100644
--- a/test/regression/kornreich/input.py
+++ b/test/regression/kornreich/input.py
@@ -11,13 +11,13 @@
 # DOI: 10.1016/j.anucene.2004.03.012
 
 # Set materials
-m1 = mcdc.MaterialMG(
+m1 = mcdc.Material.multigroup(
     capture=np.array([0.0]),
     scatter=np.array([[0.9]]),
     fission=np.array([0.1]),
     nu_p=np.array([6.0]),
 )
-m2 = mcdc.MaterialMG(
+m2 = mcdc.Material.multigroup(
     capture=np.array([0.68]),
     scatter=np.array([[0.2]]),
     fission=np.array([0.12]),
diff --git a/test/regression/moving_pellet/input.py b/test/regression/moving_pellet/input.py
index ae97167a2..ab45b832d 100644
--- a/test/regression/moving_pellet/input.py
+++ b/test/regression/moving_pellet/input.py
@@ -10,13 +10,13 @@
 # ======================================================================================
 
 # Set materials
-fuel = mcdc.MaterialMG(
+fuel = mcdc.Material.multigroup(
     capture=np.array([0.5]),
     fission=np.array([0.25]),
     nu_p=np.array([1.5]),
     speed=np.array([200000.0]),
 )
-air = mcdc.MaterialMG(
+air = mcdc.Material.multigroup(
     capture=np.array([0.002]),
     scatter=np.array([[0.008]]),
     speed=np.array([200000.0]),
diff --git a/test/regression/moving_source/input.py b/test/regression/moving_source/input.py
index 219f41a60..8de23c47b 100644
--- a/test/regression/moving_source/input.py
+++ b/test/regression/moving_source/input.py
@@ -10,7 +10,7 @@
 # ======================================================================================
 
 # Set materials
-air = mcdc.MaterialMG(
+air = mcdc.Material.multigroup(
     capture=np.array([0.002]),
     scatter=np.array([[0.008]]),
     speed=np.array([200000.0]),
diff --git a/test/regression/slab_absorbium/input.py b/test/regression/slab_absorbium/input.py
index 2046ecfbd..fb94599e8 100644
--- a/test/regression/slab_absorbium/input.py
+++ b/test/regression/slab_absorbium/input.py
@@ -10,9 +10,9 @@
 # Three slab layers with different purely-absorbing materials
 
 # Set materials
-m1 = mcdc.MaterialMG(capture=np.array([1.0]))
-m2 = mcdc.MaterialMG(capture=np.array([1.5]))
-m3 = mcdc.MaterialMG(capture=np.array([2.0]))
+m1 = mcdc.Material.multigroup(capture=np.array([1.0]))
+m2 = mcdc.Material.multigroup(capture=np.array([1.5]))
+m3 = mcdc.Material.multigroup(capture=np.array([2.0]))
 
 # Set surfaces
 s1 = mcdc.Surface.PlaneZ(z=0.0, boundary_condition="vacuum")
diff --git a/test/regression/slab_isobeam_td/input.py b/test/regression/slab_isobeam_td/input.py
index 15c1e91a1..0ae8c2091 100644
--- a/test/regression/slab_isobeam_td/input.py
+++ b/test/regression/slab_isobeam_td/input.py
@@ -11,7 +11,7 @@
 # Finite homogeneous pure-absorbing slab
 
 # Set materials
-m = mcdc.MaterialMG(capture=np.array([1.0]))
+m = mcdc.Material.multigroup(capture=np.array([1.0]))
 
 # Set surfaces
 s1 = mcdc.Surface.PlaneX(x=0.0, boundary_condition="vacuum")
diff --git a/test/regression/slab_isobeam_td_census/input.py b/test/regression/slab_isobeam_td_census/input.py
index d2b567e9c..504e0dff6 100644
--- a/test/regression/slab_isobeam_td_census/input.py
+++ b/test/regression/slab_isobeam_td_census/input.py
@@ -11,7 +11,7 @@
 # Finite homogeneous pure-absorbing slab
 
 # Set materials
-m = mcdc.MaterialMG(capture=np.array([1.0]))
+m = mcdc.Material.multigroup(capture=np.array([1.0]))
 
 # Set surfaces
 s1 = mcdc.Surface.PlaneX(x=0.0, boundary_condition="vacuum")
diff --git a/test/regression/slab_reed/input.py b/test/regression/slab_reed/input.py
index 7d5bc908e..8b1c19711 100644
--- a/test/regression/slab_reed/input.py
+++ b/test/regression/slab_reed/input.py
@@ -11,10 +11,10 @@
 # Based on William H. Reed, NSE (1971), 46:2, 309-314, DOI: 10.13182/NSE46-309
 
 # Set materials
-m1 = mcdc.MaterialMG(capture=np.array([50.0]))
-m2 = mcdc.MaterialMG(capture=np.array([5.0]))
-m3 = mcdc.MaterialMG(capture=np.array([0.0]))  # Vacuum
-m4 = mcdc.MaterialMG(capture=np.array([0.1]), scatter=np.array([[0.9]]))
+m1 = mcdc.Material.multigroup(capture=np.array([50.0]))
+m2 = mcdc.Material.multigroup(capture=np.array([5.0]))
+m3 = mcdc.Material.multigroup(capture=np.array([0.0]))  # Vacuum
+m4 = mcdc.Material.multigroup(capture=np.array([0.1]), scatter=np.array([[0.9]]))
 
 # Set surfaces
 s1 = mcdc.Surface.PlaneZ(z=0.0, boundary_condition="reflective")
diff --git a/test/regression/sphere_in_cube/input.py b/test/regression/sphere_in_cube/input.py
index 9a5766d2a..1c30814cc 100644
--- a/test/regression/sphere_in_cube/input.py
+++ b/test/regression/sphere_in_cube/input.py
@@ -10,8 +10,8 @@
 # Homogeneous pure-fission sphere inside a pure-scattering cube
 
 # Set materials
-pure_f = mcdc.MaterialMG(fission=np.array([1.0]), nu_p=np.array([1.2]))
-pure_s = mcdc.MaterialMG(scatter=np.array([[1.0]]))
+pure_f = mcdc.Material.multigroup(fission=np.array([1.0]), nu_p=np.array([1.2]))
+pure_s = mcdc.Material.multigroup(scatter=np.array([[1.0]]))
 
 # Set surfaces
 sx1 = mcdc.Surface.PlaneX(x=0.0, boundary_condition="vacuum")

From 069f13d305f6a7b15034ef963e194c0a677ed9ca Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 18:24:26 +0700
Subject: [PATCH 115/202] dinalize unified python material

---
 mcdc/__init__.py                              |   2 +-
 mcdc/code_factory/numba_layers_generator.py   | 120 ++++-
 mcdc/code_factory/python_objects_compiler.py  |   8 +-
 mcdc/constant.py                              |   4 -
 mcdc/main.py                                  |  15 -
 mcdc/mcdc_get/__init__.py                     |  22 +-
 mcdc/mcdc_get/neutron_multigroup.py           | 411 -----------------
 mcdc/mcdc_get/neutron_multigroup_data.py      | 414 ++++++++++++++++++
 mcdc/mcdc_get/technique.py                    |   3 +
 mcdc/mcdc_set/__init__.py                     |  22 +-
 mcdc/mcdc_set/neutron_multigroup.py           | 411 -----------------
 mcdc/mcdc_set/neutron_multigroup_data.py      | 414 ++++++++++++++++++
 mcdc/mcdc_set/technique.py                    |   3 +
 mcdc/numba_types.py                           |  41 +-
 mcdc/object_/material.py                      |  47 +-
 mcdc/object_/settings.py                      |   1 -
 mcdc/object_/simulation.py                    |  60 +--
 mcdc/object_/technique.py                     |  93 +++-
 ...sport_model.py => transport_model_data.py} |  86 ++--
 19 files changed, 1176 insertions(+), 1001 deletions(-)
 create mode 100644 mcdc/mcdc_get/neutron_multigroup_data.py
 create mode 100644 mcdc/mcdc_get/technique.py
 create mode 100644 mcdc/mcdc_set/neutron_multigroup_data.py
 create mode 100644 mcdc/mcdc_set/technique.py
 rename mcdc/object_/{transport_model.py => transport_model_data.py} (84%)

diff --git a/mcdc/__init__.py b/mcdc/__init__.py
index 4db32c8b2..d18a80402 100644
--- a/mcdc/__init__.py
+++ b/mcdc/__init__.py
@@ -11,7 +11,7 @@
 
 from mcdc.object_.cell import Cell, Universe, Lattice
 from mcdc.object_.material import Material
-from mcdc.object_.transport_model import NeutronMultigroup
+from mcdc.object_.transport_model_data import NeutronMultigroupData
 from mcdc.object_.mesh import MeshUniform, MeshStructured
 from mcdc.object_.simulation import Simulation
 from mcdc.object_.source import Source
diff --git a/mcdc/code_factory/numba_layers_generator.py b/mcdc/code_factory/numba_layers_generator.py
index a87a7449b..225ea5e97 100644
--- a/mcdc/code_factory/numba_layers_generator.py
+++ b/mcdc/code_factory/numba_layers_generator.py
@@ -45,6 +45,20 @@
 
 bank_names = ["bank_active", "bank_census", "bank_source", "bank_future"]
 
+
+def validate_unique_class_labels(classes):
+    """Reject distinct runtime classes that use the same structure label."""
+    classes_by_label = {}
+    for class_ in classes:
+        existing = classes_by_label.get(class_.label)
+        if existing is not None and existing is not class_:
+            print_error(
+                f"Duplicate MC/DC class label '{class_.label}' used by "
+                f"{existing.__name__} and {class_.__name__}."
+            )
+        classes_by_label[class_.label] = class_
+
+
 # ======================================================================================
 # Gather and group the classes
 # ======================================================================================
@@ -79,6 +93,8 @@
             ):
                 mcdc_classes.append(item)
 
+validate_unique_class_labels(mcdc_classes)
+
 polymorphic_bases = [
     x for x in mcdc_classes if issubclass(x, MCDCPolymorphic) and x.sub_type == -1
 ]
@@ -197,9 +213,20 @@ def generate_numba_layers(simulation):
             included_classes.append(hint_args[0])
             continue
 
-    # Set the structures and accessor targets
+    # Build child structures before structures that embed them
+    completed_structures = set()
+    active_structures = set()
+    structure_order = []
     for label in annotations.keys():
-        set_structure(label, structures, accessor_targets, annotations)
+        set_structure(
+            label,
+            structures,
+            accessor_targets,
+            annotations,
+            completed_structures,
+            active_structures,
+            structure_order,
+        )
 
     # Generate the accessor helper
     if MPI.COMM_WORLD.Get_rank() == 0:
@@ -327,14 +354,13 @@ def generate_numba_layers(simulation):
                 "from mcdc.code_factory.numba_layers_generator import into_dtype\n\n"
             )
 
-            for label in structures.keys():
+            for label in structure_order:
                 # Skip special types
                 if label in ["gpu_meta"] + bank_names + ["simulation"]:
                     continue
 
                 text += f"{label} = into_dtype([\n"
                 structure = structures[label]
-
                 for item in structure:
                     text += decode_structure_item(item)
                 text += "])\n\n"
@@ -474,7 +500,37 @@ def generate_numba_layers(simulation):
     return mcdc_simulation_container, data["array"]
 
 
-def set_structure(label, structures, accessor_targets, annotations):
+def is_embedded_mcdc_base(hint):
+    """Return whether a field is an inline, simulation-owned MC/DC object."""
+    return (
+        isinstance(hint, type)
+        and issubclass(hint, MCDCBase)
+        and not issubclass(hint, MCDCObject)
+    )
+
+
+def set_structure(
+    label,
+    structures,
+    accessor_targets,
+    annotations,
+    completed=None,
+    active=None,
+    order=None,
+):
+    # Track dependencies so embedded structures are complete before their owners
+    if completed is None:
+        completed = set()
+    if active is None:
+        active = set()
+    if order is None:
+        order = []
+    if label in completed:
+        return
+    if label in active:
+        print_error(f"Cyclic embedded MCDCBase structure involving '{label}'.")
+    active.add(label)
+
     structure = structures[label]
     annotation = annotations[label]
     accessor_target = accessor_targets[label]
@@ -483,10 +539,18 @@ def set_structure(label, structures, accessor_targets, annotations):
         hint = annotation[field]
         hint_origin = get_origin(hint)
         hint_args = get_args(hint)
+        embedded_mcdc_base = is_embedded_mcdc_base(hint)
         hint_origin_shape = None
         hint_inner_dtype = None
         fixed_size_array = False
 
+        # Inline runtime fields use their class label as their field name
+        if embedded_mcdc_base and field != hint.label:
+            print_error(
+                f"Embedded MCDCBase field '{label}.{field}' must match the "
+                f"class label '{hint.label}'."
+            )
+
         # Process annotation
         if hint_origin is Annotated:
             hint_decoded = decode_annotated_ndarray(hint)
@@ -546,7 +610,24 @@ def polymorphic_base(x):
         # ==========================================================================
 
         # Basics
-        if fixed_size_array:
+        if embedded_mcdc_base:
+            child_label = hint.label
+            if child_label not in annotations:
+                print_error(
+                    f"Missing annotations for embedded MCDCBase {label}/{field}: "
+                    f"{child_label}"
+                )
+            set_structure(
+                child_label,
+                structures,
+                accessor_targets,
+                annotations,
+                completed,
+                active,
+                order,
+            )
+            structure.append((field, into_dtype(structures[child_label])))
+        elif fixed_size_array:
             structure.append((field, type_map[hint_inner_dtype], hint_origin_shape))
         elif simple_scalar:
             structure.append((field, type_map[hint]))
@@ -586,6 +667,11 @@ def polymorphic_base(x):
         else:
             print_error(f"Unknown type hint for {label}/{field}: {hint}")
 
+    # Record a dependency-safe declaration order for generated Numba types
+    active.remove(label)
+    completed.add(label)
+    order.append(label)
+
 
 def set_object(
     object_, annotations, structures, records, data, class_=None, set_data=False
@@ -614,6 +700,28 @@ def set_object(
     if class_.label == "simulation":
         record = records["simulation"]
 
+    # Recursively pack inline MCDCBase members before packing their owner
+    if class_.label != "simulation":
+        for field, child_class in annotation.items():
+            if not is_embedded_mcdc_base(child_class):
+                continue
+            child = getattr(object_, field)
+            set_object(
+                child,
+                annotations,
+                structures,
+                records,
+                data,
+                set_data=set_data,
+            )
+            child_structure = structures[child_class.label]
+            child_container = np.zeros(1, dtype=into_dtype(child_structure))
+            child_record = child_container[0]
+            for child_item in child_structure:
+                child_field = child_item[0]
+                child_record[child_field] = records[child_class.label][child_field]
+            record[field] = child_record
+
     # Straightforwardly set up attributes
     for key in [x[0] for x in structure]:
         if key in dir(object_):
diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index 82b53d789..c7272aa90 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -5,7 +5,7 @@
 from mcdc.object_.electron_reaction import ElectronReactionBase
 from mcdc.object_.element import Element
 from mcdc.object_.material import Material
-from mcdc.object_.transport_model import NeutronMultigroup
+from mcdc.object_.transport_model_data import NeutronMultigroupData
 from mcdc.object_.mesh import MeshBase
 from mcdc.object_.neutron_reaction import NeutronReactionBase
 from mcdc.object_.nuclide import Nuclide
@@ -40,7 +40,7 @@ def compile_simulation(simulation: Simulation):
     # Reserved objects
     none_data = DataNone()
     none_distribution = DistributionNone()
-    none_neutron_multigroup = NeutronMultigroup()
+    none_neutron_multigroup = NeutronMultigroupData()
 
     # Compile reserved objects
     none_data._compile_into_simulation(simulation)
@@ -83,8 +83,8 @@ def register_object(object_: MCDCObject, simulation: Simulation) -> bool:
         object_list = simulation.lattices
     elif isinstance(object_, Material):
         object_list = simulation.materials
-    elif isinstance(object_, NeutronMultigroup):
-        object_list = simulation.neutron_multigroup
+    elif isinstance(object_, NeutronMultigroupData):
+        object_list = simulation.neutron_multigroup_data
     elif isinstance(object_, MeshBase):
         object_list = simulation.meshes
     elif isinstance(object_, Element):
diff --git a/mcdc/constant.py b/mcdc/constant.py
index 0235724ef..10bf5033c 100644
--- a/mcdc/constant.py
+++ b/mcdc/constant.py
@@ -32,10 +32,6 @@
 PARTICLE_ELECTRON = 1
 PARTICLE_PROTON = 2
 
-# Neutron multigroup energy-grid organization
-NEUTRON_MULTIGROUP_GRID_SHARED = 0
-NEUTRON_MULTIGROUP_GRID_LOCAL = 1
-
 # Neutron multigroup energy representation
 NEUTRON_MULTIGROUP_ENERGY_MIDPOINT = 0
 NEUTRON_MULTIGROUP_ENERGY_MIDPOINT_LOG = 1
diff --git a/mcdc/main.py b/mcdc/main.py
index 5c4bbc8b7..7887bd37d 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -141,21 +141,6 @@ def prepare(simulationPy: Simulation):
     importlib.reload(mcdc_get)
     importlib.reload(mcdc_set)
 
-    # ==================================================================================
-    # Adapt functions as needed
-    # ==================================================================================
-
-    # Pick physics model
-    import mcdc.transport.physics as physics
-
-    if settings.neutron_multigroup_mode:
-        physics.neutron.particle_speed = physics.neutron.multigroup.particle_speed
-        physics.neutron.macro_xs = physics.neutron.multigroup.macro_xs
-        physics.neutron.neutron_production_xs = (
-            physics.neutron.multigroup.neutron_production_xs
-        )
-        physics.neutron.collision = physics.neutron.multigroup.collision
-
     # Pick Python-version RNG if needed
     import mcdc.config as config
     import mcdc.transport.rng as rng
diff --git a/mcdc/mcdc_get/__init__.py b/mcdc/mcdc_get/__init__.py
index af9a342e2..991c0c0b7 100644
--- a/mcdc/mcdc_get/__init__.py
+++ b/mcdc/mcdc_get/__init__.py
@@ -60,7 +60,7 @@
 
 import mcdc.mcdc_get.gpu_meta as gpu_meta
 
-import mcdc.mcdc_get.neutron_multigroup as neutron_multigroup
+import mcdc.mcdc_get.neutron_multigroup_data as neutron_multigroup_data
 
 import mcdc.mcdc_get.nuclide as nuclide
 
@@ -86,24 +86,28 @@
 
 import mcdc.mcdc_get.settings as settings
 
+import mcdc.mcdc_get.technique as technique
+
+import mcdc.mcdc_get.source as source
+
+import mcdc.mcdc_get.surface as surface
+
+import mcdc.mcdc_get.surface_crossing_tally as surface_crossing_tally
+
+import mcdc.mcdc_get.tally as tally
+
 import mcdc.mcdc_get.global_weight_roulette as global_weight_roulette
 
 import mcdc.mcdc_get.implicit_capture as implicit_capture
 
+import mcdc.mcdc_get.neutron_multigroup as neutron_multigroup
+
 import mcdc.mcdc_get.population_control as population_control
 
 import mcdc.mcdc_get.weight_windows as weight_windows
 
 import mcdc.mcdc_get.weighted_emission as weighted_emission
 
-import mcdc.mcdc_get.source as source
-
-import mcdc.mcdc_get.surface as surface
-
-import mcdc.mcdc_get.surface_crossing_tally as surface_crossing_tally
-
-import mcdc.mcdc_get.tally as tally
-
 import mcdc.mcdc_get.bank_active as bank_active
 
 import mcdc.mcdc_get.bank_census as bank_census
diff --git a/mcdc/mcdc_get/neutron_multigroup.py b/mcdc/mcdc_get/neutron_multigroup.py
index cd551ac8d..fdbf8e750 100644
--- a/mcdc/mcdc_get/neutron_multigroup.py
+++ b/mcdc/mcdc_get/neutron_multigroup.py
@@ -1,414 +1,3 @@
 # The following is automatically generated by code_factory.py
 
 from numba import njit
-
-
-@njit
-def energy_grid(index, neutron_multigroup, data):
-    offset = neutron_multigroup["energy_grid_offset"]
-    return data[offset + index]
-
-
-@njit
-def energy_grid_all(neutron_multigroup, data):
-    start = neutron_multigroup["energy_grid_offset"]
-    size = neutron_multigroup["G"] + 1
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def energy_grid_last(neutron_multigroup, data):
-    start = neutron_multigroup["energy_grid_offset"]
-    size = neutron_multigroup["G"] + 1
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def energy_grid_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["energy_grid_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def speed(index, neutron_multigroup, data):
-    offset = neutron_multigroup["speed_offset"]
-    return data[offset + index]
-
-
-@njit
-def speed_all(neutron_multigroup, data):
-    start = neutron_multigroup["speed_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def speed_last(neutron_multigroup, data):
-    start = neutron_multigroup["speed_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def speed_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["speed_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def decay_rate(index, neutron_multigroup, data):
-    offset = neutron_multigroup["decay_rate_offset"]
-    return data[offset + index]
-
-
-@njit
-def decay_rate_all(neutron_multigroup, data):
-    start = neutron_multigroup["decay_rate_offset"]
-    size = neutron_multigroup["J"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def decay_rate_last(neutron_multigroup, data):
-    start = neutron_multigroup["decay_rate_offset"]
-    size = neutron_multigroup["J"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def decay_rate_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["decay_rate_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def capture(index, neutron_multigroup, data):
-    offset = neutron_multigroup["capture_offset"]
-    return data[offset + index]
-
-
-@njit
-def capture_all(neutron_multigroup, data):
-    start = neutron_multigroup["capture_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def capture_last(neutron_multigroup, data):
-    start = neutron_multigroup["capture_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def capture_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["capture_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def scatter(index, neutron_multigroup, data):
-    offset = neutron_multigroup["scatter_offset"]
-    return data[offset + index]
-
-
-@njit
-def scatter_all(neutron_multigroup, data):
-    start = neutron_multigroup["scatter_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def scatter_last(neutron_multigroup, data):
-    start = neutron_multigroup["scatter_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def scatter_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["scatter_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def fission(index, neutron_multigroup, data):
-    offset = neutron_multigroup["fission_offset"]
-    return data[offset + index]
-
-
-@njit
-def fission_all(neutron_multigroup, data):
-    start = neutron_multigroup["fission_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def fission_last(neutron_multigroup, data):
-    start = neutron_multigroup["fission_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def fission_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["fission_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def total(index, neutron_multigroup, data):
-    offset = neutron_multigroup["total_offset"]
-    return data[offset + index]
-
-
-@njit
-def total_all(neutron_multigroup, data):
-    start = neutron_multigroup["total_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def total_last(neutron_multigroup, data):
-    start = neutron_multigroup["total_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def total_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["total_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nu_s(index, neutron_multigroup, data):
-    offset = neutron_multigroup["nu_s_offset"]
-    return data[offset + index]
-
-
-@njit
-def nu_s_all(neutron_multigroup, data):
-    start = neutron_multigroup["nu_s_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def nu_s_last(neutron_multigroup, data):
-    start = neutron_multigroup["nu_s_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def nu_s_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["nu_s_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nu_p(index, neutron_multigroup, data):
-    offset = neutron_multigroup["nu_p_offset"]
-    return data[offset + index]
-
-
-@njit
-def nu_p_all(neutron_multigroup, data):
-    start = neutron_multigroup["nu_p_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def nu_p_last(neutron_multigroup, data):
-    start = neutron_multigroup["nu_p_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def nu_p_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["nu_p_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nu_d_vector(index_1, neutron_multigroup, data):
-    offset = neutron_multigroup["nu_d_offset"]
-    stride = neutron_multigroup["J"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def nu_d(index_1, index_2, neutron_multigroup, data):
-    offset = neutron_multigroup["nu_d_offset"]
-    stride = neutron_multigroup["J"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def nu_d_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["nu_d_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nu_d_total(index, neutron_multigroup, data):
-    offset = neutron_multigroup["nu_d_total_offset"]
-    return data[offset + index]
-
-
-@njit
-def nu_d_total_all(neutron_multigroup, data):
-    start = neutron_multigroup["nu_d_total_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def nu_d_total_last(neutron_multigroup, data):
-    start = neutron_multigroup["nu_d_total_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def nu_d_total_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["nu_d_total_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def nu_f(index, neutron_multigroup, data):
-    offset = neutron_multigroup["nu_f_offset"]
-    return data[offset + index]
-
-
-@njit
-def nu_f_all(neutron_multigroup, data):
-    start = neutron_multigroup["nu_f_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def nu_f_last(neutron_multigroup, data):
-    start = neutron_multigroup["nu_f_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def nu_f_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["nu_f_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def chi_s_vector(index_1, neutron_multigroup, data):
-    offset = neutron_multigroup["chi_s_offset"]
-    stride = neutron_multigroup["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def chi_s(index_1, index_2, neutron_multigroup, data):
-    offset = neutron_multigroup["chi_s_offset"]
-    stride = neutron_multigroup["G"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def chi_s_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["chi_s_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def chi_p_vector(index_1, neutron_multigroup, data):
-    offset = neutron_multigroup["chi_p_offset"]
-    stride = neutron_multigroup["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def chi_p(index_1, index_2, neutron_multigroup, data):
-    offset = neutron_multigroup["chi_p_offset"]
-    stride = neutron_multigroup["G"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def chi_p_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["chi_p_offset"]
-    end = start + length
-    return data[start:end]
-
-
-@njit
-def chi_d_vector(index_1, neutron_multigroup, data):
-    offset = neutron_multigroup["chi_d_offset"]
-    stride = neutron_multigroup["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    return data[start:end]
-
-
-@njit
-def chi_d(index_1, index_2, neutron_multigroup, data):
-    offset = neutron_multigroup["chi_d_offset"]
-    stride = neutron_multigroup["G"]
-    return data[offset + index_1 * stride + index_2]
-
-
-@njit
-def chi_d_chunk(start, length, neutron_multigroup, data):
-    start += neutron_multigroup["chi_d_offset"]
-    end = start + length
-    return data[start:end]
diff --git a/mcdc/mcdc_get/neutron_multigroup_data.py b/mcdc/mcdc_get/neutron_multigroup_data.py
new file mode 100644
index 000000000..dd42f529f
--- /dev/null
+++ b/mcdc/mcdc_get/neutron_multigroup_data.py
@@ -0,0 +1,414 @@
+# The following is automatically generated by code_factory.py
+
+from numba import njit
+
+
+@njit
+def energy_grid(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["energy_grid_offset"]
+    return data[offset + index]
+
+
+@njit
+def energy_grid_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["energy_grid_offset"]
+    size = neutron_multigroup_data["G"] + 1
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def energy_grid_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["energy_grid_offset"]
+    size = neutron_multigroup_data["G"] + 1
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def energy_grid_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["energy_grid_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def speed(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["speed_offset"]
+    return data[offset + index]
+
+
+@njit
+def speed_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["speed_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def speed_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["speed_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def speed_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["speed_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def decay_rate(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["decay_rate_offset"]
+    return data[offset + index]
+
+
+@njit
+def decay_rate_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["decay_rate_offset"]
+    size = neutron_multigroup_data["J"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def decay_rate_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["decay_rate_offset"]
+    size = neutron_multigroup_data["J"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def decay_rate_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["decay_rate_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def capture(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["capture_offset"]
+    return data[offset + index]
+
+
+@njit
+def capture_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["capture_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def capture_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["capture_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def capture_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["capture_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def scatter(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["scatter_offset"]
+    return data[offset + index]
+
+
+@njit
+def scatter_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["scatter_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def scatter_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["scatter_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def scatter_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["scatter_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def fission(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["fission_offset"]
+    return data[offset + index]
+
+
+@njit
+def fission_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["fission_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def fission_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["fission_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def fission_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["fission_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def total(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["total_offset"]
+    return data[offset + index]
+
+
+@njit
+def total_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["total_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def total_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["total_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def total_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["total_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_s(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["nu_s_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_s_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["nu_s_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_s_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["nu_s_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_s_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["nu_s_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_p(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["nu_p_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_p_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["nu_p_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_p_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["nu_p_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_p_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["nu_p_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_d_vector(index_1, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["nu_d_offset"]
+    stride = neutron_multigroup_data["J"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def nu_d(index_1, index_2, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["nu_d_offset"]
+    stride = neutron_multigroup_data["J"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def nu_d_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["nu_d_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_d_total(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["nu_d_total_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_d_total_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["nu_d_total_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_d_total_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["nu_d_total_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_d_total_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["nu_d_total_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def nu_f(index, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["nu_f_offset"]
+    return data[offset + index]
+
+
+@njit
+def nu_f_all(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["nu_f_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def nu_f_last(neutron_multigroup_data, data):
+    start = neutron_multigroup_data["nu_f_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def nu_f_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["nu_f_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def chi_s_vector(index_1, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["chi_s_offset"]
+    stride = neutron_multigroup_data["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def chi_s(index_1, index_2, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["chi_s_offset"]
+    stride = neutron_multigroup_data["G"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def chi_s_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["chi_s_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def chi_p_vector(index_1, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["chi_p_offset"]
+    stride = neutron_multigroup_data["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def chi_p(index_1, index_2, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["chi_p_offset"]
+    stride = neutron_multigroup_data["G"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def chi_p_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["chi_p_offset"]
+    end = start + length
+    return data[start:end]
+
+
+@njit
+def chi_d_vector(index_1, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["chi_d_offset"]
+    stride = neutron_multigroup_data["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    return data[start:end]
+
+
+@njit
+def chi_d(index_1, index_2, neutron_multigroup_data, data):
+    offset = neutron_multigroup_data["chi_d_offset"]
+    stride = neutron_multigroup_data["G"]
+    return data[offset + index_1 * stride + index_2]
+
+
+@njit
+def chi_d_chunk(start, length, neutron_multigroup_data, data):
+    start += neutron_multigroup_data["chi_d_offset"]
+    end = start + length
+    return data[start:end]
diff --git a/mcdc/mcdc_get/technique.py b/mcdc/mcdc_get/technique.py
new file mode 100644
index 000000000..fdbf8e750
--- /dev/null
+++ b/mcdc/mcdc_get/technique.py
@@ -0,0 +1,3 @@
+# The following is automatically generated by code_factory.py
+
+from numba import njit
diff --git a/mcdc/mcdc_set/__init__.py b/mcdc/mcdc_set/__init__.py
index 7fdc53d3c..26eedd8ba 100644
--- a/mcdc/mcdc_set/__init__.py
+++ b/mcdc/mcdc_set/__init__.py
@@ -60,7 +60,7 @@
 
 import mcdc.mcdc_set.gpu_meta as gpu_meta
 
-import mcdc.mcdc_set.neutron_multigroup as neutron_multigroup
+import mcdc.mcdc_set.neutron_multigroup_data as neutron_multigroup_data
 
 import mcdc.mcdc_set.nuclide as nuclide
 
@@ -86,24 +86,28 @@
 
 import mcdc.mcdc_set.settings as settings
 
+import mcdc.mcdc_set.technique as technique
+
+import mcdc.mcdc_set.source as source
+
+import mcdc.mcdc_set.surface as surface
+
+import mcdc.mcdc_set.surface_crossing_tally as surface_crossing_tally
+
+import mcdc.mcdc_set.tally as tally
+
 import mcdc.mcdc_set.global_weight_roulette as global_weight_roulette
 
 import mcdc.mcdc_set.implicit_capture as implicit_capture
 
+import mcdc.mcdc_set.neutron_multigroup as neutron_multigroup
+
 import mcdc.mcdc_set.population_control as population_control
 
 import mcdc.mcdc_set.weight_windows as weight_windows
 
 import mcdc.mcdc_set.weighted_emission as weighted_emission
 
-import mcdc.mcdc_set.source as source
-
-import mcdc.mcdc_set.surface as surface
-
-import mcdc.mcdc_set.surface_crossing_tally as surface_crossing_tally
-
-import mcdc.mcdc_set.tally as tally
-
 import mcdc.mcdc_set.bank_active as bank_active
 
 import mcdc.mcdc_set.bank_census as bank_census
diff --git a/mcdc/mcdc_set/neutron_multigroup.py b/mcdc/mcdc_set/neutron_multigroup.py
index 03ed012af..fdbf8e750 100644
--- a/mcdc/mcdc_set/neutron_multigroup.py
+++ b/mcdc/mcdc_set/neutron_multigroup.py
@@ -1,414 +1,3 @@
 # The following is automatically generated by code_factory.py
 
 from numba import njit
-
-
-@njit
-def energy_grid(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["energy_grid_offset"]
-    data[offset + index] = value
-
-
-@njit
-def energy_grid_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["energy_grid_offset"]
-    size = neutron_multigroup["G"] + 1
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def energy_grid_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["energy_grid_offset"]
-    size = neutron_multigroup["G"] + 1
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def energy_grid_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["energy_grid_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def speed(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["speed_offset"]
-    data[offset + index] = value
-
-
-@njit
-def speed_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["speed_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def speed_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["speed_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def speed_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["speed_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def decay_rate(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["decay_rate_offset"]
-    data[offset + index] = value
-
-
-@njit
-def decay_rate_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["decay_rate_offset"]
-    size = neutron_multigroup["J"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def decay_rate_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["decay_rate_offset"]
-    size = neutron_multigroup["J"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def decay_rate_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["decay_rate_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def capture(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["capture_offset"]
-    data[offset + index] = value
-
-
-@njit
-def capture_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["capture_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def capture_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["capture_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def capture_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["capture_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def scatter(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["scatter_offset"]
-    data[offset + index] = value
-
-
-@njit
-def scatter_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["scatter_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def scatter_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["scatter_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def scatter_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["scatter_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def fission(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["fission_offset"]
-    data[offset + index] = value
-
-
-@njit
-def fission_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["fission_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def fission_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["fission_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def fission_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["fission_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def total(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["total_offset"]
-    data[offset + index] = value
-
-
-@njit
-def total_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["total_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def total_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["total_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def total_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["total_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nu_s(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["nu_s_offset"]
-    data[offset + index] = value
-
-
-@njit
-def nu_s_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["nu_s_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def nu_s_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["nu_s_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def nu_s_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["nu_s_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nu_p(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["nu_p_offset"]
-    data[offset + index] = value
-
-
-@njit
-def nu_p_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["nu_p_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def nu_p_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["nu_p_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def nu_p_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["nu_p_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nu_d_vector(index_1, neutron_multigroup, data, value):
-    offset = neutron_multigroup["nu_d_offset"]
-    stride = neutron_multigroup["J"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def nu_d(index_1, index_2, neutron_multigroup, data, value):
-    offset = neutron_multigroup["nu_d_offset"]
-    stride = neutron_multigroup["J"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def nu_d_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["nu_d_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nu_d_total(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["nu_d_total_offset"]
-    data[offset + index] = value
-
-
-@njit
-def nu_d_total_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["nu_d_total_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def nu_d_total_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["nu_d_total_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def nu_d_total_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["nu_d_total_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def nu_f(index, neutron_multigroup, data, value):
-    offset = neutron_multigroup["nu_f_offset"]
-    data[offset + index] = value
-
-
-@njit
-def nu_f_all(neutron_multigroup, data, value):
-    start = neutron_multigroup["nu_f_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def nu_f_last(neutron_multigroup, data, value):
-    start = neutron_multigroup["nu_f_offset"]
-    size = neutron_multigroup["G"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def nu_f_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["nu_f_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def chi_s_vector(index_1, neutron_multigroup, data, value):
-    offset = neutron_multigroup["chi_s_offset"]
-    stride = neutron_multigroup["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def chi_s(index_1, index_2, neutron_multigroup, data, value):
-    offset = neutron_multigroup["chi_s_offset"]
-    stride = neutron_multigroup["G"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def chi_s_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["chi_s_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def chi_p_vector(index_1, neutron_multigroup, data, value):
-    offset = neutron_multigroup["chi_p_offset"]
-    stride = neutron_multigroup["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def chi_p(index_1, index_2, neutron_multigroup, data, value):
-    offset = neutron_multigroup["chi_p_offset"]
-    stride = neutron_multigroup["G"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def chi_p_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["chi_p_offset"]
-    end = start + length
-    data[start:end] = value
-
-
-@njit
-def chi_d_vector(index_1, neutron_multigroup, data, value):
-    offset = neutron_multigroup["chi_d_offset"]
-    stride = neutron_multigroup["G"]
-    start = offset + index_1 * stride
-    end = start + stride
-    data[start:end] = value
-
-
-@njit
-def chi_d(index_1, index_2, neutron_multigroup, data, value):
-    offset = neutron_multigroup["chi_d_offset"]
-    stride = neutron_multigroup["G"]
-    data[offset + index_1 * stride + index_2] = value
-
-
-@njit
-def chi_d_chunk(start, length, neutron_multigroup, data, value):
-    start += neutron_multigroup["chi_d_offset"]
-    end = start + length
-    data[start:end] = value
diff --git a/mcdc/mcdc_set/neutron_multigroup_data.py b/mcdc/mcdc_set/neutron_multigroup_data.py
new file mode 100644
index 000000000..dff8f10b1
--- /dev/null
+++ b/mcdc/mcdc_set/neutron_multigroup_data.py
@@ -0,0 +1,414 @@
+# The following is automatically generated by code_factory.py
+
+from numba import njit
+
+
+@njit
+def energy_grid(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["energy_grid_offset"]
+    data[offset + index] = value
+
+
+@njit
+def energy_grid_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["energy_grid_offset"]
+    size = neutron_multigroup_data["G"] + 1
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def energy_grid_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["energy_grid_offset"]
+    size = neutron_multigroup_data["G"] + 1
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def energy_grid_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["energy_grid_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def speed(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["speed_offset"]
+    data[offset + index] = value
+
+
+@njit
+def speed_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["speed_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def speed_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["speed_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def speed_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["speed_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def decay_rate(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["decay_rate_offset"]
+    data[offset + index] = value
+
+
+@njit
+def decay_rate_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["decay_rate_offset"]
+    size = neutron_multigroup_data["J"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def decay_rate_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["decay_rate_offset"]
+    size = neutron_multigroup_data["J"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def decay_rate_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["decay_rate_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def capture(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["capture_offset"]
+    data[offset + index] = value
+
+
+@njit
+def capture_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["capture_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def capture_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["capture_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def capture_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["capture_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def scatter(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["scatter_offset"]
+    data[offset + index] = value
+
+
+@njit
+def scatter_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["scatter_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def scatter_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["scatter_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def scatter_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["scatter_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def fission(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["fission_offset"]
+    data[offset + index] = value
+
+
+@njit
+def fission_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["fission_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def fission_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["fission_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def fission_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["fission_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def total(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["total_offset"]
+    data[offset + index] = value
+
+
+@njit
+def total_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["total_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def total_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["total_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def total_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["total_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_s(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["nu_s_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_s_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["nu_s_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_s_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["nu_s_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_s_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["nu_s_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_p(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["nu_p_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_p_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["nu_p_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_p_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["nu_p_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_p_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["nu_p_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_d_vector(index_1, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["nu_d_offset"]
+    stride = neutron_multigroup_data["J"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def nu_d(index_1, index_2, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["nu_d_offset"]
+    stride = neutron_multigroup_data["J"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def nu_d_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["nu_d_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_d_total(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["nu_d_total_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_d_total_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["nu_d_total_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_d_total_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["nu_d_total_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_d_total_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["nu_d_total_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def nu_f(index, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["nu_f_offset"]
+    data[offset + index] = value
+
+
+@njit
+def nu_f_all(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["nu_f_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def nu_f_last(neutron_multigroup_data, data, value):
+    start = neutron_multigroup_data["nu_f_offset"]
+    size = neutron_multigroup_data["G"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def nu_f_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["nu_f_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def chi_s_vector(index_1, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["chi_s_offset"]
+    stride = neutron_multigroup_data["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def chi_s(index_1, index_2, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["chi_s_offset"]
+    stride = neutron_multigroup_data["G"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def chi_s_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["chi_s_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def chi_p_vector(index_1, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["chi_p_offset"]
+    stride = neutron_multigroup_data["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def chi_p(index_1, index_2, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["chi_p_offset"]
+    stride = neutron_multigroup_data["G"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def chi_p_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["chi_p_offset"]
+    end = start + length
+    data[start:end] = value
+
+
+@njit
+def chi_d_vector(index_1, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["chi_d_offset"]
+    stride = neutron_multigroup_data["G"]
+    start = offset + index_1 * stride
+    end = start + stride
+    data[start:end] = value
+
+
+@njit
+def chi_d(index_1, index_2, neutron_multigroup_data, data, value):
+    offset = neutron_multigroup_data["chi_d_offset"]
+    stride = neutron_multigroup_data["G"]
+    data[offset + index_1 * stride + index_2] = value
+
+
+@njit
+def chi_d_chunk(start, length, neutron_multigroup_data, data, value):
+    start += neutron_multigroup_data["chi_d_offset"]
+    end = start + length
+    data[start:end] = value
diff --git a/mcdc/mcdc_set/technique.py b/mcdc/mcdc_set/technique.py
new file mode 100644
index 000000000..fdbf8e750
--- /dev/null
+++ b/mcdc/mcdc_set/technique.py
@@ -0,0 +1,3 @@
+# The following is automatically generated by code_factory.py
+
+from numba import njit
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index 7ffe8fb19..78202941b 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -342,10 +342,9 @@
     ('ID', int64),
 ])
 
-neutron_multigroup = into_dtype([
+neutron_multigroup_data = into_dtype([
     ('G', int64),
     ('J', int64),
-    ('has_energy_grid', bool),
     ('energy_grid_offset', int64),
     ('energy_grid_length', int64),
     ('energy_representation', int64),
@@ -541,25 +540,29 @@
     ('neutron_transport', bool),
     ('electron_transport', bool),
     ('proton_transport', bool),
-    ('neutron_multigroup_mode', bool),
     ('neutron_eigenvalue_mode', bool),
     ('gpu_strategy', int64),
     ('gpu_async_type', int64),
     ('gpu_storage', int64),
 ])
 
-global_weight_roulette = into_dtype([
-    ('active', bool),
-    ('weight_threshold', float64),
-    ('weight_target', float64),
+neutron_multigroup = into_dtype([
+    ('multigrid', bool),
 ])
 
 implicit_capture = into_dtype([
     ('active', bool),
 ])
 
-population_control = into_dtype([
+weighted_emission = into_dtype([
+    ('active', bool),
+    ('weight_target', float64),
+])
+
+global_weight_roulette = into_dtype([
     ('active', bool),
+    ('weight_threshold', float64),
+    ('weight_target', float64),
 ])
 
 weight_windows = into_dtype([
@@ -579,9 +582,17 @@
     ('upper_weights_length', int64),
 ])
 
-weighted_emission = into_dtype([
+population_control = into_dtype([
     ('active', bool),
-    ('weight_target', float64),
+])
+
+technique = into_dtype([
+    ('neutron_multigroup', neutron_multigroup),
+    ('implicit_capture', implicit_capture),
+    ('weighted_emission', weighted_emission),
+    ('global_weight_roulette', global_weight_roulette),
+    ('weight_windows', weight_windows),
+    ('population_control', population_control),
 ])
 
 source = into_dtype([
@@ -804,8 +815,8 @@ def set_simulation(N: dict):
         ('N_element', int64),
         ('materials', material, (N['material'])),
         ('N_material', int64),
-        ('neutron_multigroup', neutron_multigroup, (N['neutron_multigroup'])),
-        ('N_neutron_multigroup', int64),
+        ('neutron_multigroup_data', neutron_multigroup_data, (N['neutron_multigroup_data'])),
+        ('N_neutron_multigroup_data', int64),
         ('sources', source, (N['source'])),
         ('N_source', int64),
         ('surfaces', surface, (N['surface'])),
@@ -831,11 +842,7 @@ def set_simulation(N: dict):
         ('tallies', tally, (N['tally'])),
         ('N_tally', int64),
         ('settings', settings),
-        ('implicit_capture', implicit_capture),
-        ('weighted_emission', weighted_emission),
-        ('global_weight_roulette', global_weight_roulette),
-        ('weight_windows', weight_windows),
-        ('population_control', population_control),
+        ('technique', technique),
         ('gpu_meta', gpu_meta),
         ('bank_future', bank_future),
         ('bank_source', bank_source),
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 8cf70f5cf..67574adab 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -7,7 +7,7 @@
 
 from mcdc.object_.base import MCDCObject
 from mcdc.object_.element import Element
-from mcdc.object_.transport_model import NeutronMultigroup
+from mcdc.object_.transport_model_data import NeutronMultigroupData
 from mcdc.object_.nuclide import Nuclide
 from mcdc.object_.util import ISOTOPIC_ABUNDANCE
 from mcdc.print_ import print_error
@@ -31,10 +31,10 @@ class Material(MCDCObject):
     temperature : float, optional
         Material temperature in kelvin. Each nuclide uses the closest
         temperature available in the data library.
-    neutron_multigroup : NeutronMultigroup, optional
+    neutron_multigroup : NeutronMultigroupData, optional
         Multigroup cross sections for neutron transport. When supplied with a
-        native composition, its ``energy_grid`` is required and defines the
-        energy range over which multigroup physics applies.
+        native composition, its ``energy_grid`` defines the energy range over
+        which multigroup physics applies.
 
     Notes
     -----
@@ -42,9 +42,8 @@ class Material(MCDCObject):
     Nuclide and element compositions cannot both be specified because they are
     alternative native representations of the same material. A native
     composition may be supplied together with ``neutron_multigroup`` for hybrid
-    neutron physics. Hybrid materials require an explicit ``NeutronMultigroup``
-    energy grid so collision physics can select between native and multigroup
-    data.
+    neutron physics. An omitted multigroup energy grid uses the default
+    group-coordinate boundaries.
 
     Nuclide and element objects are created immediately; their data-library
     properties are loaded when the material is compiled into a simulation.
@@ -73,7 +72,7 @@ class Material(MCDCObject):
     >>> hybrid_fuel = mcdc.Material(
     ...     name="Hybrid fuel",
     ...     nuclide_composition={"U235": 5.0e-4, "U238": 2.2e-2},
-    ...     neutron_multigroup=mcdc.NeutronMultigroup(
+    ...     neutron_multigroup=mcdc.NeutronMultigroupData(
     ...         capture=np.array([0.10]),
     ...         fission=np.array([0.20]),
     ...         nu_p=np.array([2.50]),
@@ -93,7 +92,7 @@ class Material(MCDCObject):
 
     nuclide_composition: dict[Nuclide, float]  # Non-Numba
     element_composition: dict[Element, float]  # Non-Numba
-    neutron_multigroup: NeutronMultigroup
+    neutron_multigroup: NeutronMultigroupData
 
     nuclides: list[Nuclide]
     elements: list[Element]
@@ -106,7 +105,7 @@ def __init__(
         nuclide_composition: dict[str, float] | NoneType = None,
         element_composition: dict[str, float] | NoneType = None,
         temperature: float = 293.6,
-        neutron_multigroup: NeutronMultigroup | NoneType = None,
+        neutron_multigroup: NeutronMultigroupData | NoneType = None,
     ) -> None:
         super().__init__()
 
@@ -129,21 +128,9 @@ def __init__(
                 "or neutron_multigroup."
             )
         if neutron_multigroup is not None and not isinstance(
-            neutron_multigroup, NeutronMultigroup
+            neutron_multigroup, NeutronMultigroupData
         ):
-            print_error("neutron_multigroup must be a NeutronMultigroup object.")
-        native_composition_supplied = bool(nuclide_composition or element_composition)
-        if (
-            native_composition_supplied
-            and neutron_multigroup is not None
-            and neutron_multigroup.G > 0
-            and not neutron_multigroup.has_energy_grid
-        ):
-            print_error(
-                "Material with both a native composition and neutron_multigroup "
-                "requires neutron_multigroup.energy_grid."
-            )
-
+            print_error("neutron_multigroup must be a NeutronMultigroupData object.")
         # Initialize shared material state
         self.name = name or "(Unnamed material)"
         self.temperature = float(temperature)
@@ -152,7 +139,7 @@ def __init__(
         self.neutron_multigroup = (
             neutron_multigroup
             if neutron_multigroup is not None
-            else NeutronMultigroup()
+            else NeutronMultigroupData()
         )
         self.has_neutron_multigroup = self.neutron_multigroup.G > 0
         self.fissionable = self.neutron_multigroup.fissionable
@@ -194,16 +181,16 @@ def multigroup(
         speed: ArrayLike | NoneType = None,
         decay_rate: ArrayLike | NoneType = None,
         energy_grid: ArrayLike | NoneType = None,
-        energy_representation: str | int = "log_midpoint",
+        energy_representation: str | int = "midpoint",
     ) -> Self:
         """Construct a material containing only multigroup neutron data.
 
-        The transport arguments are forwarded to :class:`NeutronMultigroup`.
+        The transport arguments are forwarded to :class:`NeutronMultigroupData`.
         Use the regular constructor when combining multigroup data with a
         native nuclide or element composition.
         """
-        # Build the transport model while preserving Material as the sole type
-        neutron_multigroup = NeutronMultigroup(
+        # Build the transport-mode data while preserving Material as the sole type
+        neutron_multigroup = NeutronMultigroupData(
             capture=capture,
             scatter=scatter,
             fission=fission,
@@ -253,7 +240,7 @@ def _compile_into_simulation(self, simulation) -> bool:
 
         # Point absent multigroup data to the reserved neutron model
         if self.neutron_multigroup.G == 0:
-            self.neutron_multigroup = simulation.neutron_multigroup[0]
+            self.neutron_multigroup = simulation.neutron_multigroup_data[0]
         self.has_neutron_multigroup = self.neutron_multigroup.G > 0
 
         # Register the material, then compile only canonical owned members
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index 7b6421e90..2ba992987 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -83,7 +83,6 @@ class Settings(MCDCBase):
     proton_transport: bool = False
 
     # Neutron transport modes
-    neutron_multigroup_mode: bool = False
     neutron_eigenvalue_mode: bool = False
 
     # GPU mode
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 1fc88f88b..e328483af 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -6,7 +6,7 @@
     from mcdc.object_.element import Element
     from mcdc.object_.electron_reaction import ElectronReactionBase
     from mcdc.object_.material import Material
-    from mcdc.object_.transport_model import NeutronMultigroup
+    from mcdc.object_.transport_model_data import NeutronMultigroupData
     from mcdc.object_.nuclide import Nuclide
     from mcdc.object_.neutron_reaction import NeutronReactionBase
     from mcdc.object_.source import Source
@@ -32,13 +32,8 @@
 from mcdc.object_.mesh import MeshBase
 from mcdc.object_.particle import ParticleBank
 from mcdc.object_.settings import Settings
-from mcdc.object_.technique import (
-    ImplicitCapture,
-    PopulationControl,
-    GlobalWeightRoulette,
-    WeightWindows,
-    WeightedEmission,
-)
+from mcdc.object_.technique import Technique
+from mcdc.print_ import print_error
 
 from mcdc.object_.universe import Universe, Lattice
 
@@ -74,9 +69,10 @@ class Simulation(MCDCBase):
     calling configuration methods such as
     :meth:`settings.set_eigenmode <mcdc.Simulation.settings.set_eigenmode>`.
 
-    Transport techniques are configured directly on the simulation through
-    methods such as :meth:`implicit_capture <mcdc.Simulation.implicit_capture>`
-    and :meth:`weight_windows <mcdc.Simulation.weight_windows>`.
+    Transport techniques are grouped under ``simulation.technique`` and are
+    configured through callable members such as
+    ``simulation.technique.implicit_capture()`` and
+    ``simulation.technique.weight_windows(...)``.
 
     Examples
     --------
@@ -116,7 +112,7 @@ class Simulation(MCDCBase):
     nuclides: list[Nuclide]
     elements: list[Element]
     materials: list[Material]
-    neutron_multigroup: list[NeutronMultigroup]
+    neutron_multigroup_data: list[NeutronMultigroupData]
     sources: list[Source]
 
     # Geometry
@@ -135,11 +131,7 @@ class Simulation(MCDCBase):
     settings: Settings
 
     # Techniques
-    implicit_capture: ImplicitCapture
-    weighted_emission: WeightedEmission
-    global_weight_roulette: GlobalWeightRoulette
-    weight_windows: WeightWindows
-    population_control: PopulationControl
+    technique: Technique
 
     # Particle banks
     bank_active: ParticleBank  # Non-Numba
@@ -216,12 +208,7 @@ def __init__(self, name: str = "") -> None:
 
         self.settings = Settings()
 
-        # Techniques
-        self.implicit_capture = ImplicitCapture()
-        self.weighted_emission = WeightedEmission()
-        self.global_weight_roulette = GlobalWeightRoulette()
-        self.weight_windows = WeightWindows()
-        self.population_control = PopulationControl()
+        self.technique = Technique()
 
         # ==============================================================================
         # Particle banks
@@ -295,7 +282,7 @@ def _reset_model(self) -> None:
         self.nuclides = []
         self.elements = []
         self.materials = []
-        self.neutron_multigroup = []
+        self.neutron_multigroup_data = []
 
         # Geometry
         self.surfaces = []
@@ -323,6 +310,25 @@ def _finalize_compilation(self) -> None:
 
         settings = self.settings
 
+        # Require one shared grid unless multigrid was explicitly enabled
+        neutron_multigroup_data = [
+            model for model in self.neutron_multigroup_data if model.G > 0
+        ]
+        if (
+            not self.technique.neutron_multigroup.multigrid
+            and len(neutron_multigroup_data) > 1
+        ):
+            shared_grid = neutron_multigroup_data[0].energy_grid
+            if any(
+                not np.array_equal(model.energy_grid, shared_grid)
+                for model in neutron_multigroup_data[1:]
+            ):
+                print_error(
+                    "Neutron multigroup energy grids must be identical unless "
+                    "simulation.technique.neutron_multigroup(multigrid=True) is "
+                    "configured."
+                )
+
         # Limit transport to the latest requested tally boundary
         settings.time_boundary = min(
             [settings.time_boundary] + [tally.time[-1] for tally in self.tallies]
@@ -354,12 +360,6 @@ def _finalize_compilation(self) -> None:
             for element in self.elements:
                 element.set_electron_data(self)
 
-        # Preserve the current full-MG transport switch until collision-level
-        # dispatch can select neutron multigroup physics by material and energy.
-        settings.neutron_multigroup_mode = len(self.materials) == 0 or all(
-            material.neutron_multigroup.G > 0 for material in self.materials
-        )
-
         # Derive tally shapes that depend on simulation-wide settings
         if settings.use_census_based_tally:
             for tally in self.tallies:
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index 219363538..0589cfeec 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -7,6 +7,42 @@
 from numpy.typing import NDArray
 from typing import Annotated
 
+# ======================================================================================
+# Neutron multigroup
+# ======================================================================================
+
+
+class NeutronMultigroupTechnique(MCDCBase):
+    """Configure simulation-wide neutron multigroup behavior."""
+
+    # MC/DC framework metadata
+    label = "neutron_multigroup"
+
+    multigrid: bool
+
+    def __init__(self):
+        self.multigrid = False
+
+    def __call__(self, multigrid: bool = False):
+        """Configure whether multiple neutron energy grids are allowed.
+
+        Parameters
+        ----------
+        multigrid : bool, optional
+            Allow materials to use different neutron multigroup energy grids.
+            By default, compilation requires one shared grid.
+
+        Examples
+        --------
+        Allow material-local neutron multigroup grids:
+
+        >>> import mcdc
+        >>> simulation = mcdc.Simulation()
+        >>> simulation.technique.neutron_multigroup(multigrid=True)
+        """
+        self.multigrid = multigrid
+
+
 # ======================================================================================
 # Implicit capture
 # ======================================================================================
@@ -37,11 +73,11 @@ def __call__(self, active: bool = True):
 
         >>> import mcdc
         >>> simulation = mcdc.Simulation()
-        >>> simulation.implicit_capture()
+        >>> simulation.technique.implicit_capture()
 
         Disable implicit capture:
 
-        >>> simulation.implicit_capture(active=False)
+        >>> simulation.technique.implicit_capture(active=False)
         """
         self.active = active
 
@@ -80,15 +116,15 @@ def __call__(self, active: bool = True, weight_target: float = 1.0):
 
         >>> import mcdc
         >>> simulation = mcdc.Simulation()
-        >>> simulation.weighted_emission(weight_target=1.0)
+        >>> simulation.technique.weighted_emission(weight_target=1.0)
 
         Select a different target weight:
 
-        >>> simulation.weighted_emission(weight_target=0.5)
+        >>> simulation.technique.weighted_emission(weight_target=0.5)
 
         Disable weighted emission:
 
-        >>> simulation.weighted_emission(active=False)
+        >>> simulation.technique.weighted_emission(active=False)
         """
         self.active = active
         self.weight_target = weight_target
@@ -132,14 +168,14 @@ def __call__(self, weight_threshold: float = 0.0, weight_target: float = 1.0):
 
         >>> import mcdc
         >>> simulation = mcdc.Simulation()
-        >>> simulation.global_weight_roulette(
+        >>> simulation.technique.global_weight_roulette(
         ...     weight_threshold=0.25,
         ...     weight_target=1.0,
         ... )
 
         Use a lower target weight:
 
-        >>> simulation.global_weight_roulette(
+        >>> simulation.technique.global_weight_roulette(
         ...     weight_threshold=0.1,
         ...     weight_target=0.5,
         ... )
@@ -215,19 +251,19 @@ def __call__(self, weight_windows, mesh=None, energy=None):
         >>> import mcdc
         >>> simulation = mcdc.Simulation()
         >>> windows = np.array([0.5, 1.0, 2.0]).reshape(1, 1, 1, 1, 3)
-        >>> simulation.weight_windows(windows)
+        >>> simulation.technique.weight_windows(windows)
 
         Configure weight windows on a uniform spatial mesh:
 
         >>> mesh = mcdc.MeshUniform(x=(-5.0, 1.0, 10))
         >>> windows = np.tile([0.25, 0.5, 1.0], (1, 10, 1, 1, 1))
-        >>> simulation.weight_windows(windows, mesh=mesh)
+        >>> simulation.technique.weight_windows(windows, mesh=mesh)
 
         Configure both energy- and space-dependent windows:
 
         >>> energy = np.array([0.0, 0.625e-6, 20.0])
         >>> windows = np.tile([0.25, 0.5, 1.0], (2, 10, 1, 1, 1))
-        >>> simulation.weight_windows(
+        >>> simulation.technique.weight_windows(
         ...     windows,
         ...     mesh=mesh,
         ...     energy=energy,
@@ -328,10 +364,43 @@ def __call__(self, active: bool = True):
 
         >>> import mcdc
         >>> simulation = mcdc.Simulation()
-        >>> simulation.population_control()
+        >>> simulation.technique.population_control()
 
         Disable source-bank population control:
 
-        >>> simulation.population_control(active=False)
+        >>> simulation.technique.population_control(active=False)
         """
         self.active = active
+
+
+# ======================================================================================
+# Simulation technique collection
+# ======================================================================================
+
+
+class Technique(MCDCBase):
+    """Own all simulation-wide transport-technique configurations.
+
+    Access the individual callable configurations through
+    ``simulation.technique``. The same hierarchy is retained in the packed
+    runtime simulation.
+    """
+
+    # MC/DC framework metadata
+    label = "technique"
+
+    neutron_multigroup: NeutronMultigroupTechnique
+    implicit_capture: ImplicitCapture
+    weighted_emission: WeightedEmission
+    global_weight_roulette: GlobalWeightRoulette
+    weight_windows: WeightWindows
+    population_control: PopulationControl
+
+    def __init__(self):
+        # Construct every simulation-wide technique configuration
+        self.neutron_multigroup = NeutronMultigroupTechnique()
+        self.implicit_capture = ImplicitCapture()
+        self.weighted_emission = WeightedEmission()
+        self.global_weight_roulette = GlobalWeightRoulette()
+        self.weight_windows = WeightWindows()
+        self.population_control = PopulationControl()
diff --git a/mcdc/object_/transport_model.py b/mcdc/object_/transport_model_data.py
similarity index 84%
rename from mcdc/object_/transport_model.py
rename to mcdc/object_/transport_model_data.py
index b73d0cc9b..52829c591 100644
--- a/mcdc/object_/transport_model.py
+++ b/mcdc/object_/transport_model_data.py
@@ -26,10 +26,10 @@
 }
 
 
-class NeutronMultigroup(MCDCObject):
-    """Define a multigroup transport model for neutrons.
+class NeutronMultigroupData(MCDCObject):
+    """Store the cross-section data for multigroup neutron transport.
 
-    Materials may use ``NeutronMultigroup`` alone for multigroup transport or
+    Materials may use ``NeutronMultigroupData`` alone for multigroup transport or
     alongside a native composition over the energy range defined by
     ``energy_grid``.
 
@@ -74,20 +74,20 @@ class NeutronMultigroup(MCDCObject):
     energy_grid : array_like of float, optional
         Strictly increasing energy-group boundaries with shape ``(G + 1,)``.
         Group ``g`` spans ``energy_grid[g] <= E < energy_grid[g + 1]``. The
-        array may be omitted before compilation when a shared grid will be
-        supplied.
+        default is the group-coordinate grid
+        ``[1.0e-6 - 0.5, 0.5, 1.5, ...]``.
     energy_representation : str or int, optional
         Policy used to reconstruct continuous energy from a group. Midpoint
         policies select the arithmetic or geometric midpoint; uniform policies
         sample uniformly in energy or log-energy. The default is
-        ``"log_midpoint"``. Logarithmic policies require positive boundaries.
+        ``"midpoint"``. Logarithmic policies require positive boundaries.
         The corresponding ``NEUTRON_MULTIGROUP_ENERGY_*`` integer constants
         are also accepted.
 
     Notes
     -----
     ``G`` is inferred from ``capture``, ``scatter``, or ``fission``. Calling
-    ``NeutronMultigroup()`` without any cross sections creates the reserved
+    ``NeutronMultigroupData()`` without any cross sections creates the reserved
     zero-group placeholder used by materials without multigroup data. Cross
     sections are macroscopic and use inverse-length units.
 
@@ -97,7 +97,7 @@ class NeutronMultigroup(MCDCObject):
 
     >>> import mcdc
     >>> import numpy as np
-    >>> neutron_multigroup = mcdc.NeutronMultigroup(
+    >>> neutron_multigroup = mcdc.NeutronMultigroupData(
     ...     capture=np.array([1.0 / 3.0]),
     ...     scatter=np.array([[1.0 / 3.0]]),
     ...     fission=np.array([1.0 / 3.0]),
@@ -108,7 +108,7 @@ class NeutronMultigroup(MCDCObject):
     Construct data with two energy groups. Scattering is indexed by outgoing
     then incoming group:
 
-    >>> two_group = mcdc.NeutronMultigroup(
+    >>> two_group = mcdc.NeutronMultigroupData(
     ...     capture=np.array([0.1, 0.2]),
     ...     scatter=np.array([
     ...         [1.0, 2.0],
@@ -122,7 +122,7 @@ class NeutronMultigroup(MCDCObject):
     delayed yield is indexed by precursor then incoming energy group, while
     the delayed spectrum is indexed by outgoing energy then precursor group:
 
-    >>> multiple_precursors = mcdc.NeutronMultigroup(
+    >>> multiple_precursors = mcdc.NeutronMultigroupData(
     ...     fission=np.array([0.2, 0.3]),
     ...     nu_d=np.array([
     ...         [0.1, 0.2],
@@ -137,12 +137,11 @@ class NeutronMultigroup(MCDCObject):
     """
 
     # MC/DC framework metadata
-    label = "neutron_multigroup"
+    label = "neutron_multigroup_data"
 
     G: int
     J: int
 
-    has_energy_grid: bool
     energy_grid: Annotated[NDArray[float64], ("G+1",)]
     energy_representation: int
 
@@ -179,7 +178,7 @@ def __init__(
         speed: ArrayLike | NoneType = None,
         decay_rate: ArrayLike | NoneType = None,
         energy_grid: ArrayLike | NoneType = None,
-        energy_representation: str | int = "log_midpoint",
+        energy_representation: str | int = "midpoint",
     ) -> None:
         super().__init__()
 
@@ -230,31 +229,31 @@ def __init__(
 
         # Validate relationships between fission yields and spectra
         if fission is not None and nu_p is None and nu_d is None:
-            print_error("NeutronMultigroup fission data requires nu_p or nu_d.")
+            print_error("NeutronMultigroupData fission data requires nu_p or nu_d.")
         if fission is None and (nu_p is not None or nu_d is not None):
             print_error(
-                "NeutronMultigroup fission yields require fission cross sections."
+                "NeutronMultigroupData fission yields require fission cross sections."
             )
         if chi_p is not None and nu_p is None:
-            print_error("NeutronMultigroup chi_p requires nu_p.")
+            print_error("NeutronMultigroupData chi_p requires nu_p.")
         if chi_d is not None and nu_d is None:
-            print_error("NeutronMultigroup chi_d requires nu_d.")
+            print_error("NeutronMultigroupData chi_d requires nu_d.")
         if decay_rate is not None and nu_d is None:
-            print_error("NeutronMultigroup decay_rate requires nu_d.")
+            print_error("NeutronMultigroupData decay_rate requires nu_d.")
 
         # Resolve the energy grid and continuous-energy reconstruction policy
         self.energy_representation = _resolve_energy_representation(
             energy_representation
         )
-        self.has_energy_grid = energy_grid is not None
         if energy_grid is None:
-            self.energy_grid = np.zeros(self.G + 1, dtype=float64)
+            self.energy_grid = np.arange(self.G + 1, dtype=float64) - 0.5
+            self.energy_grid[0] += 1.0e-6
         else:
             if not np.all(np.isfinite(energy_grid)):
-                print_error("NeutronMultigroup energy grid entries must be finite.")
+                print_error("NeutronMultigroupData energy grid entries must be finite.")
             if np.any(np.diff(energy_grid) <= 0.0):
                 print_error(
-                    "NeutronMultigroup energy grid must be strictly increasing."
+                    "NeutronMultigroupData energy grid must be strictly increasing."
                 )
             if (
                 self.energy_representation
@@ -262,7 +261,7 @@ def __init__(
                 and energy_grid[0] <= 0.0
             ):
                 print_error(
-                    "NeutronMultigroup logarithmic energy representation requires positive "
+                    "NeutronMultigroupData logarithmic energy representation requires positive "
                     "energy boundaries."
                 )
             self.energy_grid = energy_grid
@@ -303,7 +302,7 @@ def __init__(
             if self.G == 1:
                 self.chi_p[:] = 1.0
             elif chi_p is None:
-                print_error("NeutronMultigroup with nu_p and G > 1 requires chi_p.")
+                print_error("NeutronMultigroupData with nu_p and G > 1 requires chi_p.")
             else:
                 if chi_p.ndim == 1:
                     chi_p = np.tile(chi_p[:, np.newaxis], (1, self.G))
@@ -315,7 +314,7 @@ def __init__(
             if self.G == 1:
                 self.chi_d[:] = 1.0
             elif chi_d is None:
-                print_error("NeutronMultigroup with nu_d and G > 1 requires chi_d.")
+                print_error("NeutronMultigroupData with nu_d and G > 1 requires chi_d.")
             else:
                 self.chi_d = np.swapaxes(chi_d, 0, 1).copy()
                 active_delayed_groups = np.any(nu_d > 0.0, axis=1)
@@ -325,8 +324,7 @@ def __repr__(self) -> str:
         text = super().__repr__()
         text += f"  - G: {self.G}\n"
         text += f"  - J: {self.J}\n"
-        if self.has_energy_grid:
-            text += f"  - Energy grid {print_1d_array(self.energy_grid)}\n"
+        text += f"  - Energy grid {print_1d_array(self.energy_grid)}\n"
         text += f"  - Sigma_c {print_1d_array(self.capture)}\n"
         text += f"  - Sigma_s {print_1d_array(self.scatter)}\n"
         text += f"  - Sigma_f {print_1d_array(self.fission)}\n"
@@ -348,7 +346,7 @@ def _as_array(name, value):
     try:
         return np.asarray(value, dtype=float64)
     except (TypeError, ValueError):
-        print_error(f"NeutronMultigroup {name} must be numeric array-like data.")
+        print_error(f"NeutronMultigroupData {name} must be numeric array-like data.")
 
 
 def _infer_group_count(capture, scatter, fission) -> int:
@@ -359,11 +357,11 @@ def _infer_group_count(capture, scatter, fission) -> int:
         return 0
     if defining.ndim == 0:
         print_error(
-            "NeutronMultigroup cross sections must be arrays with an energy-group axis."
+            "NeutronMultigroupData cross sections must be arrays with an energy-group axis."
         )
     if defining.shape[0] == 0:
         print_error(
-            "NeutronMultigroup cross sections must define at least one energy group."
+            "NeutronMultigroupData cross sections must define at least one energy group."
         )
     return defining.shape[0]
 
@@ -373,19 +371,21 @@ def _infer_delayed_group_count(nu_d, G: int) -> int:
     if nu_d is None:
         return 0
     if nu_d.ndim != 2:
-        print_error(f"NeutronMultigroup nu_d must have shape (J, G); got {nu_d.shape}.")
+        print_error(
+            f"NeutronMultigroupData nu_d must have shape (J, G); got {nu_d.shape}."
+        )
     if nu_d.shape[1] != G:
         print_error(
-            f"NeutronMultigroup nu_d must have shape (J, G) with G = {G}; got {nu_d.shape}."
+            f"NeutronMultigroupData nu_d must have shape (J, G) with G = {G}; got {nu_d.shape}."
         )
     return nu_d.shape[0]
 
 
 def _validate_shape(name, array, expected) -> None:
-    """Require an optional array to have its declared NeutronMultigroup shape."""
+    """Require an optional array to have its declared NeutronMultigroupData shape."""
     if array is not None and array.shape != expected:
         print_error(
-            f"NeutronMultigroup {name} must have shape {expected}; got {array.shape}."
+            f"NeutronMultigroupData {name} must have shape {expected}; got {array.shape}."
         )
 
 
@@ -395,7 +395,7 @@ def _validate_prompt_spectrum_shape(chi_p, G: int) -> None:
         return
     if chi_p.shape not in ((G,), (G, G)):
         print_error(
-            f"NeutronMultigroup chi_p must have shape ({G},) or ({G}, {G}); got {chi_p.shape}."
+            f"NeutronMultigroupData chi_p must have shape ({G},) or ({G}, {G}); got {chi_p.shape}."
         )
 
 
@@ -404,7 +404,9 @@ def _validate_nonnegative(name, array) -> None:
     if array is None:
         return
     if not np.all(np.isfinite(array)) or np.any(array < 0.0):
-        print_error(f"NeutronMultigroup {name} entries must be finite and nonnegative.")
+        print_error(
+            f"NeutronMultigroupData {name} entries must be finite and nonnegative."
+        )
 
 
 def _validate_positive(name, array) -> None:
@@ -412,7 +414,9 @@ def _validate_positive(name, array) -> None:
     if array is None:
         return
     if not np.all(np.isfinite(array)) or np.any(array <= 0.0):
-        print_error(f"NeutronMultigroup {name} entries must be finite and positive.")
+        print_error(
+            f"NeutronMultigroupData {name} entries must be finite and positive."
+        )
 
 
 def _validate_decay_rate(array) -> None:
@@ -420,7 +424,7 @@ def _validate_decay_rate(array) -> None:
     if array is None:
         return
     if np.any(np.isnan(array)) or np.any(array < 0.0):
-        print_error("NeutronMultigroup decay_rate entries must be nonnegative.")
+        print_error("NeutronMultigroupData decay_rate entries must be nonnegative.")
 
 
 def _resolve_energy_representation(policy) -> int:
@@ -429,7 +433,7 @@ def _resolve_energy_representation(policy) -> int:
         if policy not in _NEUTRON_MULTIGROUP_ENERGY_REPRESENTATIONS:
             expected = ", ".join(_NEUTRON_MULTIGROUP_ENERGY_REPRESENTATIONS)
             print_error(
-                f"Unknown NeutronMultigroup energy representation {policy!r}. "
+                f"Unknown NeutronMultigroupData energy representation {policy!r}. "
                 f"Expected one of: {expected}."
             )
         return _NEUTRON_MULTIGROUP_ENERGY_REPRESENTATIONS[policy]
@@ -441,7 +445,7 @@ def _resolve_energy_representation(policy) -> int:
     ):
         return int(policy)
 
-    print_error(f"Unknown NeutronMultigroup energy representation {policy!r}.")
+    print_error(f"Unknown NeutronMultigroupData energy representation {policy!r}.")
 
 
 def _normalize_rows(array, required, name) -> None:
@@ -450,7 +454,7 @@ def _normalize_rows(array, required, name) -> None:
         norm = np.sum(array[index])
         if required[index] and norm <= 0.0:
             print_error(
-                f"NeutronMultigroup {name} spectrum {index} must have positive mass."
+                f"NeutronMultigroupData {name} spectrum {index} must have positive mass."
             )
         if norm > 0.0:
             array[index] /= norm

From e61f1f4e544a50fc5396e6e468d36dbd52df0ab3 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 18:31:42 +0700
Subject: [PATCH 116/202] update transport

---
 mcdc/transport/particle_bank.py              |  2 +-
 mcdc/transport/physics/neutron/multigroup.py | 10 +++++-----
 mcdc/transport/physics/neutron/native.py     | 10 +++++-----
 mcdc/transport/simulation.py                 |  4 ++--
 mcdc/transport/technique.py                  |  6 +++---
 5 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/mcdc/transport/particle_bank.py b/mcdc/transport/particle_bank.py
index 9b32f9cd8..9736c2aa2 100644
--- a/mcdc/transport/particle_bank.py
+++ b/mcdc/transport/particle_bank.py
@@ -200,7 +200,7 @@ def manage_particle_banks(simulation):
         )
 
     # Population control
-    if simulation["population_control"]["active"]:
+    if simulation["technique"]["population_control"]["active"]:
         technique.population_control(simulation)
     else:
         # Swap census and source bank
diff --git a/mcdc/transport/physics/neutron/multigroup.py b/mcdc/transport/physics/neutron/multigroup.py
index d5b6c0a52..1719bede3 100644
--- a/mcdc/transport/physics/neutron/multigroup.py
+++ b/mcdc/transport/physics/neutron/multigroup.py
@@ -130,7 +130,7 @@ def collision(particle_container, collision_data_container, program, data):
     SigmaF = macro_xs(NEUTRON_REACTION_FISSION, particle_container, simulation, data)
 
     # Implicit capture
-    if simulation["implicit_capture"]["active"]:
+    if simulation["technique"]["implicit_capture"]["active"]:
         particle["w"] *= (SigmaT - SigmaC) / SigmaT
         SigmaT -= SigmaC
 
@@ -173,8 +173,8 @@ def scattering(particle_container, program, data):
     # Adjust production and product weights if weighted emission
     weight_production = 1.0
     weight_product = particle["w"]
-    if simulation["weighted_emission"]["active"]:
-        weight_target = simulation["weighted_emission"]["weight_target"]
+    if simulation["technique"]["weighted_emission"]["active"]:
+        weight_target = simulation["technique"]["weighted_emission"]["weight_target"]
         weight_production = particle["w"] / weight_target
         weight_product = weight_target
 
@@ -252,8 +252,8 @@ def fission(particle_container, program, data):
     # Adjust production and product weights if weighted emission
     weight_production = 1.0
     weight_product = particle["w"]
-    if simulation["weighted_emission"]["active"]:
-        weight_target = simulation["weighted_emission"]["weight_target"]
+    if simulation["technique"]["weighted_emission"]["active"]:
+        weight_target = simulation["technique"]["weighted_emission"]["weight_target"]
         weight_production = particle["w"] / weight_target
         weight_product = weight_target
 
diff --git a/mcdc/transport/physics/neutron/native.py b/mcdc/transport/physics/neutron/native.py
index 4aea35069..fa369bf28 100644
--- a/mcdc/transport/physics/neutron/native.py
+++ b/mcdc/transport/physics/neutron/native.py
@@ -254,7 +254,7 @@ def collision(particle_container, collision_data_container, program, data):
     SigmaT = macro_xs(NEUTRON_REACTION_TOTAL, particle_container, simulation, data)
 
     # Implicit capture
-    if simulation["implicit_capture"]["active"]:
+    if simulation["technique"]["implicit_capture"]["active"]:
         # Calculate capture fraction
         SigmaC = macro_xs(
             NEUTRON_REACTION_CAPTURE, particle_container, simulation, data
@@ -297,7 +297,7 @@ def collision(particle_container, collision_data_container, program, data):
         nuclide_density = mcdc_get.native_material.nuclide_densities(i, material, data)
         sigmaT = total_micro_xs(NEUTRON_REACTION_TOTAL, E, nuclide, data)
 
-        if simulation["implicit_capture"]["active"]:
+        if simulation["technique"]["implicit_capture"]["active"]:
             sigmaC = total_micro_xs(NEUTRON_REACTION_CAPTURE, E, nuclide, data)
             sigmaT -= sigmaC
 
@@ -346,7 +346,7 @@ def collision(particle_container, collision_data_container, program, data):
                 return
 
     # Capture
-    if not simulation["implicit_capture"]["active"]:
+    if not simulation["technique"]["implicit_capture"]["active"]:
         sigma_capture = total_micro_xs(NEUTRON_REACTION_CAPTURE, E, nuclide, data)
         total += sigma_capture
         if xi < total:
@@ -769,8 +769,8 @@ def sample_fission(
     # Adjust production and product weights if weighted emission
     weight_production = 1.0
     weight_product = particle["w"]
-    if simulation["weighted_emission"]["active"]:
-        weight_target = simulation["weighted_emission"]["weight_target"]
+    if simulation["technique"]["weighted_emission"]["active"]:
+        weight_target = simulation["technique"]["weighted_emission"]["weight_target"]
         weight_production = particle["w"] / weight_target
         weight_product = weight_target
 
diff --git a/mcdc/transport/simulation.py b/mcdc/transport/simulation.py
index 7ae7bc4b7..92783144a 100644
--- a/mcdc/transport/simulation.py
+++ b/mcdc/transport/simulation.py
@@ -331,11 +331,11 @@ def step_particle(particle_container, program, data):
         return
 
     # Weight windows
-    if simulation["weight_windows"]["active"]:
+    if simulation["technique"]["weight_windows"]["active"]:
         technique.weight_windows(particle_container, program, data)
 
     # Global weight roulette
-    if simulation["global_weight_roulette"]["active"]:
+    if simulation["technique"]["global_weight_roulette"]["active"]:
         technique.global_weight_roulette(particle_container, simulation)
 
 
diff --git a/mcdc/transport/technique.py b/mcdc/transport/technique.py
index 5de637998..30d18414d 100644
--- a/mcdc/transport/technique.py
+++ b/mcdc/transport/technique.py
@@ -60,8 +60,8 @@ def global_weight_roulette(particle_container, simulation):
     simulation : object
         Simulation state containing global weight roulette parameters.
     """
-    w_threshold = simulation["global_weight_roulette"]["weight_threshold"]
-    w_target = simulation["global_weight_roulette"]["weight_target"]
+    w_threshold = simulation["technique"]["global_weight_roulette"]["weight_threshold"]
+    w_target = simulation["technique"]["global_weight_roulette"]["weight_target"]
     weight_roulette(particle_container, w_threshold, w_target)
 
 
@@ -116,7 +116,7 @@ def query_weight_window(particle_container, simulation, data):
         Upper weight bound.
     """
     # grab objects
-    ww_obj = simulation["weight_windows"]
+    ww_obj = simulation["technique"]["weight_windows"]
     indices = get_ww_indices(particle_container, ww_obj, simulation, data)
     # grab the actual ww parameters
     lower = ww_get.lower_weights(*indices, ww_obj, data)

From 61589470c2332a11e88c7cb854e9c21074d83535 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 18:32:18 +0700
Subject: [PATCH 117/202] update examples

---
 examples/c5g7/k-eigenvalue/input.py | 2 +-
 examples/kobayashi-TD/input.py      | 2 +-
 examples/kobayashi/input.py         | 2 +-
 examples/sphere_in_cube/input.py    | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/examples/c5g7/k-eigenvalue/input.py b/examples/c5g7/k-eigenvalue/input.py
index 393a70161..a7c91386d 100644
--- a/examples/c5g7/k-eigenvalue/input.py
+++ b/examples/c5g7/k-eigenvalue/input.py
@@ -304,7 +304,7 @@ def set_mat(mat):
 simulation.settings.set_eigenmode(N_inactive=5, N_active=10, gyration_radius="all")
 
 # Techniques
-simulation.population_control()
+simulation.technique.population_control()
 
 # Run
 simulation.run()
diff --git a/examples/kobayashi-TD/input.py b/examples/kobayashi-TD/input.py
index 61fb41ce7..034b2b436 100644
--- a/examples/kobayashi-TD/input.py
+++ b/examples/kobayashi-TD/input.py
@@ -76,7 +76,7 @@
 simulation.settings.N_batch = 2
 
 # Techniques
-simulation.implicit_capture()
+simulation.technique.implicit_capture()
 
 # Run
 simulation.run()
diff --git a/examples/kobayashi/input.py b/examples/kobayashi/input.py
index 9b5762927..9ebb08afe 100644
--- a/examples/kobayashi/input.py
+++ b/examples/kobayashi/input.py
@@ -71,7 +71,7 @@
 simulation.settings.N_batch = 2
 
 # Techniques
-simulation.implicit_capture()
+simulation.technique.implicit_capture()
 
 # Run
 simulation.run()
diff --git a/examples/sphere_in_cube/input.py b/examples/sphere_in_cube/input.py
index 55aee8c28..8c0be2619 100644
--- a/examples/sphere_in_cube/input.py
+++ b/examples/sphere_in_cube/input.py
@@ -57,7 +57,7 @@
 simulation.settings.N_batch = 2
 
 # Techniques
-simulation.implicit_capture()
+simulation.technique.implicit_capture()
 
 # Run
 simulation.run()

From ef1dba14c1d06eb973bb49b319428435d70e979b Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 18:32:56 +0700
Subject: [PATCH 118/202] update regression tests

---
 test/regression/azurv1_census/input.py            | 2 +-
 test/regression/azurv1_census_tally/input.py      | 2 +-
 test/regression/basic_weight_windows/input.py     | 2 +-
 test/regression/c5g7_2d_k_eigenvalue/input.py     | 2 +-
 test/regression/cooper2/input.py                  | 4 ++--
 test/regression/inf_shem361_k_eigenvalue/input.py | 2 +-
 test/regression/inf_shem361_td_census/input.py    | 2 +-
 test/regression/kobayashi3-TD/input.py            | 2 +-
 test/regression/slab_isobeam_td_census/input.py   | 2 +-
 test/regression/sphere_in_cube/input.py           | 2 +-
 10 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/test/regression/azurv1_census/input.py b/test/regression/azurv1_census/input.py
index a0d0ddab7..553230e3a 100644
--- a/test/regression/azurv1_census/input.py
+++ b/test/regression/azurv1_census/input.py
@@ -57,7 +57,7 @@
 simulation.settings.set_time_census(np.linspace(0.0, 20.0, 21)[1:-1])
 
 # Techniques
-simulation.population_control()
+simulation.technique.population_control()
 
 # Run
 simulation.run()
diff --git a/test/regression/azurv1_census_tally/input.py b/test/regression/azurv1_census_tally/input.py
index a739a93e6..413e78a3a 100644
--- a/test/regression/azurv1_census_tally/input.py
+++ b/test/regression/azurv1_census_tally/input.py
@@ -57,7 +57,7 @@
 simulation.settings.set_time_census(np.linspace(0.0, 20.0, 21)[1:], tally_frequency=5)
 
 # Techniques
-simulation.population_control()
+simulation.technique.population_control()
 
 # Run
 simulation.run()
diff --git a/test/regression/basic_weight_windows/input.py b/test/regression/basic_weight_windows/input.py
index a475a125e..7201320bd 100644
--- a/test/regression/basic_weight_windows/input.py
+++ b/test/regression/basic_weight_windows/input.py
@@ -64,6 +64,6 @@
 ww_array[..., 0] = 0.55  # Forces roulette on split particles from 1.0
 ww_array[..., 1] = 0.7  # arbitrary in the middle
 ww_array[..., 2] = 0.9  # forces splitting on all particles born with w=1.0
-simulation.weight_windows(ww_array, mesh=mesh)
+simulation.technique.weight_windows(ww_array, mesh=mesh)
 
 simulation.run()
diff --git a/test/regression/c5g7_2d_k_eigenvalue/input.py b/test/regression/c5g7_2d_k_eigenvalue/input.py
index dea106e72..d56395f36 100644
--- a/test/regression/c5g7_2d_k_eigenvalue/input.py
+++ b/test/regression/c5g7_2d_k_eigenvalue/input.py
@@ -205,7 +205,7 @@ def set_mat(mat):
 )
 
 # Techniques
-simulation.population_control()
+simulation.technique.population_control()
 
 # Run
 simulation.run()
diff --git a/test/regression/cooper2/input.py b/test/regression/cooper2/input.py
index 6da73d24b..bb932fede 100644
--- a/test/regression/cooper2/input.py
+++ b/test/regression/cooper2/input.py
@@ -64,8 +64,8 @@
 simulation.settings.N_batch = 2
 
 # Techniques
-simulation.implicit_capture()
-simulation.global_weight_roulette(0.1, 1.0)
+simulation.technique.implicit_capture()
+simulation.technique.global_weight_roulette(0.1, 1.0)
 
 # Run
 simulation.run()
diff --git a/test/regression/inf_shem361_k_eigenvalue/input.py b/test/regression/inf_shem361_k_eigenvalue/input.py
index 7cb168d81..b49805149 100644
--- a/test/regression/inf_shem361_k_eigenvalue/input.py
+++ b/test/regression/inf_shem361_k_eigenvalue/input.py
@@ -64,7 +64,7 @@
 simulation.settings.set_eigenmode(N_inactive=1, N_active=2)
 
 # Techniques
-simulation.population_control()
+simulation.technique.population_control()
 
 # Run
 simulation.run()
diff --git a/test/regression/inf_shem361_td_census/input.py b/test/regression/inf_shem361_td_census/input.py
index 11e9d487b..04be93aa7 100644
--- a/test/regression/inf_shem361_td_census/input.py
+++ b/test/regression/inf_shem361_td_census/input.py
@@ -73,7 +73,7 @@
 simulation.settings.source_bank_buffer_ratio = 5.0
 
 # Techniques
-simulation.population_control()
+simulation.technique.population_control()
 
 # Run
 simulation.run()
diff --git a/test/regression/kobayashi3-TD/input.py b/test/regression/kobayashi3-TD/input.py
index 3a92fa9ce..6766f563a 100644
--- a/test/regression/kobayashi3-TD/input.py
+++ b/test/regression/kobayashi3-TD/input.py
@@ -81,7 +81,7 @@
 simulation.settings.N_particle = 25
 
 # Techniques
-simulation.implicit_capture()
+simulation.technique.implicit_capture()
 
 # Run
 simulation.run()
diff --git a/test/regression/slab_isobeam_td_census/input.py b/test/regression/slab_isobeam_td_census/input.py
index 504e0dff6..382d1f083 100644
--- a/test/regression/slab_isobeam_td_census/input.py
+++ b/test/regression/slab_isobeam_td_census/input.py
@@ -54,7 +54,7 @@
 simulation.settings.set_time_census(np.linspace(0.0, 5.0, 6)[1:])
 
 # Techniques
-simulation.population_control()
+simulation.technique.population_control()
 
 # Run
 simulation.run()
diff --git a/test/regression/sphere_in_cube/input.py b/test/regression/sphere_in_cube/input.py
index 1c30814cc..a8897ae8d 100644
--- a/test/regression/sphere_in_cube/input.py
+++ b/test/regression/sphere_in_cube/input.py
@@ -64,7 +64,7 @@
 simulation.settings.N_batch = 2
 
 # Techniques
-simulation.implicit_capture()
+simulation.technique.implicit_capture()
 
 # Run
 simulation.run()

From 3ea8a29c96295ce4d4bef754075cfc355ce7c2a1 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 18:34:42 +0700
Subject: [PATCH 119/202] update unit tests

---
 test/unit/tally/conftest.py                |   2 +-
 test/unit/tally/test_tally_factory.py      |   2 +-
 test/unit/technique/test_weight_windows.py |   4 +-
 test/unit/test_material.py                 | 133 +++++++++
 test/unit/test_mgxs.py                     | 305 --------------------
 test/unit/test_numba_layers_generator.py   |  71 +++++
 test/unit/test_object_compilation.py       |  53 +++-
 test/unit/test_transport_model_data.py     | 321 +++++++++++++++++++++
 test/unit/test_visualize.py                |   2 +-
 9 files changed, 573 insertions(+), 320 deletions(-)
 create mode 100644 test/unit/test_material.py
 delete mode 100644 test/unit/test_mgxs.py
 create mode 100644 test/unit/test_transport_model_data.py

diff --git a/test/unit/tally/conftest.py b/test/unit/tally/conftest.py
index 3d0e2e67b..40267b03f 100644
--- a/test/unit/tally/conftest.py
+++ b/test/unit/tally/conftest.py
@@ -9,7 +9,7 @@
 @pytest.fixture
 def material_mg():
     # Minimal multigroup material so particle speed is defined.
-    return mcdc.MaterialMG(capture=np.array([1.0]))
+    return mcdc.Material.multigroup(capture=np.array([1.0]))
 
 
 @pytest.fixture
diff --git a/test/unit/tally/test_tally_factory.py b/test/unit/tally/test_tally_factory.py
index 6a01a75b6..c03f7e7ba 100644
--- a/test/unit/tally/test_tally_factory.py
+++ b/test/unit/tally/test_tally_factory.py
@@ -97,7 +97,7 @@ def test_tally_factory_allows_combined_supported_filters(slab_plane_x):
 
 
 def test_all_groups_filter_resizes_compiled_tally_bins(prepare_simulation):
-    material = mcdc.MaterialMG(capture=np.ones(3))
+    material = mcdc.Material.multigroup(capture=np.ones(3))
     cell = mcdc.Cell(fill=material)
     tally = mcdc.Tally(scores=["flux"], energy="all_groups")
 
diff --git a/test/unit/technique/test_weight_windows.py b/test/unit/technique/test_weight_windows.py
index b12a598cd..a9fdaa5d3 100644
--- a/test/unit/technique/test_weight_windows.py
+++ b/test/unit/technique/test_weight_windows.py
@@ -53,7 +53,7 @@ def make_ww_model_params(
         ww_array[..., 2] = upper
 
     def configure(simulation):
-        simulation.weight_windows(ww_array, mesh=mesh)
+        simulation.technique.weight_windows(ww_array, mesh=mesh)
 
     mcdc_container, data = prepare_simulation(configure=configure)
     return mcdc_container[0], data
@@ -77,7 +77,7 @@ def make_ww_model_distinct(prepare_simulation):
                     ww_array[e, i, j, k, 2] = 20000 + val
 
     def configure(simulation):
-        simulation.weight_windows(ww_array, mesh=mesh, energy=energy)
+        simulation.technique.weight_windows(ww_array, mesh=mesh, energy=energy)
 
     mcdc_container, data = prepare_simulation(configure=configure)
     return mcdc_container[0], data
diff --git a/test/unit/test_material.py b/test/unit/test_material.py
new file mode 100644
index 000000000..0915117b4
--- /dev/null
+++ b/test/unit/test_material.py
@@ -0,0 +1,133 @@
+import pytest
+
+import mcdc
+from mcdc.constant import FILL_MATERIAL
+from mcdc.object_.base import MCDCObject, MCDCPolymorphic
+from mcdc.object_.material import Material
+from mcdc.object_.nuclide import Nuclide
+
+
+def test_material_is_the_only_public_non_polymorphic_material_type():
+    assert mcdc.Material is Material
+    assert issubclass(Material, MCDCObject)
+    assert not issubclass(Material, MCDCPolymorphic)
+    assert not hasattr(mcdc, "MaterialMG")
+
+
+def test_multigroup_factory_returns_a_material_and_forwards_transport_data():
+    material = Material.multigroup(
+        name="Delayed fuel",
+        fission=[0.2, 0.3],
+        nu_d=[[0.1, 0.2], [0.3, 0.4]],
+        chi_d=[[1.0, 3.0], [3.0, 1.0]],
+        decay_rate=[0.01, 0.02],
+        energy_grid=[1.0e-5, 1.0, 20.0e6],
+    )
+
+    assert type(material) is Material
+    assert material.name == "Delayed fuel"
+    assert material.has_neutron_multigroup
+    assert material.neutron_multigroup.G == 2
+    assert material.neutron_multigroup.J == 2
+
+
+def test_material_accepts_native_multigroup_and_hybrid_data():
+    native = Material(nuclide_composition={"H1": 0.1})
+    neutron_multigroup = mcdc.NeutronMultigroupData(capture=[0.2])
+    multigroup = Material(neutron_multigroup=neutron_multigroup)
+    hybrid = Material(
+        element_composition={"H": 0.1},
+        neutron_multigroup=mcdc.NeutronMultigroupData(
+            scatter=[[0.3]],
+            energy_grid=[1.0e-5, 20.0e6],
+        ),
+    )
+
+    assert list(nuclide.name for nuclide in native.nuclides) == ["H1"]
+    assert not native.has_neutron_multigroup
+    assert native.neutron_multigroup.G == 0
+    assert multigroup.has_neutron_multigroup
+    assert multigroup.neutron_multigroup is neutron_multigroup
+    assert hybrid.has_neutron_multigroup
+    assert hybrid.elements[0].name == "H"
+    assert hybrid.neutron_multigroup.G == 1
+
+
+@pytest.mark.parametrize(
+    "kwargs, expected_message",
+    [
+        ({}, "Material requires"),
+        (
+            {
+                "nuclide_composition": {"H1": 0.1},
+                "element_composition": {"H": 0.1},
+            },
+            "Cannot specify both",
+        ),
+        (
+            {"neutron_multigroup": object()},
+            "neutron_multigroup must be a NeutronMultigroupData object",
+        ),
+    ],
+)
+def test_material_rejects_invalid_representations(kwargs, expected_message, capsys):
+    with pytest.raises(SystemExit):
+        Material(**kwargs)
+
+    assert expected_message in capsys.readouterr().out
+
+
+def test_absent_mg_points_to_the_reserved_simulation_object(monkeypatch):
+    # Isolate object registration from native data-library loading
+    def compile_nuclide(nuclide, simulation):
+        nuclide.fissionable = False
+        return MCDCObject._compile_into_simulation(nuclide, simulation)
+
+    monkeypatch.setattr(Nuclide, "_compile_into_simulation", compile_nuclide)
+
+    simulation = mcdc.Simulation()
+    simulation.compile()
+    material = Material(nuclide_composition={"H1": 0.1})
+
+    material._compile_into_simulation(simulation)
+
+    assert material.neutron_multigroup is simulation.neutron_multigroup_data[0]
+    assert material.neutron_multigroup.ID == 0
+    assert not material.has_neutron_multigroup
+    assert simulation.materials == [material]
+    assert len(simulation.neutron_multigroup_data) == 1
+
+
+def test_shared_mg_is_registered_once_for_multiple_materials():
+    neutron_multigroup = mcdc.NeutronMultigroupData(capture=[0.1])
+    material_a = Material(neutron_multigroup=neutron_multigroup)
+    material_b = Material(neutron_multigroup=neutron_multigroup)
+    simulation = mcdc.Simulation()
+    simulation.compile()
+
+    material_a._compile_into_simulation(simulation)
+    material_b._compile_into_simulation(simulation)
+
+    assert simulation.materials == [material_a, material_b]
+    assert len(simulation.neutron_multigroup_data) == 2
+    assert simulation.neutron_multigroup_data[1] is neutron_multigroup
+    assert neutron_multigroup.ID == 1
+
+
+def test_material_mg_reference_is_packed(prepare_simulation):
+    neutron_multigroup = mcdc.NeutronMultigroupData(capture=[0.1, 0.2])
+    material = Material(neutron_multigroup=neutron_multigroup)
+    cell = mcdc.Cell(fill=material)
+
+    simulation_container, _ = prepare_simulation(cells=[cell])
+    simulation = simulation_container[0]
+    packed = simulation["materials"][0]
+    packed_cell = simulation["cells"][0]
+
+    assert simulation["N_material"] == 1
+    assert simulation["N_neutron_multigroup_data"] == 2
+    assert packed["ID"] == 0
+    assert packed["has_neutron_multigroup"]
+    assert packed["neutron_multigroup_ID"] == 1
+    assert packed_cell["fill_type"] == FILL_MATERIAL
+    assert packed_cell["fill_ID"] == 0
diff --git a/test/unit/test_mgxs.py b/test/unit/test_mgxs.py
deleted file mode 100644
index 58044ab76..000000000
--- a/test/unit/test_mgxs.py
+++ /dev/null
@@ -1,305 +0,0 @@
-import numpy as np
-import pytest
-
-import mcdc
-from mcdc.constant import (
-    MULTIGROUP_NEUTRON_ENERGY_MIDPOINT,
-    MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG,
-    MULTIGROUP_NEUTRON_ENERGY_UNIFORM,
-    MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
-)
-from mcdc.mcdc_get import mgxs as get_mgxs
-from mcdc.object_.base import MCDCObject, MCDCPolymorphic
-from mcdc.object_.mgxs import MGXS
-
-
-def test_mgxs_is_public():
-    assert mcdc.MGXS is MGXS
-    assert issubclass(MGXS, MCDCObject)
-    assert not issubclass(MGXS, MCDCPolymorphic)
-
-
-def test_zero_group_placeholder():
-    mgxs = MGXS()
-
-    assert mgxs.G == 0
-    assert mgxs.J == 0
-    assert not mgxs.fissionable
-    assert not mgxs.has_energy_grid
-    assert mgxs.energy_representation == MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG
-
-    np.testing.assert_array_equal(mgxs.energy_grid, [0.0])
-    np.testing.assert_array_equal(mgxs.speed, [])
-    np.testing.assert_array_equal(mgxs.decay_rate, [])
-    np.testing.assert_array_equal(mgxs.capture, [])
-    np.testing.assert_array_equal(mgxs.scatter, [])
-    np.testing.assert_array_equal(mgxs.fission, [])
-    np.testing.assert_array_equal(mgxs.total, [])
-    np.testing.assert_array_equal(mgxs.nu_s, [])
-    np.testing.assert_array_equal(mgxs.nu_p, [])
-    np.testing.assert_array_equal(mgxs.nu_d, np.empty((0, 0)))
-    np.testing.assert_array_equal(mgxs.nu_d_total, [])
-    np.testing.assert_array_equal(mgxs.nu_f, [])
-    np.testing.assert_array_equal(mgxs.chi_s, np.empty((0, 0)))
-    np.testing.assert_array_equal(mgxs.chi_p, np.empty((0, 0)))
-    np.testing.assert_array_equal(mgxs.chi_d, np.empty((0, 0)))
-
-
-def test_capture_only_defaults():
-    mgxs = MGXS(capture=[0.1, 0.2])
-
-    assert mgxs.G == 2
-    assert mgxs.J == 0
-    assert not mgxs.fissionable
-    assert not mgxs.has_energy_grid
-
-    np.testing.assert_array_equal(mgxs.energy_grid, [0.0, 0.0, 0.0])
-    np.testing.assert_array_equal(mgxs.speed, [1.0, 1.0])
-    np.testing.assert_array_equal(mgxs.capture, [0.1, 0.2])
-    np.testing.assert_array_equal(mgxs.scatter, [0.0, 0.0])
-    np.testing.assert_array_equal(mgxs.fission, [0.0, 0.0])
-    np.testing.assert_array_equal(mgxs.total, [0.1, 0.2])
-    np.testing.assert_array_equal(mgxs.nu_s, [1.0, 1.0])
-    np.testing.assert_array_equal(mgxs.nu_f, [0.0, 0.0])
-    assert mgxs.capture.dtype == np.float64
-
-
-def test_scatter_matrix_is_reoriented_and_normalized():
-    mgxs = MGXS(
-        scatter=[
-            [1.0, 2.0],
-            [3.0, 0.0],
-        ],
-        nu_s=[1.1, 1.2],
-    )
-
-    np.testing.assert_array_equal(mgxs.scatter, [4.0, 2.0])
-    np.testing.assert_allclose(
-        mgxs.chi_s,
-        [
-            [0.25, 0.75],
-            [1.0, 0.0],
-        ],
-    )
-    np.testing.assert_array_equal(mgxs.total, [4.0, 2.0])
-    np.testing.assert_array_equal(mgxs.nu_s, [1.1, 1.2])
-
-
-def test_prompt_fission_spectrum_is_shared_and_normalized():
-    mgxs = MGXS(
-        fission=[0.2, 0.3],
-        nu_p=[2.4, 2.5],
-        chi_p=[1.0, 3.0],
-    )
-
-    assert mgxs.fissionable
-    np.testing.assert_array_equal(mgxs.nu_f, [2.4, 2.5])
-    np.testing.assert_allclose(
-        mgxs.chi_p,
-        [
-            [0.25, 0.75],
-            [0.25, 0.75],
-        ],
-    )
-
-
-def test_delayed_fission_data_is_reoriented_and_normalized():
-    mgxs = MGXS(
-        fission=[0.2, 0.3],
-        nu_d=[
-            [0.1, 0.2],
-            [0.3, 0.4],
-        ],
-        chi_d=[
-            [1.0, 3.0],
-            [3.0, 1.0],
-        ],
-        decay_rate=[0.01, 0.02],
-    )
-
-    assert mgxs.J == 2
-    np.testing.assert_array_equal(
-        mgxs.nu_d,
-        [
-            [0.1, 0.3],
-            [0.2, 0.4],
-        ],
-    )
-    np.testing.assert_allclose(mgxs.nu_d_total, [0.4, 0.6])
-    np.testing.assert_allclose(mgxs.nu_f, [0.4, 0.6])
-    np.testing.assert_allclose(
-        mgxs.chi_d,
-        [
-            [0.25, 0.75],
-            [0.75, 0.25],
-        ],
-    )
-    np.testing.assert_array_equal(mgxs.decay_rate, [0.01, 0.02])
-
-
-def test_one_group_fission_spectra_default_to_one():
-    mgxs = MGXS(
-        fission=[0.2],
-        nu_p=[2.4],
-        nu_d=[[0.1], [0.2]],
-    )
-
-    np.testing.assert_array_equal(mgxs.chi_p, [[1.0]])
-    np.testing.assert_array_equal(mgxs.chi_d, [[1.0], [1.0]])
-    np.testing.assert_array_equal(mgxs.nu_f, [2.7])
-    np.testing.assert_array_equal(mgxs.decay_rate, [np.inf, np.inf])
-
-
-def test_standalone_mgxs_registration_and_packing(prepare_simulation):
-    mgxs = MGXS(
-        capture=[0.1, 0.2],
-        scatter=[[1.0, 2.0], [3.0, 0.0]],
-        energy_grid=[1.0e-5, 1.0, 20.0e6],
-    )
-
-    simulation_container, data = prepare_simulation(objects=[mgxs])
-    simulation = simulation_container[0]
-    reserved = simulation["mgxs"][0]
-    packed = simulation["mgxs"][1]
-
-    assert simulation["N_mgxs"] == 2
-    assert reserved["ID"] == 0
-    assert reserved["G"] == 0
-    assert mgxs.ID == 1
-    assert packed["ID"] == 1
-    assert packed["G"] == 2
-    assert packed["has_energy_grid"]
-
-    np.testing.assert_array_equal(get_mgxs.energy_grid_all(reserved, data), [0.0])
-    np.testing.assert_array_equal(
-        get_mgxs.energy_grid_all(packed, data),
-        [1.0e-5, 1.0, 20.0e6],
-    )
-    np.testing.assert_array_equal(get_mgxs.capture_all(packed, data), [0.1, 0.2])
-    np.testing.assert_array_equal(get_mgxs.scatter_all(packed, data), [4.0, 2.0])
-    np.testing.assert_allclose(
-        get_mgxs.chi_s_vector(0, packed, data),
-        [0.25, 0.75],
-    )
-
-
-@pytest.mark.parametrize(
-    "policy, expected",
-    [
-        ("midpoint", MULTIGROUP_NEUTRON_ENERGY_MIDPOINT),
-        ("log_midpoint", MULTIGROUP_NEUTRON_ENERGY_MIDPOINT_LOG),
-        ("uniform", MULTIGROUP_NEUTRON_ENERGY_UNIFORM),
-        ("log_uniform", MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG),
-        (MULTIGROUP_NEUTRON_ENERGY_MIDPOINT, MULTIGROUP_NEUTRON_ENERGY_MIDPOINT),
-        (
-            np.int64(MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG),
-            MULTIGROUP_NEUTRON_ENERGY_UNIFORM_LOG,
-        ),
-    ],
-)
-def test_energy_grid_and_representation(policy, expected):
-    mgxs = MGXS(
-        capture=[0.1, 0.2],
-        energy_grid=[1.0e-5, 1.0, 20.0e6],
-        energy_representation=policy,
-    )
-
-    assert mgxs.has_energy_grid
-    assert mgxs.energy_representation == expected
-    np.testing.assert_array_equal(mgxs.energy_grid, [1.0e-5, 1.0, 20.0e6])
-
-
-@pytest.mark.parametrize(
-    "kwargs, expected_message",
-    [
-        (
-            {"capture": [0.1, 0.2], "energy_grid": [1.0, 2.0]},
-            "energy_grid must have shape (3,)",
-        ),
-        (
-            {"capture": [0.1, 0.2], "energy_grid": [1.0, 2.0, 2.0]},
-            "energy grid must be strictly increasing",
-        ),
-        (
-            {"capture": [0.1], "energy_grid": [0.0, 1.0]},
-            "logarithmic energy representation requires positive",
-        ),
-        (
-            {"capture": [0.1], "energy_representation": "average"},
-            "Unknown MGXS energy representation",
-        ),
-        (
-            {"fission": [0.1]},
-            "Fission MGXS requires nu_p or nu_d",
-        ),
-        (
-            {"nu_p": [2.4]},
-            "nu_p must have shape (0,)",
-        ),
-        (
-            {"fission": [0.1, 0.2], "nu_p": [2.4, 2.5]},
-            "MGXS with nu_p and G > 1 requires chi_p",
-        ),
-        (
-            {"fission": [0.1, 0.2], "nu_d": [[0.1, 0.2]]},
-            "MGXS with nu_d and G > 1 requires chi_d",
-        ),
-        (
-            {"capture": [-0.1]},
-            "capture entries must be finite and nonnegative",
-        ),
-        (
-            {"capture": [0.1], "speed": [0.0]},
-            "speed entries must be finite and positive",
-        ),
-        (
-            {
-                "fission": [0.1, 0.2],
-                "nu_p": [2.4, 2.5],
-                "chi_p": [0.0, 0.0],
-            },
-            "chi_p spectrum 0 must have positive mass",
-        ),
-    ],
-)
-def test_invalid_inputs_are_rejected(kwargs, expected_message, capsys):
-    with pytest.raises(SystemExit):
-        MGXS(**kwargs)
-
-    assert expected_message in capsys.readouterr().out
-
-
-@pytest.mark.parametrize(
-    "kwargs, expected_message",
-    [
-        (
-            {"capture": [0.1, 0.2], "fission": [0.3], "nu_p": [2.4, 2.5]},
-            "fission must have shape (2,)",
-        ),
-        (
-            {"scatter": [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]]},
-            "scatter must have shape (2, 2)",
-        ),
-        (
-            {"capture": [0.1, 0.2], "speed": [1.0]},
-            "speed must have shape (2,)",
-        ),
-        (
-            {
-                "fission": [0.1, 0.2],
-                "nu_p": [2.4],
-                "chi_p": [0.5, 0.5],
-            },
-            "nu_p must have shape (2,)",
-        ),
-        (
-            {"fission": [0.1, 0.2], "nu_d": [[0.1]]},
-            "nu_d must have shape (J, G) with G = 2",
-        ),
-    ],
-)
-def test_inconsistent_shapes_are_rejected(kwargs, expected_message, capsys):
-    with pytest.raises(SystemExit):
-        MGXS(**kwargs)
-
-    assert expected_message in capsys.readouterr().out
diff --git a/test/unit/test_numba_layers_generator.py b/test/unit/test_numba_layers_generator.py
index 43f93884f..21531dced 100644
--- a/test/unit/test_numba_layers_generator.py
+++ b/test/unit/test_numba_layers_generator.py
@@ -12,13 +12,44 @@
     _accessor_2d_element,
     _accessor_3d_element,
     _accessor_4d_element,
+    set_object,
     set_structure,
+    validate_unique_class_labels,
     validate_accessor_targets,
 )
 from mcdc.mcdc_get import cell as get_cell
+from mcdc.object_.base import MCDCBase
 from mcdc.object_.surface import Surface
 
 
+class EmbeddedLeaf(MCDCBase):
+    label = "child"
+
+    active: bool
+    values: NDArray[np.float64]
+
+    def __init__(self):
+        self.active = True
+        self.values = np.array([2.0, 3.0])
+
+
+class EmbeddedOwner(MCDCBase):
+    label = "embedded_owner_test"
+
+    child: EmbeddedLeaf
+
+    def __init__(self):
+        self.child = EmbeddedLeaf()
+
+
+class DuplicateLabelA(MCDCBase):
+    label = "duplicate_label"
+
+
+class DuplicateLabelB(MCDCBase):
+    label = "duplicate_label"
+
+
 def test_set_structure_tracks_logical_accessor_types():
     annotations = {
         "example": {
@@ -41,6 +72,46 @@ def test_set_structure_tracks_logical_accessor_types():
     ]
 
 
+def test_embedded_mcdc_base_structures_and_records_are_recursive():
+    annotations = {
+        EmbeddedOwner.label: {"child": EmbeddedLeaf},
+        EmbeddedLeaf.label: {
+            "active": bool,
+            "values": NDArray[np.float64],
+        },
+    }
+    structures = {label: [] for label in annotations}
+    accessor_targets = {label: [] for label in annotations}
+    records = {label: {} for label in annotations}
+    order = []
+
+    set_structure(
+        EmbeddedOwner.label,
+        structures,
+        accessor_targets,
+        annotations,
+        order=order,
+    )
+
+    owner = EmbeddedOwner()
+    data = {"size": 0}
+    set_object(owner, annotations, structures, records, data)
+    data = {"size": 0, "array": np.zeros(data["size"])}
+    set_object(owner, annotations, structures, records, data, set_data=True)
+
+    assert order == [EmbeddedLeaf.label, EmbeddedOwner.label]
+    assert structures[EmbeddedOwner.label][0][0] == "child"
+    assert records[EmbeddedOwner.label]["child"]["active"]
+    np.testing.assert_array_equal(data["array"], owner.child.values)
+
+
+def test_runtime_class_labels_must_be_unique(capsys):
+    with pytest.raises(SystemExit):
+        validate_unique_class_labels([DuplicateLabelA, DuplicateLabelB])
+
+    assert "Duplicate MC/DC class label 'duplicate_label'" in capsys.readouterr().out
+
+
 def test_scalar_integer_getters_cast_values_from_data():
     assert "return int64(data[offset + index])" in _accessor_1d_element(
         "example", "values", cast_to_int=True
diff --git a/test/unit/test_object_compilation.py b/test/unit/test_object_compilation.py
index d5ff3b543..b6ed8de5c 100644
--- a/test/unit/test_object_compilation.py
+++ b/test/unit/test_object_compilation.py
@@ -1,10 +1,12 @@
 import numpy as np
+import pytest
 
 import mcdc
 
 from mcdc.object_.base import MCDCBase, MCDCObject
 from mcdc.object_.data import DataPolynomial
-from mcdc.object_.mgxs import MGXS
+from mcdc.object_.transport_model_data import NeutronMultigroupData
+from mcdc.object_.technique import Technique
 from mcdc.object_.nuclide import Nuclide
 from mcdc.object_.universe import Universe
 
@@ -30,16 +32,47 @@ def __init__(self):
         self.member = None
 
 
-def test_simulation_reserves_zero_group_mgxs_as_id_zero():
+def test_simulation_reserves_zero_group_mg_as_id_zero():
     simulation = mcdc.Simulation()
 
+    assert isinstance(simulation.technique, Technique)
+
     simulation.compile()
 
-    assert len(simulation.mgxs) == 1
-    assert isinstance(simulation.mgxs[0], MGXS)
-    assert simulation.mgxs[0].ID == 0
-    assert simulation.mgxs[0].G == 0
-    assert simulation.mgxs[0].compile_ID == simulation.compile_ID
+    assert len(simulation.neutron_multigroup_data) == 1
+    assert isinstance(simulation.neutron_multigroup_data[0], NeutronMultigroupData)
+    assert simulation.neutron_multigroup_data[0].ID == 0
+    assert simulation.neutron_multigroup_data[0].G == 0
+    assert simulation.neutron_multigroup_data[0].compile_ID == simulation.compile_ID
+
+
+def test_simulation_requires_a_shared_neutron_multigroup_grid(capsys):
+    material_a = mcdc.Material.multigroup(capture=[0.1], energy_grid=[1.0, 2.0])
+    material_b = mcdc.Material.multigroup(capture=[0.2], energy_grid=[2.0, 3.0])
+    simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell(fill=material_a), mcdc.Cell(fill=material_b)])
+
+    with pytest.raises(SystemExit):
+        simulation.compile()
+
+    assert "energy grids must be identical" in capsys.readouterr().out
+
+
+def test_neutron_multigroup_technique_allows_and_packs_multigrid(
+    prepare_simulation,
+):
+    material_a = mcdc.Material.multigroup(capture=[0.1], energy_grid=[1.0, 2.0])
+    material_b = mcdc.Material.multigroup(capture=[0.2], energy_grid=[2.0, 3.0])
+
+    simulation_container, _ = prepare_simulation(
+        cells=[mcdc.Cell(fill=material_a), mcdc.Cell(fill=material_b)],
+        configure=lambda simulation: simulation.technique.neutron_multigroup(
+            multigrid=True
+        ),
+    )
+
+    simulation = simulation_container[0]
+    assert simulation["technique"]["neutron_multigroup"]["multigrid"]
 
 
 def test_mcdc_object_compiles_object_members_and_lists():
@@ -62,12 +95,13 @@ def test_simulation_compiles_objects_owned_by_embedded_configuration():
     mesh = mcdc.MeshUniform()
     weight_windows = np.ones((1, 1, 1, 1, 3))
     simulation = mcdc.Simulation()
-    simulation.weight_windows(weight_windows, mesh=mesh)
+    simulation.technique.weight_windows(weight_windows, mesh=mesh)
 
     simulation.compile()
 
     assert simulation.meshes == [mesh]
-    assert simulation.weight_windows.compile_ID == simulation.compile_ID
+    assert simulation.technique.compile_ID == simulation.compile_ID
+    assert simulation.technique.weight_windows.compile_ID == simulation.compile_ID
 
 
 def test_embedded_compile_id_prevents_cycles_and_supports_recompilation():
@@ -127,7 +161,6 @@ def test_simulation_compilation_finalizes_model_wide_state():
     simulation.compile()
 
     assert np.allclose([source_a.probability, source_b.probability], [0.25, 0.75])
-    assert simulation.settings.neutron_multigroup_mode
     assert simulation.k_eff == 1.25
     assert not simulation.cycle_active
     assert simulation.k_cycle.shape == (4,)
diff --git a/test/unit/test_transport_model_data.py b/test/unit/test_transport_model_data.py
new file mode 100644
index 000000000..6b8ea1193
--- /dev/null
+++ b/test/unit/test_transport_model_data.py
@@ -0,0 +1,321 @@
+import numpy as np
+import pytest
+
+import mcdc
+from mcdc.constant import (
+    NEUTRON_MULTIGROUP_ENERGY_MIDPOINT,
+    NEUTRON_MULTIGROUP_ENERGY_MIDPOINT_LOG,
+    NEUTRON_MULTIGROUP_ENERGY_UNIFORM,
+    NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG,
+)
+from mcdc.mcdc_get import neutron_multigroup_data as get_neutron_multigroup_data
+from mcdc.object_.base import MCDCObject, MCDCPolymorphic
+from mcdc.object_.transport_model_data import NeutronMultigroupData
+
+
+def test_neutron_multigroup_is_public():
+    assert mcdc.NeutronMultigroupData is NeutronMultigroupData
+    assert not hasattr(mcdc, "NeutronMultigroup")
+    assert not hasattr(mcdc, "MGXS")
+    assert issubclass(NeutronMultigroupData, MCDCObject)
+    assert not issubclass(NeutronMultigroupData, MCDCPolymorphic)
+    assert NeutronMultigroupData.label == "neutron_multigroup_data"
+
+
+def test_zero_group_placeholder():
+    neutron_multigroup = NeutronMultigroupData()
+
+    assert neutron_multigroup.G == 0
+    assert neutron_multigroup.J == 0
+    assert not neutron_multigroup.fissionable
+    assert (
+        neutron_multigroup.energy_representation == NEUTRON_MULTIGROUP_ENERGY_MIDPOINT
+    )
+
+    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [-0.499999])
+    np.testing.assert_array_equal(neutron_multigroup.speed, [])
+    np.testing.assert_array_equal(neutron_multigroup.decay_rate, [])
+    np.testing.assert_array_equal(neutron_multigroup.capture, [])
+    np.testing.assert_array_equal(neutron_multigroup.scatter, [])
+    np.testing.assert_array_equal(neutron_multigroup.fission, [])
+    np.testing.assert_array_equal(neutron_multigroup.total, [])
+    np.testing.assert_array_equal(neutron_multigroup.nu_s, [])
+    np.testing.assert_array_equal(neutron_multigroup.nu_p, [])
+    np.testing.assert_array_equal(neutron_multigroup.nu_d, np.empty((0, 0)))
+    np.testing.assert_array_equal(neutron_multigroup.nu_d_total, [])
+    np.testing.assert_array_equal(neutron_multigroup.nu_f, [])
+    np.testing.assert_array_equal(neutron_multigroup.chi_s, np.empty((0, 0)))
+    np.testing.assert_array_equal(neutron_multigroup.chi_p, np.empty((0, 0)))
+    np.testing.assert_array_equal(neutron_multigroup.chi_d, np.empty((0, 0)))
+
+
+def test_capture_only_defaults():
+    neutron_multigroup = NeutronMultigroupData(capture=[0.1, 0.2])
+
+    assert neutron_multigroup.G == 2
+    assert neutron_multigroup.J == 0
+    assert not neutron_multigroup.fissionable
+
+    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [-0.499999, 0.5, 1.5])
+    np.testing.assert_array_equal(neutron_multigroup.speed, [1.0, 1.0])
+    np.testing.assert_array_equal(neutron_multigroup.capture, [0.1, 0.2])
+    np.testing.assert_array_equal(neutron_multigroup.scatter, [0.0, 0.0])
+    np.testing.assert_array_equal(neutron_multigroup.fission, [0.0, 0.0])
+    np.testing.assert_array_equal(neutron_multigroup.total, [0.1, 0.2])
+    np.testing.assert_array_equal(neutron_multigroup.nu_s, [1.0, 1.0])
+    np.testing.assert_array_equal(neutron_multigroup.nu_f, [0.0, 0.0])
+    assert neutron_multigroup.capture.dtype == np.float64
+
+
+def test_documented_two_group_example():
+    neutron_multigroup = NeutronMultigroupData(
+        capture=[0.1, 0.2],
+        scatter=[
+            [1.0, 2.0],
+            [3.0, 0.0],
+        ],
+        nu_s=[1.1, 1.2],
+        energy_grid=[1.0e-5, 1.0, 20.0e6],
+    )
+
+    assert neutron_multigroup.G == 2
+    np.testing.assert_array_equal(neutron_multigroup.capture, [0.1, 0.2])
+    np.testing.assert_array_equal(neutron_multigroup.scatter, [4.0, 2.0])
+    np.testing.assert_allclose(
+        neutron_multigroup.chi_s,
+        [
+            [0.25, 0.75],
+            [1.0, 0.0],
+        ],
+    )
+    np.testing.assert_array_equal(neutron_multigroup.total, [4.1, 2.2])
+    np.testing.assert_array_equal(neutron_multigroup.nu_s, [1.1, 1.2])
+    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [1.0e-5, 1.0, 20.0e6])
+
+
+def test_prompt_fission_spectrum_is_shared_and_normalized():
+    neutron_multigroup = NeutronMultigroupData(
+        fission=[0.2, 0.3],
+        nu_p=[2.4, 2.5],
+        chi_p=[1.0, 3.0],
+    )
+
+    assert neutron_multigroup.fissionable
+    np.testing.assert_array_equal(neutron_multigroup.nu_f, [2.4, 2.5])
+    np.testing.assert_allclose(
+        neutron_multigroup.chi_p,
+        [
+            [0.25, 0.75],
+            [0.25, 0.75],
+        ],
+    )
+
+
+def test_documented_multiple_precursor_group_example():
+    neutron_multigroup = NeutronMultigroupData(
+        fission=[0.2, 0.3],
+        nu_d=[
+            [0.1, 0.2],
+            [0.3, 0.4],
+        ],
+        chi_d=[
+            [1.0, 3.0],
+            [3.0, 1.0],
+        ],
+        decay_rate=[0.01, 0.02],
+    )
+
+    assert neutron_multigroup.J == 2
+    np.testing.assert_array_equal(
+        neutron_multigroup.nu_d,
+        [
+            [0.1, 0.3],
+            [0.2, 0.4],
+        ],
+    )
+    np.testing.assert_allclose(neutron_multigroup.nu_d_total, [0.4, 0.6])
+    np.testing.assert_allclose(neutron_multigroup.nu_f, [0.4, 0.6])
+    np.testing.assert_allclose(
+        neutron_multigroup.chi_d,
+        [
+            [0.25, 0.75],
+            [0.75, 0.25],
+        ],
+    )
+    np.testing.assert_array_equal(neutron_multigroup.decay_rate, [0.01, 0.02])
+
+
+def test_one_group_fission_spectra_default_to_one():
+    neutron_multigroup = NeutronMultigroupData(
+        fission=[0.2],
+        nu_p=[2.4],
+        nu_d=[[0.1], [0.2]],
+    )
+
+    np.testing.assert_array_equal(neutron_multigroup.chi_p, [[1.0]])
+    np.testing.assert_array_equal(neutron_multigroup.chi_d, [[1.0], [1.0]])
+    np.testing.assert_array_equal(neutron_multigroup.nu_f, [2.7])
+    np.testing.assert_array_equal(neutron_multigroup.decay_rate, [np.inf, np.inf])
+
+
+def test_standalone_mg_registration_and_packing(prepare_simulation):
+    neutron_multigroup = NeutronMultigroupData(
+        capture=[0.1, 0.2],
+        scatter=[[1.0, 2.0], [3.0, 0.0]],
+        energy_grid=[1.0e-5, 1.0, 20.0e6],
+    )
+
+    simulation_container, data = prepare_simulation(objects=[neutron_multigroup])
+    simulation = simulation_container[0]
+    reserved = simulation["neutron_multigroup_data"][0]
+    packed = simulation["neutron_multigroup_data"][1]
+
+    assert simulation["N_neutron_multigroup_data"] == 2
+    assert reserved["ID"] == 0
+    assert reserved["G"] == 0
+    assert neutron_multigroup.ID == 1
+    assert packed["ID"] == 1
+    assert packed["G"] == 2
+
+    np.testing.assert_array_equal(
+        get_neutron_multigroup_data.energy_grid_all(reserved, data), [-0.499999]
+    )
+    np.testing.assert_array_equal(
+        get_neutron_multigroup_data.energy_grid_all(packed, data),
+        [1.0e-5, 1.0, 20.0e6],
+    )
+    np.testing.assert_array_equal(
+        get_neutron_multigroup_data.capture_all(packed, data), [0.1, 0.2]
+    )
+    np.testing.assert_array_equal(
+        get_neutron_multigroup_data.scatter_all(packed, data), [4.0, 2.0]
+    )
+    np.testing.assert_allclose(
+        get_neutron_multigroup_data.chi_s_vector(0, packed, data),
+        [0.25, 0.75],
+    )
+
+
+@pytest.mark.parametrize(
+    "policy, expected",
+    [
+        ("midpoint", NEUTRON_MULTIGROUP_ENERGY_MIDPOINT),
+        ("log_midpoint", NEUTRON_MULTIGROUP_ENERGY_MIDPOINT_LOG),
+        ("uniform", NEUTRON_MULTIGROUP_ENERGY_UNIFORM),
+        ("log_uniform", NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG),
+        (NEUTRON_MULTIGROUP_ENERGY_MIDPOINT, NEUTRON_MULTIGROUP_ENERGY_MIDPOINT),
+        (
+            np.int64(NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG),
+            NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG,
+        ),
+    ],
+)
+def test_energy_grid_and_representation(policy, expected):
+    neutron_multigroup = NeutronMultigroupData(
+        capture=[0.1, 0.2],
+        energy_grid=[1.0e-5, 1.0, 20.0e6],
+        energy_representation=policy,
+    )
+
+    assert neutron_multigroup.energy_representation == expected
+    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [1.0e-5, 1.0, 20.0e6])
+
+
+@pytest.mark.parametrize(
+    "kwargs, expected_message",
+    [
+        (
+            {"capture": [0.1, 0.2], "energy_grid": [1.0, 2.0]},
+            "energy_grid must have shape (3,)",
+        ),
+        (
+            {"capture": [0.1, 0.2], "energy_grid": [1.0, 2.0, 2.0]},
+            "energy grid must be strictly increasing",
+        ),
+        (
+            {
+                "capture": [0.1],
+                "energy_grid": [0.0, 1.0],
+                "energy_representation": "log_midpoint",
+            },
+            "logarithmic energy representation requires positive",
+        ),
+        (
+            {"capture": [0.1], "energy_representation": "average"},
+            "Unknown NeutronMultigroupData energy representation",
+        ),
+        (
+            {"fission": [0.1]},
+            "NeutronMultigroupData fission data requires nu_p or nu_d",
+        ),
+        (
+            {"nu_p": [2.4]},
+            "nu_p must have shape (0,)",
+        ),
+        (
+            {"fission": [0.1, 0.2], "nu_p": [2.4, 2.5]},
+            "NeutronMultigroupData with nu_p and G > 1 requires chi_p",
+        ),
+        (
+            {"fission": [0.1, 0.2], "nu_d": [[0.1, 0.2]]},
+            "NeutronMultigroupData with nu_d and G > 1 requires chi_d",
+        ),
+        (
+            {"capture": [-0.1]},
+            "capture entries must be finite and nonnegative",
+        ),
+        (
+            {"capture": [0.1], "speed": [0.0]},
+            "speed entries must be finite and positive",
+        ),
+        (
+            {
+                "fission": [0.1, 0.2],
+                "nu_p": [2.4, 2.5],
+                "chi_p": [0.0, 0.0],
+            },
+            "chi_p spectrum 0 must have positive mass",
+        ),
+    ],
+)
+def test_invalid_inputs_are_rejected(kwargs, expected_message, capsys):
+    with pytest.raises(SystemExit):
+        NeutronMultigroupData(**kwargs)
+
+    assert expected_message in capsys.readouterr().out
+
+
+@pytest.mark.parametrize(
+    "kwargs, expected_message",
+    [
+        (
+            {"capture": [0.1, 0.2], "fission": [0.3], "nu_p": [2.4, 2.5]},
+            "fission must have shape (2,)",
+        ),
+        (
+            {"scatter": [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]]},
+            "scatter must have shape (2, 2)",
+        ),
+        (
+            {"capture": [0.1, 0.2], "speed": [1.0]},
+            "speed must have shape (2,)",
+        ),
+        (
+            {
+                "fission": [0.1, 0.2],
+                "nu_p": [2.4],
+                "chi_p": [0.5, 0.5],
+            },
+            "nu_p must have shape (2,)",
+        ),
+        (
+            {"fission": [0.1, 0.2], "nu_d": [[0.1]]},
+            "nu_d must have shape (J, G) with G = 2",
+        ),
+    ],
+)
+def test_inconsistent_shapes_are_rejected(kwargs, expected_message, capsys):
+    with pytest.raises(SystemExit):
+        NeutronMultigroupData(**kwargs)
+
+    assert expected_message in capsys.readouterr().out
diff --git a/test/unit/test_visualize.py b/test/unit/test_visualize.py
index 11a5d2da7..5b1eb80a9 100644
--- a/test/unit/test_visualize.py
+++ b/test/unit/test_visualize.py
@@ -7,7 +7,7 @@
 
 
 def test_visualize_model(tmp_path):
-    material = mcdc.MaterialMG(capture=np.array([1.0]))
+    material = mcdc.Material.multigroup(capture=np.array([1.0]))
     left = mcdc.Surface.PlaneZ(z=0.0, boundary_condition="vacuum")
     right = mcdc.Surface.PlaneZ(z=1.0, boundary_condition="vacuum")
     cell = mcdc.Cell(region=+left & -right, fill=material)

From cf4b784c223f0587b1966a3c178d3f699da19f45 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 18:40:30 +0700
Subject: [PATCH 120/202] update docs

---
 docs/source/contributing/index.rst             |  3 ++-
 .../architecture/runtime_data_layout.rst       | 14 +++++++++-----
 .../developer_guide/documentation/sphinx.rst   | 16 ++++++++--------
 .../extending/extending_the_object_model.rst   | 15 +++++++++++----
 docs/source/examples/c5g7_k_eigenvalue.rst     |  4 ++--
 docs/source/reference/python_api/index.rst     | 15 +++++++--------
 docs/source/theory/variance_reduction.rst      | 18 +++++++++---------
 .../getting_started/first_simulation.rst       | 16 +++++++++-------
 .../source/user_guide/simulation_lifecycle.rst |  4 ++--
 9 files changed, 59 insertions(+), 46 deletions(-)

diff --git a/docs/source/contributing/index.rst b/docs/source/contributing/index.rst
index 203491a7b..591dbc1c4 100644
--- a/docs/source/contributing/index.rst
+++ b/docs/source/contributing/index.rst
@@ -122,7 +122,8 @@ classes and configuration are primarily defined in ``mcdc/object_/``. Common
 input-related locations include:
 
 #. ``mcdc/object_/settings.py`` — simulation settings and k-eigenvalue parameters
-#. ``mcdc/object_/material.py`` — material definitions (``Material``, ``MaterialMG``)
+#. ``mcdc/object_/material.py`` — material and composition definition
+#. ``mcdc/object_/transport_model_data.py`` — particle-specific transport-model data
 #. ``mcdc/object_/surface.py`` — surface geometry (``Surface`` class methods)
 #. ``mcdc/object_/cell.py`` — cell definitions (``Cell``)
 #. ``mcdc/object_/source.py`` — source specifications (``Source``)
diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index 2458e1d56..72fa92c8e 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -140,7 +140,9 @@ Because every dimension is an integer literal, the three-component array is embe
 The symbolic dimension ``N_move`` names the surface record field that supplies its size at runtime.
 Because that dimension depends on the model, the array is flattened into ``data``, and the surface record stores its offset and total length.
 Fully symbolic multidimensional arrays use the same mechanism.
-For example, ``mgxs_nu_d`` is shaped ``("G", "J")`` and uses the named energy-group and delayed-neutron-group dimensions to reconstruct indexing into its flattened payload.
+For example, ``NeutronMultigroupData.nu_d`` is shaped ``("G", "J")`` and uses the
+named energy-group and delayed-neutron-group dimensions to reconstruct indexing
+into its flattened payload.
 Generated accessors for arrays stored in ``data`` currently support array ranks from one through four dimensions.
 
 ``mcdc.code_factory`` generates modules under ``mcdc/mcdc_get`` and ``mcdc/mcdc_set`` for fields stored in ``data``.
@@ -171,13 +173,15 @@ For ``move_velocities``, the generated accessor uses the fixed trailing dimensio
        move_index, component_index, surface, data
    )
 
-For ``mgxs_nu_d``, the generated element getter reads the named trailing dimension ``J`` from the material record and uses it as the runtime row stride:
+For ``NeutronMultigroupData.nu_d``, the generated element getter reads the named
+trailing dimension ``J`` from the neutron-model record and uses it as the
+runtime row stride:
 
 .. code-block:: python
 
-   def mgxs_nu_d(group, delayed_group, material, data):
-       offset = material["mgxs_nu_d_offset"]
-       stride = material["J"]
+   def nu_d(group, delayed_group, neutron_multigroup, data):
+       offset = neutron_multigroup["nu_d_offset"]
+       stride = neutron_multigroup["J"]
        return data[offset + group * stride + delayed_group]
 
 In the row-major flattened layout, ``J`` determines the stride between energy groups, while ``G`` determines the number of rows.
diff --git a/docs/source/developer_guide/documentation/sphinx.rst b/docs/source/developer_guide/documentation/sphinx.rst
index b56d02c61..5bb486700 100644
--- a/docs/source/developer_guide/documentation/sphinx.rst
+++ b/docs/source/developer_guide/documentation/sphinx.rst
@@ -72,18 +72,18 @@ Within MC/DC's source code, we document functions and classes using docstrings.
 For ``autodoc`` and ``autosummary`` to work, the docstrings within MC/DC's source code must be written in correct rst.
 
 The ``autodoc`` extension includes a set of directives to document different chunks of code (e.g., modules, functions, classes).
-For example, below is the entire rst file that generates the :doc:`../../reference/python_api/generated/mcdc.MaterialMG` page:
+For example, below is the entire rst file that generates the :doc:`../../reference/python_api/generated/mcdc.NeutronMultigroupData` page:
 
 .. code-block::
 
-   mcdc.MaterialMG
-   ===============
+   mcdc.NeutronMultigroupData
+   ======================
 
    .. currentmodule:: mcdc
 
-   .. autoclass:: MaterialMG
+   .. autoclass:: NeutronMultigroupData
 
-(That in-line reference was created using :code:`:doc:\`../../reference/python_api/generated/mcdc.MaterialMG\``, by the way).
+(That in-line reference was created using :code:`:doc:\`../../reference/python_api/generated/mcdc.NeutronMultigroupData\``, by the way).
 
 A rst file with an ``autodoc`` directive is required for each module or function that we would like to document.
 Rather than create all of these rst files by hand, we use the ``autosummary`` extension to do it for us.
@@ -95,12 +95,12 @@ For example, consider the first ``autosummary`` directive in ``source/reference/
    .. autosummary::
 
       mcdc.Material
-      mcdc.MaterialMG
+      mcdc.NeutronMultigroupData
 
 This directive:
-  #. Generates two files in ``reference/python_api/generated/``: ``mcdc.Material.rst`` and ``mcdc.MaterialMG.rst``.
+  #. Generates two files in ``reference/python_api/generated/``: ``mcdc.Material.rst`` and ``mcdc.NeutronMultigroupData.rst``.
   #. Populates each file with the proper autoclass directive.
-  #. Creates a table on :doc:`../../reference/python_api/index` with entries mcdc.Material and mcdc.MaterialMG that link to the respective generated pages.
+  #. Creates a table on :doc:`../../reference/python_api/index` with entries mcdc.Material and mcdc.NeutronMultigroupData that link to the respective generated pages.
 
 
 Building Locally
diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index bd2faa2d1..77ba246be 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -98,7 +98,7 @@ Initialization
       non_numba = ["region", "fill"]
 
       region: Region
-      fill: MaterialBase | Universe | Lattice | None
+      fill: Material | Universe | Lattice | None
       region_RPN_tokens: list[int]
       fill_type: int
       fill_ID: int
@@ -158,7 +158,7 @@ The layer generator interprets annotations according to the field's role:
      - Transport access
    * - ``active: bool``
      - Scalar structured field
-     - ``technique["active"]``
+     - ``simulation["technique"]["new_technique"]["active"]``
    * - ``translation: Annotated[NDArray[float64], (3,)]``
      - Fixed-size embedded array
      - ``cell["translation"][axis]``
@@ -228,17 +228,24 @@ A minimal class has a label, annotated fields, and initialized values:
            self.strength = 1.0
 
 Add an annotated field for the object to its owner and instantiate it with the owner.
-For simulation-wide configuration, this normally means adding the field to ``Simulation`` and constructing it in ``Simulation.__init__``.
+Simulation-wide transport techniques belong to the ``Technique`` aggregate,
+which is itself owned by ``Simulation``.
 The embedded object participates in recursive compilation but does not require a registry branch or object ID.
+This Python ownership hierarchy is preserved under the packed
+``simulation["technique"]`` record.
 
 .. code-block:: python
 
-   class Simulation(MCDCBase):
+   class Technique(MCDCBase):
        new_technique: NewTechnique
 
        def __init__(self):
            self.new_technique = NewTechnique()
 
+The corresponding user and runtime interfaces are
+``simulation.technique.new_technique(...)`` and
+``simulation["technique"]["new_technique"]``.
+
 If the embedded object refers to an ``MCDCObject``, annotate that reference.
 The default traversal will register the referenced object when compilation reaches the embedded configuration.
 
diff --git a/docs/source/examples/c5g7_k_eigenvalue.rst b/docs/source/examples/c5g7_k_eigenvalue.rst
index 9aeb74da1..a054ef719 100644
--- a/docs/source/examples/c5g7_k_eigenvalue.rst
+++ b/docs/source/examples/c5g7_k_eigenvalue.rst
@@ -21,8 +21,8 @@ using MC/DC’s lattice and universe system.
 
 Key concepts demonstrated:
 
-- **Multi-group materials** loaded from an external HDF5 library via
-  ``mcdc.MaterialMG(library=...)``.
+- **Multigroup data** loaded from an external HDF5 library and used to construct
+  materials through ``mcdc.Material.multigroup(...)``.
 - **Pin-cell universes** built from cylindrical fuel pins in square
   moderator cells.
 - **Lattice assemblies** that tile pin-cell universes into fuel
diff --git a/docs/source/reference/python_api/index.rst b/docs/source/reference/python_api/index.rst
index 166f5edbc..9617e9d18 100644
--- a/docs/source/reference/python_api/index.rst
+++ b/docs/source/reference/python_api/index.rst
@@ -43,10 +43,9 @@ Model building blocks
 Materials
 ^^^^^^^^^
 
-Materials define the interaction data used by cells. Use
-:class:`mcdc.Material` for continuous-energy transport and
-:class:`mcdc.MaterialMG` for multigroup transport. :class:`mcdc.MGXS` stores
-particle-agnostic groupwise interaction data for the unified material model.
+Materials define the interaction data used by cells. :class:`mcdc.Material`
+accepts native compositions and particle-specific transport-mode data.
+:class:`mcdc.NeutronMultigroupData` stores reduced multigroup neutron data.
 
 .. autosummary::
    :toctree: generated
@@ -54,8 +53,7 @@ particle-agnostic groupwise interaction data for the unified material model.
    :template: omcclass.rst
 
    mcdc.Material
-   mcdc.MaterialMG
-   mcdc.MGXS
+   mcdc.NeutronMultigroupData
 
 
 Geometry
@@ -134,8 +132,9 @@ the complete settings interface.
 Transport techniques
 ^^^^^^^^^^^^^^^^^^^^
 
-Transport techniques are configured directly on the simulation instance. See
-:class:`mcdc.Simulation` for their signatures and examples.
+Transport techniques are grouped under ``simulation.technique``. For example,
+enable implicit capture with ``simulation.technique.implicit_capture()``. See
+:class:`mcdc.Simulation` for the ownership model and examples.
 
 Compiling and running
 ^^^^^^^^^^^^^^^^^^^^^
diff --git a/docs/source/theory/variance_reduction.rst b/docs/source/theory/variance_reduction.rst
index 7802e1b47..ace885bb9 100644
--- a/docs/source/theory/variance_reduction.rst
+++ b/docs/source/theory/variance_reduction.rst
@@ -33,7 +33,7 @@ effective in highly absorbing media.
 
 .. code-block:: python3
 
-   simulation.implicit_capture()
+   simulation.technique.implicit_capture()
 
 .. note::
 
@@ -59,7 +59,7 @@ preserving the expected weight (unbiased).
 
 .. code-block:: python3
 
-   simulation.global_weight_roulette(
+   simulation.technique.global_weight_roulette(
        weight_threshold=0.25,
        weight_target=1.0,
    )
@@ -88,7 +88,7 @@ This reduces the variance of the fission source weight distribution.
 
 .. code-block:: python3
 
-   simulation.weighted_emission(active=True, weight_target=1.0)
+   simulation.technique.weighted_emission(active=True, weight_target=1.0)
 
 
 Population Control
@@ -105,7 +105,7 @@ rouletting low-weight ones, targeting a uniform weight close to
 
 .. code-block:: python3
 
-   simulation.population_control()
+   simulation.technique.population_control()
 
 Population control is typically combined with a time census
 (``set_time_census``) that checkpoints the particle population at
@@ -133,8 +133,8 @@ setup might use:
 
 .. code-block:: python3
 
-   simulation.implicit_capture()
-   simulation.global_weight_roulette(
+   simulation.technique.implicit_capture()
+   simulation.technique.global_weight_roulette(
        weight_threshold=0.25,
        weight_target=1.0,
    )
@@ -143,9 +143,9 @@ For time-dependent fission problems:
 
 .. code-block:: python3
 
-   simulation.implicit_capture()
-   simulation.weighted_emission(active=True, weight_target=1.0)
-   simulation.population_control()
+   simulation.technique.implicit_capture()
+   simulation.technique.weighted_emission(active=True, weight_target=1.0)
+   simulation.technique.population_control()
 
 The order of activation does not matter — MC/DC applies them in the
 correct transport-physics order internally.
diff --git a/docs/source/user_guide/getting_started/first_simulation.rst b/docs/source/user_guide/getting_started/first_simulation.rst
index 293789924..7e51719c5 100644
--- a/docs/source/user_guide/getting_started/first_simulation.rst
+++ b/docs/source/user_guide/getting_started/first_simulation.rst
@@ -90,23 +90,25 @@ The ``Simulation`` instance collects the model and controls its execution:
 Materials
 ~~~~~~~~~
 
-``MaterialMG`` represents multigroup interaction data. A one-element capture
-array and a :math:`1 \times 1` scattering matrix define a one-group material:
+``NeutronMultigroupData`` stores the underlying multigroup neutron data.
+``Material.multigroup()`` conveniently constructs that model and attaches it to
+a ``Material``. A one-element capture array and a :math:`1 \times 1` scattering
+matrix define one-group neutron data:
 
 .. code-block:: python3
 
-   source_region_material = mcdc.MaterialMG(
+   source_region_material = mcdc.Material.multigroup(
        capture=np.array([0.1]),
        scatter=np.array([[0.9]]),
    )
-   shield_material = mcdc.MaterialMG(
+   shield_material = mcdc.Material.multigroup(
        capture=np.array([0.7]),
        scatter=np.array([[0.3]]),
    )
 
-Continuous-energy calculations instead use :class:`mcdc.Material` and require
-an MC/DC nuclear-data library. See :ref:`install-data-library` for
-configuration instructions.
+Native compositions use the same :class:`mcdc.Material` interface and require
+an MC/DC nuclear-data library. See :ref:`install-data-library` for configuration
+instructions.
 
 Geometry
 ~~~~~~~~
diff --git a/docs/source/user_guide/simulation_lifecycle.rst b/docs/source/user_guide/simulation_lifecycle.rst
index 8bcd598ac..8108369b1 100644
--- a/docs/source/user_guide/simulation_lifecycle.rst
+++ b/docs/source/user_guide/simulation_lifecycle.rst
@@ -27,7 +27,7 @@ objects:
 
 .. code-block:: python
 
-   material = mcdc.MaterialMG(
+   material = mcdc.Material.multigroup(
        capture=np.array([0.1]),
        scatter=np.array([[0.9]]),
    )
@@ -63,7 +63,7 @@ simulation:
 
    simulation.settings.N_particle = 10_000
    simulation.settings.N_batch = 20
-   simulation.implicit_capture()
+   simulation.technique.implicit_capture()
 
 This explicit ownership replaces the former process-wide singleton workflow.
 

From b2858a670f1129f96226087844218d3deda812b3 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 20:29:46 +0700
Subject: [PATCH 121/202] make group independent of energy in particle

---
 mcdc/mcdc_get/tally.py     |  29 ++++++++++
 mcdc/mcdc_set/tally.py     |  29 ++++++++++
 mcdc/numba_types.py        |  13 +++--
 mcdc/object_/particle.py   |   8 ++-
 mcdc/object_/simulation.py |   5 +-
 mcdc/object_/source.py     |  77 +++++++++++++------------
 mcdc/object_/tally.py      | 114 +++++++++++++++++++++++++------------
 mcdc/visualize.py          |   2 +-
 8 files changed, 198 insertions(+), 79 deletions(-)

diff --git a/mcdc/mcdc_get/tally.py b/mcdc/mcdc_get/tally.py
index 5556883c1..3e1c7be67 100644
--- a/mcdc/mcdc_get/tally.py
+++ b/mcdc/mcdc_get/tally.py
@@ -91,6 +91,35 @@ def azi_chunk(start, length, tally, data):
     return data[start:end]
 
 
+@njit
+def group(index, tally, data):
+    offset = tally["group_offset"]
+    return data[offset + index]
+
+
+@njit
+def group_all(tally, data):
+    start = tally["group_offset"]
+    size = tally["group_length"]
+    end = start + size
+    return data[start:end]
+
+
+@njit
+def group_last(tally, data):
+    start = tally["group_offset"]
+    size = tally["group_length"]
+    end = start + size
+    return data[end - 1]
+
+
+@njit
+def group_chunk(start, length, tally, data):
+    start += tally["group_offset"]
+    end = start + length
+    return data[start:end]
+
+
 @njit
 def energy(index, tally, data):
     offset = tally["energy_offset"]
diff --git a/mcdc/mcdc_set/tally.py b/mcdc/mcdc_set/tally.py
index d8daaf548..fb3cd93cd 100644
--- a/mcdc/mcdc_set/tally.py
+++ b/mcdc/mcdc_set/tally.py
@@ -90,6 +90,35 @@ def azi_chunk(start, length, tally, data, value):
     data[start:end] = value
 
 
+@njit
+def group(index, tally, data, value):
+    offset = tally["group_offset"]
+    data[offset + index] = value
+
+
+@njit
+def group_all(tally, data, value):
+    start = tally["group_offset"]
+    size = tally["group_length"]
+    end = start + size
+    data[start:end] = value
+
+
+@njit
+def group_last(tally, data, value):
+    start = tally["group_offset"]
+    size = tally["group_length"]
+    end = start + size
+    data[end - 1] = value
+
+
+@njit
+def group_chunk(start, length, tally, data, value):
+    start += tally["group_offset"]
+    end = start + length
+    data[start:end] = value
+
+
 @njit
 def energy(index, tally, data, value):
     offset = tally["energy_offset"]
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index 78202941b..4d1c46404 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -18,7 +18,7 @@
     ('ux', float64),
     ('uy', float64),
     ('uz', float64),
-    ('g', int64),
+    ('group', int64),
     ('E', float64),
     ('w', float64),
     ('particle_type', int64),
@@ -39,7 +39,7 @@
     ('ux', float64),
     ('uy', float64),
     ('uz', float64),
-    ('g', int64),
+    ('group', int64),
     ('E', float64),
     ('w', float64),
     ('particle_type', int64),
@@ -608,10 +608,11 @@
     ('direction', float64, (3,)),
     ('polar_cosine', float64, (2,)),
     ('azimuthal', float64, (2,)),
+    ('mono_group', bool),
+    ('group', int64),
+    ('group_pmf_ID', int64),
     ('mono_energetic', bool),
-    ('energy_group', int64),
     ('energy', float64),
-    ('energy_group_pmf_ID', int64),
     ('energy_pdf_ID', int64),
     ('discrete_time', bool),
     ('time', float64),
@@ -684,6 +685,7 @@
     ('scores_offset', int64),
     ('scores_length', int64),
     ('filter_direction', bool),
+    ('filter_group', bool),
     ('filter_energy', bool),
     ('filter_time', bool),
     ('mu_offset', int64),
@@ -691,6 +693,8 @@
     ('azi_offset', int64),
     ('azi_length', int64),
     ('polar_reference', float64, (3,)),
+    ('group_offset', int64),
+    ('group_length', int64),
     ('energy_offset', int64),
     ('energy_length', int64),
     ('time_offset', int64),
@@ -705,6 +709,7 @@
     ('bin_shape_length', int64),
     ('stride_mu', int64),
     ('stride_azi', int64),
+    ('stride_group', int64),
     ('stride_energy', int64),
     ('stride_time', int64),
     ('ID', int64),
diff --git a/mcdc/object_/particle.py b/mcdc/object_/particle.py
index bbd7319f1..64f048972 100644
--- a/mcdc/object_/particle.py
+++ b/mcdc/object_/particle.py
@@ -13,7 +13,11 @@
 
 @dataclass
 class ParticleData(MCDCBase):
-    """Serializable phase-space state stored in particle banks."""
+    """Serializable phase-space state stored in particle banks.
+
+    ``group`` is an integer state interpreted by the active transport mode. Neutron
+    multigroup transport uses it as the neutron energy-group index.
+    """
 
     # MC/DC framework metadata
     label = "particle_data"
@@ -25,7 +29,7 @@ class ParticleData(MCDCBase):
     ux: float = 0.0
     uy: float = 0.0
     uz: float = 0.0
-    g: int = -1
+    group: int = -1
     E: float = 0.0
     w: float = 0.0
     particle_type: int = PARTICLE_NEUTRON
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index e328483af..97a93cc04 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -360,7 +360,10 @@ def _finalize_compilation(self) -> None:
             for element in self.elements:
                 element.set_electron_data(self)
 
-        # Derive tally shapes that depend on simulation-wide settings
+        # Resolve tally filters and shapes that require the complete model
+        for tally in self.tallies:
+            tally._resolve_group_filter(self)
+
         if settings.use_census_based_tally:
             for tally in self.tallies:
                 tally._use_census_based_tally(settings.census_tally_frequency, self)
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 8b4b513b1..5bf8a3d1c 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -28,8 +28,8 @@
 class Source(MCDCObject):
     """Define a particle source.
 
-    A source specifies the initial position, direction, energy, time, particle
-    type, and relative sampling probability for emitted particles.
+    A source specifies the position, direction, energy, time, particle type,
+    transport-mode group, and relative sampling probability for emitted particles.
 
     Parameters
     ----------
@@ -67,12 +67,14 @@ class Source(MCDCObject):
         a tabulated distribution: the first row contains energy values and the
         second row contains their probability density. Defaults to a
         mono-energetic source at **1 MeV**.
-    energy_group : int or array_like, optional
-        Source energy group. A Python or NumPy integer defines a mono-group
-        source. An array-like value with shape ``(2, N)`` defines a discrete
-        probability mass function: the first row contains group IDs and the
-        second row contains their probabilities. In multigroup simulations,
-        the default is **group 0**.
+    group : int or array_like, optional
+        Transport-mode group number. A Python or NumPy integer defines a
+        mono-group source. An array-like value with shape ``(2, N)`` defines a
+        discrete probability mass function: the first row contains integer
+        group numbers and the second row contains their probabilities. The
+        interpretation belongs to the active transport mode; neutron
+        multigroup transport interprets it as an energy-group index. The
+        default is **group 0**.
     time : real or array_like of float, optional
         Emission time in seconds. A real scalar, including a NumPy scalar,
         defines a discrete emission time. An array-like value with shape
@@ -100,7 +102,9 @@ class Source(MCDCObject):
       source;
     - otherwise, the default direction behavior is used.
 
-    ``energy_group`` takes precedence over ``energy`` when both are provided.
+    ``energy`` and ``group`` are independent source variables and may both be supplied.
+    If ``energy`` and ``group`` are related, such as in neutron multigroup mode,
+    ``group`` takes precedence over ``energy`` when both are provided.
     Array-like inputs may be supplied as lists, tuples, or NumPy arrays.
 
     Examples
@@ -145,10 +149,10 @@ class Source(MCDCObject):
     ...     azimuthal=[0.0, np.pi / 2],
     ... )
 
-    Discrete energy-group source:
+    Source with a discrete group:
 
     >>> src = mcdc.Source(
-    ...     energy_group=3,
+    ...     group=3,
     ... )
 
     Sample a continuous-energy source from a tabulated probability density:
@@ -162,10 +166,10 @@ class Source(MCDCObject):
     ...     direction=[0.0, 0.0, 1.0],
     ... )
 
-    Sample between two multigroup energy groups:
+    Sample between two groups:
 
     >>> multigroup_source = mcdc.Source(
-    ...     energy_group=(
+    ...     group=(
     ...         [0, 1],
     ...         [0.25, 0.75],
     ...     ),
@@ -198,11 +202,14 @@ class Source(MCDCObject):
     polar_cosine: Annotated[NDArray[float64], (2,)]
     azimuthal: Annotated[NDArray[float64], (2,)]
 
+    # Group
+    mono_group: bool
+    group: int
+    group_pmf: DistributionPMF
+
     # Energy
     mono_energetic: bool
-    energy_group: int
     energy: float
-    energy_group_pmf: DistributionPMF
     energy_pdf: DistributionTabulated
 
     # Time
@@ -238,7 +245,7 @@ def __init__(
         azimuthal: Sequence[float] | NoneType = None,
         #
         energy: ArrayLike | NoneType = None,
-        energy_group: ArrayLike | NoneType = None,
+        group: ArrayLike | NoneType = None,
         #
         time: ArrayLike = 0.0,
         #
@@ -252,7 +259,8 @@ def __init__(
 
         # ==============================================================================
         # Default attributes
-        #   Point source at origin, isotropic, mono-energetic at 1 MeV or at group 0,
+        #   Point source at origin, isotropic, mono-group at 0,
+        #   mono-energetic at 1 MeV,
         #   time = 0, neutron
         # ==============================================================================
 
@@ -271,11 +279,14 @@ def __init__(
         self.polar_cosine = np.array([-1.0, 1.0])
         self.azimuthal = np.array([0.0, 2.0 * PI])
 
+        # Group
+        self.mono_group = True
+        self.group = 0
+        self.group_pmf = DistributionPMF(np.array([0.0]), np.array([1.0]))
+
         # Energy
         self.mono_energetic = True
-        self.energy_group = 0
         self.energy = 1.0e6
-        self.energy_group_pmf = DistributionPMF(np.array([0.0]), np.array([1.0]))
         self.energy_pdf = DistributionTabulated(
             np.array([1.0e6 - 1.0, 1.0e6 + 1.0]),
             np.array([1.0, 1.0]),
@@ -329,17 +340,17 @@ def __init__(
         # Normalize direction
         self.direction /= np.linalg.norm(self.direction)
 
-        # Energy
-        if energy_group is not None:
-            if isinstance(energy_group, Integral) and not isinstance(
-                energy_group, (bool, np.bool_)
-            ):
-                self.energy_group = int(energy_group)
+        # Group
+        if group is not None:
+            if isinstance(group, Integral) and not isinstance(group, (bool, np.bool_)):
+                self.group = int(group)
             else:
-                values, probabilities = _distribution_pair(energy_group, "Energy-group")
-                self.mono_energetic = False
-                self.energy_group_pmf = DistributionPMF(values, probabilities)
-        elif energy is not None:
+                values, probabilities = _distribution_pair(group, "Group")
+                self.mono_group = False
+                self.group_pmf = DistributionPMF(values, probabilities)
+
+        # Energy
+        if energy is not None:
             if isinstance(energy, Real) and not isinstance(energy, (bool, np.bool_)):
                 self.energy = float(energy)
             else:
@@ -392,12 +403,8 @@ def __repr__(self):
             text += f"  - Direction [ux, uy, yz]: {self.direction}\n"
         elif self.white_direction:
             text += f"  - Isotropic halfspace: {self.direction}\n"
-        if self.mono_energetic:
-            text += (
-                f"  - Energy / energy group: {self.energy} eV / {self.energy_group}\n"
-            )
-        else:
-            text += f"  - Energy / energy group: PDF / PMF\n"
+        text += f"  - Group: {self.group if self.mono_group else 'PMF'}\n"
+        text += f"  - Energy: {f'{self.energy} eV' if self.mono_energetic else 'PDF'}\n"
         if self.discrete_time:
             text += f"  - Time: {self.time} s\n"
         else:
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 4697ff3dd..e2afd1064 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -71,8 +71,13 @@ class Tally(MCDCPolymorphic):
         Azimuthal-angle bin boundaries in radians.
     polar_reference : sequence of 3 float, optional
         Reference direction for the angular filters.
-    energy : sequence of float or "all_groups", optional
-        Energy-bin boundaries in eV, or ``"all_groups"`` in multigroup mode.
+    group : sequence of float or "all_groups", optional
+        Transport-mode group-bin boundaries. These bins may collapse several
+        transport groups into one tally bin. ``"all_groups"`` creates one
+        tally bin per group during compilation. For neutron multigroup transport, this
+        corresponds to energy group.
+    energy : sequence of float, optional
+        Continuous-energy bin boundaries in eV.
     time : sequence of float, optional
         Time-bin boundaries in seconds.
 
@@ -151,12 +156,12 @@ class Tally(MCDCPolymorphic):
     ...     scores=["energy_deposition"],
     ... )
 
-    Use one energy bin per multigroup energy group:
+    Use one bin per (energy, for neutron) group:
 
     >>> group_flux = mcdc.Tally(
     ...     cell=cell,
     ...     scores=["flux"],
-    ...     energy="all_groups",
+    ...     group="all_groups",
     ... )
     """
 
@@ -170,11 +175,13 @@ class Tally(MCDCPolymorphic):
 
     # Non-spatial filters
     filter_direction: bool
+    filter_group: bool
     filter_energy: bool
     filter_time: bool
     mu: NDArray[float64]
     azi: NDArray[float64]
     polar_reference: Annotated[NDArray[float64], (3,)]
+    group: NDArray[float64]
     energy: NDArray[float64]
     time: NDArray[float64]
 
@@ -187,6 +194,7 @@ class Tally(MCDCPolymorphic):
     # Filter strides
     stride_mu: int
     stride_azi: int
+    stride_group: int
     stride_energy: int
     stride_time: int
 
@@ -200,7 +208,8 @@ def __new__(
         mu: Sequence[float] | NoneType = None,
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
-        energy: Sequence[float] | str | NoneType = None,
+        group: Sequence[float] | str | NoneType = None,
+        energy: Sequence[float] | NoneType = None,
         time: Sequence[float] | NDArray[float64] | NoneType = None,
         spatial_shape: tuple[int, ...] | NoneType = None,
     ) -> TallySurfaceCrossing | TallyTracklength | TallyCollision:
@@ -259,7 +268,8 @@ def __init__(
         mu: Sequence[float] | NoneType = None,
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
-        energy: Sequence[float] | str | NoneType = None,
+        group: Sequence[float] | str | NoneType = None,
+        energy: Sequence[float] | NoneType = None,
         time: Sequence[float] | NoneType = None,
         spatial_shape: tuple[int, ...] | NoneType = None,
     ):
@@ -296,12 +306,14 @@ def __init__(
         self.mu = np.array([-1.0, 1.0])
         self.azi = np.array([-PI, PI])
         self.polar_reference = np.array([0.0, 0.0, 1.0])
+        self.group = np.array([-INF, INF])
         self.energy = np.array([-1.0, INF])
         self.time = np.array([0.0, INF])
         self.filter_direction = False
+        self.filter_group = False
         self.filter_energy = False
         self.filter_time = False
-        self.energy_all_groups = False
+        self.all_groups = False
         if mu is not None:
             self.mu = np.array(mu)
             self.filter_direction = True
@@ -313,12 +325,15 @@ def __init__(
             self.polar_reference = polar_reference_arr / np.linalg.norm(
                 polar_reference_arr
             )
-        if energy is not None:
-            if type(energy) == str and energy == "all_groups":
-                self.energy_all_groups = True
-                self.energy = np.array([0])  # A placeholder
+        if group is not None:
+            if type(group) == str and group == "all_groups":
+                self.all_groups = True
+                self.group = np.array([0])  # Compilation placeholder
             else:
-                self.energy = np.array(energy)
+                self.group = np.array(group)
+            self.filter_group = True
+        if energy is not None:
+            self.energy = np.array(energy)
             self.filter_energy = True
         if time is not None:
             self.time = np.array(time)
@@ -327,14 +342,17 @@ def __init__(
         # Determine bin shape
         N_mu = len(self.mu) - 1
         N_azi = len(self.azi) - 1
+        N_group = len(self.group) - 1
         N_energy = len(self.energy) - 1
         N_time = len(self.time) - 1
         N_score = len(self.scores)
         #
         if spatial_shape is None:
-            shape = (N_mu, N_azi, N_energy, N_time, N_score)
+            shape = (N_mu, N_azi, N_group, N_energy, N_time, N_score)
         else:
-            shape = (N_mu, N_azi, N_energy, N_time) + spatial_shape + (N_score,)
+            shape = (
+                (N_mu, N_azi, N_group, N_energy, N_time) + spatial_shape + (N_score,)
+            )
 
         # Set bins and strides
         self._set_bin_shape_and_strides(shape)
@@ -344,8 +362,9 @@ def _set_bin_shape_and_strides(self, shape: tuple):
         self.bin_shape = list(shape)
 
         # Set strides
-        self.stride_time = reduce(operator.mul, shape[4:])
-        self.stride_energy = reduce(operator.mul, shape[3:])
+        self.stride_time = reduce(operator.mul, shape[5:])
+        self.stride_energy = reduce(operator.mul, shape[4:])
+        self.stride_group = reduce(operator.mul, shape[3:])
         self.stride_azi = reduce(operator.mul, shape[2:])
         self.stride_mu = reduce(operator.mul, shape[1:])
 
@@ -355,32 +374,42 @@ def _use_census_based_tally(self, frequency: int, simulation):
 
         N_mu = len(self.mu) - 1
         N_azi = len(self.azi) - 1
+        N_group = len(self.group) - 1
         N_energy = len(self.energy) - 1
         N_score = len(self.scores)
 
         spatial_shape = None
-        if len(self.bin_shape) > 5:
-            spatial_shape = tuple(self.bin_shape[4:-1])
+        if len(self.bin_shape) > 6:
+            spatial_shape = tuple(self.bin_shape[5:-1])
 
         if spatial_shape is None:
-            shape = (N_mu, N_azi, N_energy, frequency, N_score)
+            shape = (N_mu, N_azi, N_group, N_energy, frequency, N_score)
         else:
-            shape = (N_mu, N_azi, N_energy, frequency) + spatial_shape + (N_score,)
+            shape = (
+                (N_mu, N_azi, N_group, N_energy, frequency) + spatial_shape + (N_score,)
+            )
 
         self._set_bin_shape_and_strides(shape)
 
     def _phasespace_filter_text(self):
         text = ""
         text += f"  - Scores: {', '.join(decode_score_type(x) for x in self.scores)}\n"
-        if self.filter_time or self.filter_energy or self.filter_direction:
+        if (
+            self.filter_time
+            or self.filter_energy
+            or self.filter_group
+            or self.filter_direction
+        ):
             text += f"  - Phase-space filters\n"
         if self.filter_time:
             text += f"    - Time {print_1d_array(self.time)} s\n"
-        if self.filter_energy:
-            if self.energy_all_groups:
-                text += f"    - Energy: All groups\n"
+        if self.filter_group:
+            if self.all_groups:
+                text += f"    - Group: All groups\n"
             else:
-                text += f"    - Energy {print_1d_array(self.energy)} eV\n"
+                text += f"    - Group {print_1d_array(self.group)}\n"
+        if self.filter_energy:
+            text += f"    - Energy {print_1d_array(self.energy)} eV\n"
         if self.filter_direction:
             text += f"    - Direction\n"
             text += f"    -   Polar reference: {self.polar_reference}\n"
@@ -393,16 +422,17 @@ def _compile_into_simulation(self, simulation) -> bool:
         if not super()._compile_into_simulation(simulation):
             return False
 
-        # Resolve the "all_groups" energy filter and resize its tally bins.
-        if self.energy_all_groups:
+        return True
+
+    def _resolve_group_filter(self, simulation) -> None:
+        """Resolve group filters that require the complete material model."""
+        if self.all_groups:
             G = simulation.materials[0].neutron_multigroup.G
-            self.energy = np.linspace(0, G, G + 1) - 0.5
+            self.group = np.linspace(0, G, G + 1) - 0.5
             shape = list(self.bin_shape)
             shape[2] = G
             self._set_bin_shape_and_strides(tuple(shape))
 
-        return True
-
     def __repr__(self):
         text = super().__repr__()
 
@@ -470,7 +500,8 @@ def __init__(
         mu: Sequence[float] | NoneType = None,
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
-        energy: Sequence[float] | str | NoneType = None,
+        group: Sequence[float] | str | NoneType = None,
+        energy: Sequence[float] | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
         super().__init__(
@@ -479,6 +510,7 @@ def __init__(
             mu=mu,
             azi=azi,
             polar_reference=polar_reference,
+            group=group,
             energy=energy,
             time=time,
         )
@@ -539,7 +571,9 @@ def __repr__(self):
         if isinstance(self.cell, Cell):
             text += f"  - Cell filter: {self.cell.name}\n"
         text += super()._phasespace_filter_text()
-        text += f"  - Bin shape [mu, azi, energy, time, score]: {self.bin_shape} \n"
+        text += (
+            f"  - Bin shape [mu, azi, group, energy, time, score]: {self.bin_shape} \n"
+        )
         return text
 
 
@@ -583,7 +617,8 @@ def __init__(
         mu: Sequence[float] | NoneType = None,
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
-        energy: Sequence[float] | str | NoneType = None,
+        group: Sequence[float] | str | NoneType = None,
+        energy: Sequence[float] | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
         spatial_shape = None
@@ -596,6 +631,7 @@ def __init__(
             mu=mu,
             azi=azi,
             polar_reference=polar_reference,
+            group=group,
             energy=energy,
             time=time,
             spatial_shape=spatial_shape,
@@ -667,7 +703,9 @@ def __repr__(self):
         if self.mesh:
             text += f"  - Mesh: {self.mesh.name}\n"
         text += super()._phasespace_filter_text()
-        text += f"  - Bin shape [mu, azi, energy, time, score]: {self.bin_shape} \n"
+        text += (
+            f"  - Bin shape [mu, azi, group, energy, time, score]: {self.bin_shape} \n"
+        )
         return text
 
 
@@ -711,7 +749,8 @@ def __init__(
         mu: Sequence[float] | NoneType = None,
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
-        energy: Sequence[float] | str | NoneType = None,
+        group: Sequence[float] | str | NoneType = None,
+        energy: Sequence[float] | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
         spatial_shape = None
@@ -724,6 +763,7 @@ def __init__(
             mu=mu,
             azi=azi,
             polar_reference=polar_reference,
+            group=group,
             energy=energy,
             time=time,
             spatial_shape=spatial_shape,
@@ -796,5 +836,7 @@ def __repr__(self):
         if self.mesh:
             text += f"  - Mesh: {self.mesh.name}\n"
         text += super()._phasespace_filter_text()
-        text += f"  - Bin shape [mu, azi, energy, time, score]: {self.bin_shape} \n"
+        text += (
+            f"  - Bin shape [mu, azi, group, energy, time, score]: {self.bin_shape} \n"
+        )
         return text
diff --git a/mcdc/visualize.py b/mcdc/visualize.py
index 27de675be..b52c66ffa 100644
--- a/mcdc/visualize.py
+++ b/mcdc/visualize.py
@@ -95,7 +95,7 @@ def _compute_material_row(
 
         # Set time and energy
         particle["t"] = time_val
-        particle["g"] = 0
+        particle["group"] = 0
         particle["E"] = 1e6
         particle["ux"] = 0.0
         particle["uy"] = 0.0

From b858301631469feac49f9e73f7b90bca618526f1 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 20:47:55 +0700
Subject: [PATCH 122/202] add particle_type to tally

---
 mcdc/numba_types.py        |  1 +
 mcdc/object_/simulation.py |  1 +
 mcdc/object_/tally.py      | 77 ++++++++++++++++++++++++++++++++++++++
 3 files changed, 79 insertions(+)

diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index 4d1c46404..9d42bd46d 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -684,6 +684,7 @@
     ('name', 'U32'),
     ('scores_offset', int64),
     ('scores_length', int64),
+    ('particle_type', int64),
     ('filter_direction', bool),
     ('filter_group', bool),
     ('filter_energy', bool),
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 97a93cc04..788570c69 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -362,6 +362,7 @@ def _finalize_compilation(self) -> None:
 
         # Resolve tally filters and shapes that require the complete model
         for tally in self.tallies:
+            tally._resolve_particle_type(settings)
             tally._resolve_group_filter(self)
 
         if settings.use_census_based_tally:
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index e2afd1064..ade99ae35 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -23,6 +23,9 @@
     MESH_STRUCTURED,
     MESH_UNIFORM,
     PI,
+    PARTICLE_NEUTRON,
+    PARTICLE_ELECTRON,
+    PARTICLE_PROTON,
     SCORE_FLUX,
     SCORE_DENSITY,
     SCORE_COLLISION,
@@ -71,6 +74,10 @@ class Tally(MCDCPolymorphic):
         Azimuthal-angle bin boundaries in radians.
     polar_reference : sequence of 3 float, optional
         Reference direction for the angular filters.
+    particle_type : {"neutron", "electron", "proton"}, optional
+        Particle type selected by the tally. If omitted, compilation infers it
+        when exactly one particle type is transported per the simulation settings.
+        It must be specified when multiple particle types are transported.
     group : sequence of float or "all_groups", optional
         Transport-mode group-bin boundaries. These bins may collapse several
         transport groups into one tally bin. ``"all_groups"`` creates one
@@ -174,6 +181,7 @@ class Tally(MCDCPolymorphic):
     scores: list[int]
 
     # Non-spatial filters
+    particle_type: int
     filter_direction: bool
     filter_group: bool
     filter_energy: bool
@@ -208,6 +216,7 @@ def __new__(
         mu: Sequence[float] | NoneType = None,
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
+        particle_type: str | NoneType = None,
         group: Sequence[float] | str | NoneType = None,
         energy: Sequence[float] | NoneType = None,
         time: Sequence[float] | NDArray[float64] | NoneType = None,
@@ -268,6 +277,7 @@ def __init__(
         mu: Sequence[float] | NoneType = None,
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
+        particle_type: str | NoneType = None,
         group: Sequence[float] | str | NoneType = None,
         energy: Sequence[float] | NoneType = None,
         time: Sequence[float] | NoneType = None,
@@ -302,6 +312,18 @@ def __init__(
             else:
                 print_error(f"Unknown tally score: {score}")
 
+        # Particle filter
+        if particle_type is None:
+            self.particle_type = -1
+        elif particle_type == "neutron":
+            self.particle_type = PARTICLE_NEUTRON
+        elif particle_type == "electron":
+            self.particle_type = PARTICLE_ELECTRON
+        elif particle_type == "proton":
+            self.particle_type = PARTICLE_PROTON
+        else:
+            print_error(f"Unsupported tally particle type: {particle_type}")
+
         # Phase-space filters
         self.mu = np.array([-1.0, 1.0])
         self.azi = np.array([-PI, PI])
@@ -394,6 +416,12 @@ def _use_census_based_tally(self, frequency: int, simulation):
     def _phasespace_filter_text(self):
         text = ""
         text += f"  - Scores: {', '.join(decode_score_type(x) for x in self.scores)}\n"
+        particle_name = {
+            PARTICLE_NEUTRON: "Neutron",
+            PARTICLE_ELECTRON: "Electron",
+            PARTICLE_PROTON: "Proton",
+        }.get(self.particle_type, "Unspecified")
+        text += f"  - Particle: {particle_name}\n"
         if (
             self.filter_time
             or self.filter_energy
@@ -427,12 +455,55 @@ def _compile_into_simulation(self, simulation) -> bool:
     def _resolve_group_filter(self, simulation) -> None:
         """Resolve group filters that require the complete material model."""
         if self.all_groups:
+            if self.particle_type != PARTICLE_NEUTRON:
+                print_error("The all_groups filter currently supports only neutrons.")
+            if not simulation.materials or any(
+                not material.has_neutron_multigroup for material in simulation.materials
+            ):
+                print_error(
+                    "The all_groups neutron filter requires multigroup data for "
+                    "every material."
+                )
+            shared_grid = simulation.materials[0].neutron_multigroup.energy_grid
+            if any(
+                not np.array_equal(material.neutron_multigroup.energy_grid, shared_grid)
+                for material in simulation.materials[1:]
+            ):
+                print_error(
+                    "The all_groups neutron filter requires one shared multigroup "
+                    "energy grid."
+                )
             G = simulation.materials[0].neutron_multigroup.G
             self.group = np.linspace(0, G, G + 1) - 0.5
             shape = list(self.bin_shape)
             shape[2] = G
             self._set_bin_shape_and_strides(tuple(shape))
 
+    def _resolve_particle_type(self, settings) -> None:
+        """Infer an unspecified tally particle type from transport settings."""
+        if self.particle_type != -1:
+            return
+
+        transported = []
+        if settings.neutron_transport:
+            transported.append(PARTICLE_NEUTRON)
+        if settings.electron_transport:
+            transported.append(PARTICLE_ELECTRON)
+        if settings.proton_transport:
+            transported.append(PARTICLE_PROTON)
+
+        if len(transported) > 1:
+            print_error(
+                "Tally particle_type must be specified when multiple particle "
+                "types are transported."
+            )
+        if len(transported) == 0:
+            print_error(
+                "Tally particle_type cannot be inferred because no particle type "
+                "is transported."
+            )
+        self.particle_type = transported[0]
+
     def __repr__(self):
         text = super().__repr__()
 
@@ -500,6 +571,7 @@ def __init__(
         mu: Sequence[float] | NoneType = None,
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
+        particle_type: str | NoneType = None,
         group: Sequence[float] | str | NoneType = None,
         energy: Sequence[float] | NoneType = None,
         time: Sequence[float] | NoneType = None,
@@ -510,6 +582,7 @@ def __init__(
             mu=mu,
             azi=azi,
             polar_reference=polar_reference,
+            particle_type=particle_type,
             group=group,
             energy=energy,
             time=time,
@@ -617,6 +690,7 @@ def __init__(
         mu: Sequence[float] | NoneType = None,
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
+        particle_type: str | NoneType = None,
         group: Sequence[float] | str | NoneType = None,
         energy: Sequence[float] | NoneType = None,
         time: Sequence[float] | NoneType = None,
@@ -631,6 +705,7 @@ def __init__(
             mu=mu,
             azi=azi,
             polar_reference=polar_reference,
+            particle_type=particle_type,
             group=group,
             energy=energy,
             time=time,
@@ -749,6 +824,7 @@ def __init__(
         mu: Sequence[float] | NoneType = None,
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
+        particle_type: str | NoneType = None,
         group: Sequence[float] | str | NoneType = None,
         energy: Sequence[float] | NoneType = None,
         time: Sequence[float] | NoneType = None,
@@ -763,6 +839,7 @@ def __init__(
             mu=mu,
             azi=azi,
             polar_reference=polar_reference,
+            particle_type=particle_type,
             group=group,
             energy=energy,
             time=time,

From b5165ce11c993f2a77404c1aa2b793c7683850eb Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 21:34:15 +0700
Subject: [PATCH 123/202] add type check

---
 mcdc/object_/source.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 5bf8a3d1c..5ef3fac5b 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -346,6 +346,10 @@ def __init__(
                 self.group = int(group)
             else:
                 values, probabilities = _distribution_pair(group, "Group")
+                if not np.all(np.isfinite(values)) or not np.all(
+                    values == np.floor(values)
+                ):
+                    print_error("Group distribution values must be integers")
                 self.mono_group = False
                 self.group_pmf = DistributionPMF(values, probabilities)
 

From 89cd826c1cca005ee5ec159861f15ddaf447a6e5 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 21:40:03 +0700
Subject: [PATCH 124/202] introduce PARTICLE_ANY

---
 mcdc/constant.py      |  1 +
 mcdc/object_/tally.py | 22 +++++++++++++---------
 2 files changed, 14 insertions(+), 9 deletions(-)

diff --git a/mcdc/constant.py b/mcdc/constant.py
index 10bf5033c..90381aaab 100644
--- a/mcdc/constant.py
+++ b/mcdc/constant.py
@@ -31,6 +31,7 @@
 PARTICLE_NEUTRON = 0
 PARTICLE_ELECTRON = 1
 PARTICLE_PROTON = 2
+PARTICLE_ANY = 100
 
 # Neutron multigroup energy representation
 NEUTRON_MULTIGROUP_ENERGY_MIDPOINT = 0
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index ade99ae35..e3dc95251 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -23,6 +23,7 @@
     MESH_STRUCTURED,
     MESH_UNIFORM,
     PI,
+    PARTICLE_ANY,
     PARTICLE_NEUTRON,
     PARTICLE_ELECTRON,
     PARTICLE_PROTON,
@@ -78,9 +79,9 @@ class Tally(MCDCPolymorphic):
         Particle type selected by the tally. If omitted, compilation infers it
         when exactly one particle type is transported per the simulation settings.
         It must be specified when multiple particle types are transported.
-    group : sequence of float or "all_groups", optional
+    group : sequence of float or "all", optional
         Transport-mode group-bin boundaries. These bins may collapse several
-        transport groups into one tally bin. ``"all_groups"`` creates one
+        transport groups into one tally bin. ``"all"`` creates one
         tally bin per group during compilation. For neutron multigroup transport, this
         corresponds to energy group.
     energy : sequence of float, optional
@@ -168,7 +169,7 @@ class Tally(MCDCPolymorphic):
     >>> group_flux = mcdc.Tally(
     ...     cell=cell,
     ...     scores=["flux"],
-    ...     group="all_groups",
+    ...     group="all",
     ... )
     """
 
@@ -314,7 +315,7 @@ def __init__(
 
         # Particle filter
         if particle_type is None:
-            self.particle_type = -1
+            self.particle_type = PARTICLE_ANY
         elif particle_type == "neutron":
             self.particle_type = PARTICLE_NEUTRON
         elif particle_type == "electron":
@@ -348,7 +349,9 @@ def __init__(
                 polar_reference_arr
             )
         if group is not None:
-            if type(group) == str and group == "all_groups":
+            if isinstance(group, str):
+                if group != "all":
+                    print_error(f"Unsupported tally group filter: {group}")
                 self.all_groups = True
                 self.group = np.array([0])  # Compilation placeholder
             else:
@@ -417,6 +420,7 @@ def _phasespace_filter_text(self):
         text = ""
         text += f"  - Scores: {', '.join(decode_score_type(x) for x in self.scores)}\n"
         particle_name = {
+            PARTICLE_ANY: "Any",
             PARTICLE_NEUTRON: "Neutron",
             PARTICLE_ELECTRON: "Electron",
             PARTICLE_PROTON: "Proton",
@@ -456,12 +460,12 @@ def _resolve_group_filter(self, simulation) -> None:
         """Resolve group filters that require the complete material model."""
         if self.all_groups:
             if self.particle_type != PARTICLE_NEUTRON:
-                print_error("The all_groups filter currently supports only neutrons.")
+                print_error('The group="all" filter currently supports only neutrons.')
             if not simulation.materials or any(
                 not material.has_neutron_multigroup for material in simulation.materials
             ):
                 print_error(
-                    "The all_groups neutron filter requires multigroup data for "
+                    'The neutron group="all" filter requires multigroup data for '
                     "every material."
                 )
             shared_grid = simulation.materials[0].neutron_multigroup.energy_grid
@@ -470,7 +474,7 @@ def _resolve_group_filter(self, simulation) -> None:
                 for material in simulation.materials[1:]
             ):
                 print_error(
-                    "The all_groups neutron filter requires one shared multigroup "
+                    'The neutron group="all" filter requires one shared multigroup '
                     "energy grid."
                 )
             G = simulation.materials[0].neutron_multigroup.G
@@ -481,7 +485,7 @@ def _resolve_group_filter(self, simulation) -> None:
 
     def _resolve_particle_type(self, settings) -> None:
         """Infer an unspecified tally particle type from transport settings."""
-        if self.particle_type != -1:
+        if self.particle_type != PARTICLE_ANY:
             return
 
         transported = []

From 89fb7120afc6d536adc84c103d3530a2e591de1a Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 21:41:34 +0700
Subject: [PATCH 125/202] imporve particle type filtering

---
 mcdc/object_/simulation.py |  1 -
 mcdc/object_/tally.py      | 30 ++----------------------------
 2 files changed, 2 insertions(+), 29 deletions(-)

diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 788570c69..97a93cc04 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -362,7 +362,6 @@ def _finalize_compilation(self) -> None:
 
         # Resolve tally filters and shapes that require the complete model
         for tally in self.tallies:
-            tally._resolve_particle_type(settings)
             tally._resolve_group_filter(self)
 
         if settings.use_census_based_tally:
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index e3dc95251..c6f9918c4 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -76,9 +76,8 @@ class Tally(MCDCPolymorphic):
     polar_reference : sequence of 3 float, optional
         Reference direction for the angular filters.
     particle_type : {"neutron", "electron", "proton"}, optional
-        Particle type selected by the tally. If omitted, compilation infers it
-        when exactly one particle type is transported per the simulation settings.
-        It must be specified when multiple particle types are transported.
+        Particle type selected by the tally. If omitted, the tally accepts any
+        transported particle type.
     group : sequence of float or "all", optional
         Transport-mode group-bin boundaries. These bins may collapse several
         transport groups into one tally bin. ``"all"`` creates one
@@ -483,31 +482,6 @@ def _resolve_group_filter(self, simulation) -> None:
             shape[2] = G
             self._set_bin_shape_and_strides(tuple(shape))
 
-    def _resolve_particle_type(self, settings) -> None:
-        """Infer an unspecified tally particle type from transport settings."""
-        if self.particle_type != PARTICLE_ANY:
-            return
-
-        transported = []
-        if settings.neutron_transport:
-            transported.append(PARTICLE_NEUTRON)
-        if settings.electron_transport:
-            transported.append(PARTICLE_ELECTRON)
-        if settings.proton_transport:
-            transported.append(PARTICLE_PROTON)
-
-        if len(transported) > 1:
-            print_error(
-                "Tally particle_type must be specified when multiple particle "
-                "types are transported."
-            )
-        if len(transported) == 0:
-            print_error(
-                "Tally particle_type cannot be inferred because no particle type "
-                "is transported."
-            )
-        self.particle_type = transported[0]
-
     def __repr__(self):
         text = super().__repr__()
 

From 7516d77a4be2fd9bce7ce0443248826b34394f29 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 22:21:12 +0700
Subject: [PATCH 126/202] comment out file-based source

---
 mcdc/main.py | 48 ++++++++++++++++++++----------------------------
 1 file changed, 20 insertions(+), 28 deletions(-)

diff --git a/mcdc/main.py b/mcdc/main.py
index 7887bd37d..7f017856a 100644
--- a/mcdc/main.py
+++ b/mcdc/main.py
@@ -117,10 +117,6 @@ def prepare(simulationPy: Simulation):
     This function packs that model, allocates execution resources, configures
     the selected backend, and loads any external source-particle state.
     """
-    from mpi4py import MPI
-
-    settings = simulationPy.settings
-
     # ==================================================================================
     # Generate Numba runtime layers
     # ==================================================================================
@@ -155,30 +151,26 @@ def prepare(simulationPy: Simulation):
     # ==================================================================================
     # Source particles from file
     # ==================================================================================
-    # TODO: Use parallel h5py, may need to compile for speed
-
-    import h5py
-
-    # All ranks, take turn
-    for i in range(simulation["mpi_size"]):
-        if simulation["mpi_rank"] == i:
-            if settings.use_source_file:
-                with h5py.File(settings.source_file_name, "r") as f:
-                    # Get source particle size
-                    N_particle = f["particles_size"][()]
-
-                    # Redistribute work
-                    mpi.distribute_work(N_particle, simulation)
-                    N_local = simulation["mpi_work_size"]
-                    start = simulation["mpi_work_start"]
-                    end = start + N_local
-
-                    # Add particles to source bank
-                    simulation["bank_source"]["particles"][:N_local] = f["particles"][
-                        start:end
-                    ]
-                    simulation["bank_source"]["size"] = N_local
-        MPI.COMM_WORLD.Barrier()
+    # TODO: Re-enable file-backed source initialization after its particle-bank
+    # schema and MPI redistribution path are updated.
+    #
+    # import h5py
+    # import mcdc.transport.mpi as mpi
+    # from mpi4py import MPI
+    #
+    # for i in range(simulation["mpi_size"]):
+    #     if simulation["mpi_rank"] == i and settings.use_source_file:
+    #         with h5py.File(settings.source_file_name, "r") as f:
+    #             N_particle = f["particles_size"][()]
+    #             mpi.distribute_work(N_particle, simulation)
+    #             N_local = simulation["mpi_work_size"]
+    #             start = simulation["mpi_work_start"]
+    #             end = start + N_local
+    #             simulation["bank_source"]["particle_data"][:N_local] = f[
+    #                 "particles"
+    #             ][start:end]
+    #             simulation["bank_source"]["size"] = N_local
+    #     MPI.COMM_WORLD.Barrier()
 
     # ==================================================================================
     # Finalize

From d8e3fbba9c37499cd7e2c634c8c280e0109a2e15 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 22:29:51 +0700
Subject: [PATCH 127/202] cleanup inconsistencies

---
 .../user_guide/simulation_lifecycle.rst       |  6 ++++++
 mcdc/code_factory/python_objects_compiler.py  |  4 ++++
 mcdc/object_/material.py                      | 21 +++++++++++++++----
 mcdc/object_/settings.py                      |  2 +-
 mcdc/object_/source.py                        |  6 +++---
 mcdc/object_/tally.py                         |  9 ++++----
 mcdc/object_/transport_model_data.py          | 11 +++++++++-
 7 files changed, 45 insertions(+), 14 deletions(-)

diff --git a/docs/source/user_guide/simulation_lifecycle.rst b/docs/source/user_guide/simulation_lifecycle.rst
index 8108369b1..1c62eb62a 100644
--- a/docs/source/user_guide/simulation_lifecycle.rst
+++ b/docs/source/user_guide/simulation_lifecycle.rst
@@ -107,6 +107,12 @@ modify an attached object after explicitly compiling or visualizing the model,
 call ``simulation.compile()`` again before inspecting or visualizing the
 change.
 
+Compilation finalizes some user-facing values in place. In particular, source
+probabilities are normalized, tally limits may reduce ``settings.time_boundary``,
+and particle-bank buffer ratios may be adjusted for the selected run mode. Set
+new raw values explicitly before recompiling when an iterative workflow changes
+one of these inputs.
+
 4. Visualize or Run
 -------------------
 
diff --git a/mcdc/code_factory/python_objects_compiler.py b/mcdc/code_factory/python_objects_compiler.py
index c7272aa90..dc734d4bf 100644
--- a/mcdc/code_factory/python_objects_compiler.py
+++ b/mcdc/code_factory/python_objects_compiler.py
@@ -26,6 +26,10 @@ def compile_simulation(simulation: Simulation):
     complete, the owning :class:`~mcdc.object_.simulation.Simulation` resolves
     model-wide state before runtime packing begins.
     """
+    # Require geometry rooted in at least one cell
+    if len(simulation.root_universe.cells) == 0:
+        print_error("Simulation model has not been set (root universe is empty).")
+
     # Preserve explicitly configured roots before resetting their registered
     # object lists. Geometry members may reference these objects and compile
     # them while the model graph is traversed.
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 67574adab..e52a6c4fb 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -33,8 +33,8 @@ class Material(MCDCObject):
         temperature available in the data library.
     neutron_multigroup : NeutronMultigroupData, optional
         Multigroup cross sections for neutron transport. When supplied with a
-        native composition, its ``energy_grid`` defines the energy range over
-        which multigroup physics applies.
+        native composition, an explicit ``energy_grid`` is required and defines
+        the energy range over which multigroup physics applies.
 
     Notes
     -----
@@ -42,8 +42,7 @@ class Material(MCDCObject):
     Nuclide and element compositions cannot both be specified because they are
     alternative native representations of the same material. A native
     composition may be supplied together with ``neutron_multigroup`` for hybrid
-    neutron physics. An omitted multigroup energy grid uses the default
-    group-coordinate boundaries.
+    neutron physics.
 
     Nuclide and element objects are created immediately; their data-library
     properties are loaded when the material is compiled into a simulation.
@@ -131,6 +130,20 @@ def __init__(
             neutron_multigroup, NeutronMultigroupData
         ):
             print_error("neutron_multigroup must be a NeutronMultigroupData object.")
+        if neutron_multigroup is not None and neutron_multigroup.G == 0:
+            print_error(
+                "Material neutron_multigroup must define at least one energy group."
+            )
+        if (
+            (nuclide_composition or element_composition)
+            and neutron_multigroup is not None
+            and neutron_multigroup.G > 0
+            and neutron_multigroup._uses_default_energy_grid
+        ):
+            print_error(
+                "Material requires an explicit neutron multigroup energy_grid "
+                "when a nuclide or element composition is supplied."
+            )
         # Initialize shared material state
         self.name = name or "(Unnamed material)"
         self.temperature = float(temperature)
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index 2ba992987..5665f6442 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -136,7 +136,7 @@ def set_time_census(self, time, tally_frequency=None):
 
         # Set the census-based tallying
         if tally_frequency is not None and tally_frequency > 0:
-            # Flag to reset all tallies' time grids (done in main.py)
+            # Flag to reset all tally time grids during simulation compilation
             self.use_census_based_tally = True
             self.census_tally_frequency = tally_frequency
 
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 5ef3fac5b..78675fe3f 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -102,9 +102,9 @@ class Source(MCDCObject):
       source;
     - otherwise, the default direction behavior is used.
 
-    ``energy`` and ``group`` are independent source variables and may both be supplied.
-    If ``energy`` and ``group`` are related, such as in neutron multigroup mode,
-    ``group`` takes precedence over ``energy`` when both are provided.
+    ``energy`` and ``group`` are independent source variables and may both be
+    supplied. When shared-grid neutron multigroup transport is used, ``group``
+    takes precedence over ``energy`` when both are provided.
     Array-like inputs may be supplied as lists, tuples, or NumPy arrays.
 
     Examples
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index c6f9918c4..43b41e585 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -80,9 +80,8 @@ class Tally(MCDCPolymorphic):
         transported particle type.
     group : sequence of float or "all", optional
         Transport-mode group-bin boundaries. These bins may collapse several
-        transport groups into one tally bin. ``"all"`` creates one
-        tally bin per group during compilation. For neutron multigroup transport, this
-        corresponds to energy group.
+        transport groups into one tally bin. ``"all"`` creates one tally bin
+        per neutron energy group during compilation.
     energy : sequence of float, optional
         Continuous-energy bin boundaries in eV.
     time : sequence of float, optional
@@ -163,7 +162,7 @@ class Tally(MCDCPolymorphic):
     ...     scores=["energy_deposition"],
     ... )
 
-    Use one bin per (energy, for neutron) group:
+    Use one bin per neutron energy group:
 
     >>> group_flux = mcdc.Tally(
     ...     cell=cell,
@@ -458,7 +457,7 @@ def _compile_into_simulation(self, simulation) -> bool:
     def _resolve_group_filter(self, simulation) -> None:
         """Resolve group filters that require the complete material model."""
         if self.all_groups:
-            if self.particle_type != PARTICLE_NEUTRON:
+            if self.particle_type not in (PARTICLE_ANY, PARTICLE_NEUTRON):
                 print_error('The group="all" filter currently supports only neutrons.')
             if not simulation.materials or any(
                 not material.has_neutron_multigroup for material in simulation.materials
diff --git a/mcdc/object_/transport_model_data.py b/mcdc/object_/transport_model_data.py
index 52829c591..3c2dd57ca 100644
--- a/mcdc/object_/transport_model_data.py
+++ b/mcdc/object_/transport_model_data.py
@@ -89,7 +89,8 @@ class NeutronMultigroupData(MCDCObject):
     ``G`` is inferred from ``capture``, ``scatter``, or ``fission``. Calling
     ``NeutronMultigroupData()`` without any cross sections creates the reserved
     zero-group placeholder used by materials without multigroup data. Cross
-    sections are macroscopic and use inverse-length units.
+    sections are macroscopic and use inverse-length units. The generated default
+    energy grid supports only the default ``"midpoint"`` representation.
 
     Examples
     --------
@@ -138,10 +139,12 @@ class NeutronMultigroupData(MCDCObject):
 
     # MC/DC framework metadata
     label = "neutron_multigroup_data"
+    non_numba = ["_uses_default_energy_grid"]
 
     G: int
     J: int
 
+    _uses_default_energy_grid: bool  # Non-Numba
     energy_grid: Annotated[NDArray[float64], ("G+1",)]
     energy_representation: int
 
@@ -245,7 +248,13 @@ def __init__(
         self.energy_representation = _resolve_energy_representation(
             energy_representation
         )
+        self._uses_default_energy_grid = energy_grid is None
         if energy_grid is None:
+            if self.energy_representation != NEUTRON_MULTIGROUP_ENERGY_MIDPOINT:
+                print_error(
+                    "NeutronMultigroupData requires an explicit energy_grid when "
+                    "energy_representation is not 'midpoint'."
+                )
             self.energy_grid = np.arange(self.G + 1, dtype=float64) - 0.5
             self.energy_grid[0] += 1.0e-6
         else:

From c8f43b4ae3fa2f2560784aa46cc90421c9b5be23 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 22:49:48 +0700
Subject: [PATCH 128/202] clean leftover

---
 mcdc/object_/particle.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/mcdc/object_/particle.py b/mcdc/object_/particle.py
index 64f048972..3b9c4ec8a 100644
--- a/mcdc/object_/particle.py
+++ b/mcdc/object_/particle.py
@@ -1,6 +1,6 @@
 import numpy as np
 
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 from typing import Annotated
 from numpy import int64, uint64
 from numpy.typing import NDArray
@@ -8,7 +8,7 @@
 ####
 
 from mcdc.constant import PARTICLE_NEUTRON
-from mcdc.object_.base import MCDCBase, MCDCBase
+from mcdc.object_.base import MCDCBase
 
 
 @dataclass

From da2fa0806fc2a8dd842fbdd04b094bbe6aaf0e7d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 22:50:34 +0700
Subject: [PATCH 129/202] update examples

---
 examples/c5g7/k-eigenvalue/input.py            | 4 ++--
 examples/c5g7/transient/input.py               | 2 +-
 examples/fuel_array_packaged/input.py          | 2 +-
 examples/iterative_source_reweighting/input.py | 4 ++--
 examples/kobayashi-TD/input.py                 | 2 +-
 examples/kobayashi/input.py                    | 2 +-
 examples/moving_pellet/input.py                | 2 +-
 examples/moving_source/input.py                | 2 +-
 examples/slab_shielding/input.py               | 2 +-
 examples/sphere_in_cube/input.py               | 2 +-
 10 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/examples/c5g7/k-eigenvalue/input.py b/examples/c5g7/k-eigenvalue/input.py
index a7c91386d..edd163960 100644
--- a/examples/c5g7/k-eigenvalue/input.py
+++ b/examples/c5g7/k-eigenvalue/input.py
@@ -279,7 +279,7 @@ def set_mat(mat):
     y=[-pitch * 17 * 2, 0.0],
     z=[-core_height / 2, core_height / 2],
     isotropic=True,
-    energy_group=0,  # Highest energy
+    group=0,  # Highest energy
 )
 simulation.set_sources([source])
 
@@ -295,7 +295,7 @@ def set_mat(mat):
 )
 g_grid = np.array([-0.5, 3.5, 6.5])  # Collapsing to fast (1-4) and slow (5-7)
 mesh = mcdc.MeshStructured(x=x_grid, y=y_grid, z=z_grid)
-tally = mcdc.Tally(mesh=mesh, scores=["flux"], energy=g_grid)
+tally = mcdc.Tally(mesh=mesh, scores=["flux"], group=g_grid)
 simulation.set_tallies([tally])
 
 # Settings
diff --git a/examples/c5g7/transient/input.py b/examples/c5g7/transient/input.py
index 55462d474..f7d5da4c0 100644
--- a/examples/c5g7/transient/input.py
+++ b/examples/c5g7/transient/input.py
@@ -340,7 +340,7 @@ def set_mat(mat):
     y=np.array([-pitch * 17 * 3 / 2] * 2) + np.array([-pitch / 2, +pitch / 2]),
     z=[-core_height / 2, core_height / 2],
     isotropic=True,
-    energy_group=0,  # Highest energy
+    group=0,  # Highest energy
     time=[0.0, 15.0],
 )
 simulation.set_sources([source])
diff --git a/examples/fuel_array_packaged/input.py b/examples/fuel_array_packaged/input.py
index 3a1039189..294d0d991 100644
--- a/examples/fuel_array_packaged/input.py
+++ b/examples/fuel_array_packaged/input.py
@@ -77,7 +77,7 @@
 # Set source
 # ======================================================================================
 
-source = mcdc.Source(x=[-0.1, 0.1], isotropic=True, energy_group=0)
+source = mcdc.Source(x=[-0.1, 0.1], isotropic=True, group=0)
 simulation.set_sources([source])
 
 # ======================================================================================
diff --git a/examples/iterative_source_reweighting/input.py b/examples/iterative_source_reweighting/input.py
index a0ac53d0f..15c57b69a 100644
--- a/examples/iterative_source_reweighting/input.py
+++ b/examples/iterative_source_reweighting/input.py
@@ -22,13 +22,13 @@
     name="Left source",
     z=[1.0, 2.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
 )
 source_right = mcdc.Source(
     name="Right source",
     z=[8.0, 9.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
 )
 simulation.set_sources([source_left, source_right])
 
diff --git a/examples/kobayashi-TD/input.py b/examples/kobayashi-TD/input.py
index 034b2b436..6fb8c5e30 100644
--- a/examples/kobayashi-TD/input.py
+++ b/examples/kobayashi-TD/input.py
@@ -55,7 +55,7 @@
     y=[0.0, 10.0],
     z=[0.0, 10.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
     time=[0.0, 50.0],
 )
 simulation.set_sources([source])
diff --git a/examples/kobayashi/input.py b/examples/kobayashi/input.py
index 9ebb08afe..524aef46e 100644
--- a/examples/kobayashi/input.py
+++ b/examples/kobayashi/input.py
@@ -53,7 +53,7 @@
     y=[0.0, 10.0],
     z=[0.0, 10.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
 )
 simulation.set_sources([source])
 
diff --git a/examples/moving_pellet/input.py b/examples/moving_pellet/input.py
index 677d89973..aa1fce45b 100644
--- a/examples/moving_pellet/input.py
+++ b/examples/moving_pellet/input.py
@@ -57,7 +57,7 @@
     y=[-0.5, 0.5],
     z=[-0.5, 0.5],
     isotropic=True,
-    energy_group=0,
+    group=0,
     time=[0.0, 9.0],
 )
 simulation.set_sources([source])
diff --git a/examples/moving_source/input.py b/examples/moving_source/input.py
index a013a036f..196395068 100644
--- a/examples/moving_source/input.py
+++ b/examples/moving_source/input.py
@@ -37,7 +37,7 @@
     z=[-0.5, 0.5],
     direction=[1.0, 1.0, 0.0],
     polar_cosine=[-1.0, -0.9],
-    energy_group=0,
+    group=0,
     time=[0.0, 10.0],
 )
 src.move(
diff --git a/examples/slab_shielding/input.py b/examples/slab_shielding/input.py
index 43a25beb2..af98b89fa 100644
--- a/examples/slab_shielding/input.py
+++ b/examples/slab_shielding/input.py
@@ -33,7 +33,7 @@
 source = mcdc.Source(
     z=[0.0, 2.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
 )
 simulation.set_sources([source])
 
diff --git a/examples/sphere_in_cube/input.py b/examples/sphere_in_cube/input.py
index 8c0be2619..9729aea9d 100644
--- a/examples/sphere_in_cube/input.py
+++ b/examples/sphere_in_cube/input.py
@@ -37,7 +37,7 @@
     y=[0.0, 4.0],
     z=[0.0, 4.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
     time=[0.0, 50.0],
 )
 simulation.set_sources([source])

From 3754680954e7992d548a2692f0db7ab80ca9688d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 22:51:29 +0700
Subject: [PATCH 130/202] update regression tests

---
 test/regression/azurv1/input.py                   | 2 +-
 test/regression/azurv1_census/input.py            | 2 +-
 test/regression/azurv1_census_tally/input.py      | 2 +-
 test/regression/c5g7_2d_k_eigenvalue/input.py     | 2 +-
 test/regression/cooper2/input.py                  | 2 +-
 test/regression/fuel_array_packaged/input.py      | 2 +-
 test/regression/inf_shem361/input.py              | 4 ++--
 test/regression/inf_shem361_k_eigenvalue/input.py | 4 ++--
 test/regression/inf_shem361_td/input.py           | 4 ++--
 test/regression/inf_shem361_td_census/input.py    | 4 ++--
 test/regression/kobayashi3-TD/input.py            | 2 +-
 test/regression/kornreich/input.py                | 2 +-
 test/regression/moving_pellet/input.py            | 2 +-
 test/regression/moving_source/input.py            | 2 +-
 test/regression/slab_absorbium/input.py           | 2 +-
 test/regression/slab_isobeam_td/input.py          | 2 +-
 test/regression/slab_isobeam_td_census/input.py   | 2 +-
 test/regression/slab_reed/input.py                | 4 ++--
 test/regression/sphere_in_cube/input.py           | 2 +-
 19 files changed, 24 insertions(+), 24 deletions(-)

diff --git a/test/regression/azurv1/input.py b/test/regression/azurv1/input.py
index dd9f21ac8..09efc5ea1 100644
--- a/test/regression/azurv1/input.py
+++ b/test/regression/azurv1/input.py
@@ -37,7 +37,7 @@
 source = mcdc.Source(
     position=[0.0, 0.0, 0.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
     time=0.0,
 )
 simulation.set_sources([source])
diff --git a/test/regression/azurv1_census/input.py b/test/regression/azurv1_census/input.py
index 553230e3a..f55ad04aa 100644
--- a/test/regression/azurv1_census/input.py
+++ b/test/regression/azurv1_census/input.py
@@ -35,7 +35,7 @@
 source = mcdc.Source(
     position=[0.0, 0.0, 0.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
     time=0.0,
 )
 simulation.set_sources([source])
diff --git a/test/regression/azurv1_census_tally/input.py b/test/regression/azurv1_census_tally/input.py
index 413e78a3a..e3c19587b 100644
--- a/test/regression/azurv1_census_tally/input.py
+++ b/test/regression/azurv1_census_tally/input.py
@@ -35,7 +35,7 @@
 source = mcdc.Source(
     position=[0.0, 0.0, 0.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
     time=0.0,
 )
 simulation.set_sources([source])
diff --git a/test/regression/c5g7_2d_k_eigenvalue/input.py b/test/regression/c5g7_2d_k_eigenvalue/input.py
index d56395f36..885b649c5 100644
--- a/test/regression/c5g7_2d_k_eigenvalue/input.py
+++ b/test/regression/c5g7_2d_k_eigenvalue/input.py
@@ -180,7 +180,7 @@ def set_mat(mat):
     x=[0.0, pitch * 17 * 2],
     y=[-pitch * 17 * 2, 0.0],
     isotropic=True,
-    energy_group=6,
+    group=6,
 )
 simulation.set_sources([source])
 
diff --git a/test/regression/cooper2/input.py b/test/regression/cooper2/input.py
index bb932fede..6d8c0afed 100644
--- a/test/regression/cooper2/input.py
+++ b/test/regression/cooper2/input.py
@@ -45,7 +45,7 @@
     x=[0.0, 1.0],
     y=[0.0, 1.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
     time=0.0,
 )
 simulation.set_sources([source])
diff --git a/test/regression/fuel_array_packaged/input.py b/test/regression/fuel_array_packaged/input.py
index 54618e733..c1065abf1 100644
--- a/test/regression/fuel_array_packaged/input.py
+++ b/test/regression/fuel_array_packaged/input.py
@@ -78,7 +78,7 @@
 # Set source
 # ======================================================================================
 
-source = mcdc.Source(x=[-0.1, 0.1], isotropic=True, energy_group=0)
+source = mcdc.Source(x=[-0.1, 0.1], isotropic=True, group=0)
 simulation.set_sources([source])
 
 # ======================================================================================
diff --git a/test/regression/inf_shem361/input.py b/test/regression/inf_shem361/input.py
index 93643a317..ab17cc273 100644
--- a/test/regression/inf_shem361/input.py
+++ b/test/regression/inf_shem361/input.py
@@ -46,7 +46,7 @@
 # ======================================================================================
 
 source = mcdc.Source(
-    position=(0.0, 0.0, 0.0), isotropic=True, energy_group=np.array([[360], [1.0]])
+    position=(0.0, 0.0, 0.0), isotropic=True, group=np.array([[360], [1.0]])
 )
 simulation.set_sources([source])
 
@@ -55,7 +55,7 @@
 # ======================================================================================
 
 # Tallies
-tally = mcdc.Tally(scores=["flux"], energy="all_groups")
+tally = mcdc.Tally(scores=["flux"], group="all")
 simulation.set_tallies([tally])
 
 # Settings
diff --git a/test/regression/inf_shem361_k_eigenvalue/input.py b/test/regression/inf_shem361_k_eigenvalue/input.py
index b49805149..98025240e 100644
--- a/test/regression/inf_shem361_k_eigenvalue/input.py
+++ b/test/regression/inf_shem361_k_eigenvalue/input.py
@@ -45,7 +45,7 @@
 # =============================================================================
 
 source = mcdc.Source(
-    position=(0.0, 0.0, 0.0), isotropic=True, energy_group=np.array([[360], [1.0]])
+    position=(0.0, 0.0, 0.0), isotropic=True, group=np.array([[360], [1.0]])
 )
 simulation.set_sources([source])
 
@@ -54,7 +54,7 @@
 # =============================================================================
 
 # Tallies
-tally = mcdc.Tally(scores=["flux"], energy="all_groups")
+tally = mcdc.Tally(scores=["flux"], group="all")
 simulation.set_tallies([tally])
 
 # Settings
diff --git a/test/regression/inf_shem361_td/input.py b/test/regression/inf_shem361_td/input.py
index 8cb10c049..dedb1b214 100644
--- a/test/regression/inf_shem361_td/input.py
+++ b/test/regression/inf_shem361_td/input.py
@@ -48,7 +48,7 @@
 # ======================================================================================
 
 source = mcdc.Source(
-    position=(0.0, 0.0, 0.0), isotropic=True, energy_group=np.array([[360], [1.0]])
+    position=(0.0, 0.0, 0.0), isotropic=True, group=np.array([[360], [1.0]])
 )
 simulation.set_sources([source])
 
@@ -60,7 +60,7 @@
 tally = mcdc.Tally(
     scores=["flux"],
     time=np.insert(np.logspace(-8, 1, 100), 0, 0.0),
-    energy="all_groups",
+    group="all",
 )
 simulation.set_tallies([tally])
 
diff --git a/test/regression/inf_shem361_td_census/input.py b/test/regression/inf_shem361_td_census/input.py
index 04be93aa7..5a1d49b32 100644
--- a/test/regression/inf_shem361_td_census/input.py
+++ b/test/regression/inf_shem361_td_census/input.py
@@ -48,7 +48,7 @@
 # ======================================================================================
 
 source = mcdc.Source(
-    position=(0.0, 0.0, 0.0), isotropic=True, energy_group=np.array([[360], [1.0]])
+    position=(0.0, 0.0, 0.0), isotropic=True, group=np.array([[360], [1.0]])
 )
 simulation.set_sources([source])
 
@@ -60,7 +60,7 @@
 tally = mcdc.Tally(
     scores=["flux"],
     time=np.insert(np.logspace(-8, 1, 100), 0, 0.0),
-    energy="all_groups",
+    group="all",
 )
 simulation.set_tallies([tally])
 
diff --git a/test/regression/kobayashi3-TD/input.py b/test/regression/kobayashi3-TD/input.py
index 6766f563a..607d66a43 100644
--- a/test/regression/kobayashi3-TD/input.py
+++ b/test/regression/kobayashi3-TD/input.py
@@ -56,7 +56,7 @@
     y=[0.0, 10.0],
     z=[0.0, 10.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
     time=[0.0, 50.0],
 )
 simulation.set_sources([source])
diff --git a/test/regression/kornreich/input.py b/test/regression/kornreich/input.py
index 2a9962a2f..2d0841fc0 100644
--- a/test/regression/kornreich/input.py
+++ b/test/regression/kornreich/input.py
@@ -38,7 +38,7 @@
 # Set source
 # ======================================================================================
 
-source = mcdc.Source(x=[0.0, 2.5], isotropic=True, energy_group=0)
+source = mcdc.Source(x=[0.0, 2.5], isotropic=True, group=0)
 simulation.set_sources([source])
 
 # ======================================================================================
diff --git a/test/regression/moving_pellet/input.py b/test/regression/moving_pellet/input.py
index ab45b832d..7628e4253 100644
--- a/test/regression/moving_pellet/input.py
+++ b/test/regression/moving_pellet/input.py
@@ -58,7 +58,7 @@
     y=[-0.5, 0.5],
     z=[-0.5, 0.5],
     isotropic=True,
-    energy_group=0,
+    group=0,
     time=[0.0, 9.0],
 )
 simulation.set_sources([source])
diff --git a/test/regression/moving_source/input.py b/test/regression/moving_source/input.py
index 8de23c47b..20099cd48 100644
--- a/test/regression/moving_source/input.py
+++ b/test/regression/moving_source/input.py
@@ -38,7 +38,7 @@
     z=[-0.5, 0.5],
     direction=[1.0, 1.0, 0.0],
     polar_cosine=[-1.0, -0.9],
-    energy_group=0,
+    group=0,
     time=[0.0, 10.0],
 )
 src.move([[1.0, 0.0, 0.0], [-0.5, 2.0, 0.0], [0.0, -3.0, 0.0]], [7.0, 2.0, 1.0])
diff --git a/test/regression/slab_absorbium/input.py b/test/regression/slab_absorbium/input.py
index fb94599e8..39e12a0de 100644
--- a/test/regression/slab_absorbium/input.py
+++ b/test/regression/slab_absorbium/input.py
@@ -31,7 +31,7 @@
 # ======================================================================================
 # Uniform isotropic source throughout the domain
 
-source = mcdc.Source(z=[0.0, 6.0], isotropic=True, energy_group=0)
+source = mcdc.Source(z=[0.0, 6.0], isotropic=True, group=0)
 simulation.set_sources([source])
 
 # ======================================================================================
diff --git a/test/regression/slab_isobeam_td/input.py b/test/regression/slab_isobeam_td/input.py
index 0ae8c2091..7eec22bd8 100644
--- a/test/regression/slab_isobeam_td/input.py
+++ b/test/regression/slab_isobeam_td/input.py
@@ -29,7 +29,7 @@
 source = mcdc.Source(
     position=(0.0, 0.0, 0.0),
     white_direction=(1.0, 0.0, 0.0),
-    energy_group=0,
+    group=0,
     time=[0.0, 5.0],
 )
 simulation.set_sources([source])
diff --git a/test/regression/slab_isobeam_td_census/input.py b/test/regression/slab_isobeam_td_census/input.py
index 382d1f083..27915511a 100644
--- a/test/regression/slab_isobeam_td_census/input.py
+++ b/test/regression/slab_isobeam_td_census/input.py
@@ -29,7 +29,7 @@
 source = mcdc.Source(
     position=(1e-10, 0.0, 0.0),
     white_direction=(1.0, 0.0, 0.0),
-    energy_group=0,
+    group=0,
     time=[0.0, 5.0],
 )
 simulation.set_sources([source])
diff --git a/test/regression/slab_reed/input.py b/test/regression/slab_reed/input.py
index 8b1c19711..9d8362d49 100644
--- a/test/regression/slab_reed/input.py
+++ b/test/regression/slab_reed/input.py
@@ -35,11 +35,11 @@
 # ======================================================================================
 
 # Isotropic source in the absorbing medium
-source_1 = mcdc.Source(z=[0.0, 2.0], isotropic=True, energy_group=0, probability=50.0)
+source_1 = mcdc.Source(z=[0.0, 2.0], isotropic=True, group=0, probability=50.0)
 
 # Isotropic source in the first half of the outermost medium,
 # with 1/100 strength
-source_2 = mcdc.Source(z=[5.0, 6.0], isotropic=True, energy_group=0, probability=0.5)
+source_2 = mcdc.Source(z=[5.0, 6.0], isotropic=True, group=0, probability=0.5)
 simulation.set_sources([source_1, source_2])
 
 # ======================================================================================
diff --git a/test/regression/sphere_in_cube/input.py b/test/regression/sphere_in_cube/input.py
index a8897ae8d..1bf38e1bb 100644
--- a/test/regression/sphere_in_cube/input.py
+++ b/test/regression/sphere_in_cube/input.py
@@ -41,7 +41,7 @@
     y=[0.0, 4.0],
     z=[0.0, 4.0],
     isotropic=True,
-    energy_group=0,
+    group=0,
     time=[0.0, 50.0],
 )
 simulation.set_sources([source])

From 2233841a4014aa78679b36279ec24db3671cad56 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 22:51:59 +0700
Subject: [PATCH 131/202] update unit tests

---
 test/unit/conftest.py                      |  3 +-
 test/unit/tally/conftest.py                |  4 +--
 test/unit/tally/test_collision_tally.py    |  1 +
 test/unit/tally/test_tally_factory.py      | 11 ++++---
 test/unit/tally/test_tracklength_tally.py  |  1 +
 test/unit/technique/test_weight_windows.py |  1 -
 test/unit/test_config.py                   |  1 +
 test/unit/test_material.py                 | 27 +++++++++++++++
 test/unit/test_object_compilation.py       | 16 +++++++++
 test/unit/test_print.py                    | 14 ++++++++
 test/unit/test_source.py                   | 38 +++++++++++++++-------
 test/unit/test_transport_model_data.py     | 11 ++++++-
 12 files changed, 107 insertions(+), 21 deletions(-)

diff --git a/test/unit/conftest.py b/test/unit/conftest.py
index d46e2d639..adbd9ed61 100644
--- a/test/unit/conftest.py
+++ b/test/unit/conftest.py
@@ -9,6 +9,7 @@
 def prepare_simulation():
     """Compile and pack an explicit simulation for kernel-level unit tests."""
     from mcdc.main import prepare
+    from mcdc.object_.cell import Cell
     from mcdc.object_.simulation import Simulation
 
     def _prepare(
@@ -20,7 +21,7 @@ def _prepare(
         configure=None,
     ):
         simulation = Simulation()
-        simulation.set_model(cells)
+        simulation.set_model(cells or (Cell(),))
         simulation.set_tallies(tallies)
         simulation.set_sources(sources)
         if configure is not None:
diff --git a/test/unit/tally/conftest.py b/test/unit/tally/conftest.py
index 40267b03f..8bc2cf117 100644
--- a/test/unit/tally/conftest.py
+++ b/test/unit/tally/conftest.py
@@ -22,7 +22,7 @@ def _particle(surface_ID, x, ux, cell_ID=-1, w=2.0):
         particle["surface_ID"] = surface_ID
         particle["cell_ID"] = cell_ID
         particle["material_ID"] = 0
-        particle["g"] = 0
+        particle["group"] = 0
         particle["x"] = x
         particle["y"] = 0.0
         particle["z"] = 0.0
@@ -80,7 +80,7 @@ def surface_crossing_tally_context(slab_plane_x, prepare_simulation):
     particle = particle_container[0]
     particle["particle_type"] = PARTICLE_NEUTRON
     particle["material_ID"] = 0
-    particle["g"] = 0
+    particle["group"] = 0
     particle["x"] = 0.0
     particle["y"] = 0.0
     particle["z"] = 0.0
diff --git a/test/unit/tally/test_collision_tally.py b/test/unit/tally/test_collision_tally.py
index 265565d01..2e5b53a6b 100644
--- a/test/unit/tally/test_collision_tally.py
+++ b/test/unit/tally/test_collision_tally.py
@@ -11,6 +11,7 @@ def test_collision_tally_with_mesh_filter():
     )
     tally = mcdc.Tally(mesh=mesh, scores=["energy_deposition"])
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
     simulation.set_tallies([tally])
     simulation.compile()
 
diff --git a/test/unit/tally/test_tally_factory.py b/test/unit/tally/test_tally_factory.py
index c03f7e7ba..eb77f31ac 100644
--- a/test/unit/tally/test_tally_factory.py
+++ b/test/unit/tally/test_tally_factory.py
@@ -2,6 +2,7 @@
 import pytest
 
 import mcdc
+from mcdc.constant import PARTICLE_ANY
 
 from mcdc.object_.tally import (
     TallyCollision,
@@ -96,17 +97,19 @@ def test_tally_factory_allows_combined_supported_filters(slab_plane_x):
     assert cell_mesh_tally.mesh_filter_ID == mesh.ID
 
 
-def test_all_groups_filter_resizes_compiled_tally_bins(prepare_simulation):
+def test_all_group_filter_resizes_compiled_tally_bins(prepare_simulation):
     material = mcdc.Material.multigroup(capture=np.ones(3))
     cell = mcdc.Cell(fill=material)
-    tally = mcdc.Tally(scores=["flux"], energy="all_groups")
+    tally = mcdc.Tally(scores=["flux"], group="all")
 
     simulation_container, data = prepare_simulation(cells=[cell], tallies=[tally])
     simulation = simulation_container[0]
     tally_record = simulation["tallies"][tally.ID]
 
-    np.testing.assert_array_equal(tally.energy, [-0.5, 0.5, 1.5, 2.5])
-    assert tally.bin_shape == [1, 1, 3, 1, 1]
+    assert tally.particle_type == PARTICLE_ANY
+    np.testing.assert_array_equal(tally.group, [-0.5, 0.5, 1.5, 2.5])
+    assert tally.bin_shape == [1, 1, 3, 1, 1, 1]
+    assert tally.stride_group == 1
     assert tally.stride_energy == 1
     assert tally.stride_azi == 3
     assert tally.stride_mu == 3
diff --git a/test/unit/tally/test_tracklength_tally.py b/test/unit/tally/test_tracklength_tally.py
index 678447fee..ded758486 100644
--- a/test/unit/tally/test_tracklength_tally.py
+++ b/test/unit/tally/test_tracklength_tally.py
@@ -24,6 +24,7 @@ def test_tracklength_tally_with_mesh_filter():
     )
     tally = mcdc.Tally(mesh=mesh, scores=["flux"])
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
     simulation.set_tallies([tally])
     simulation.compile()
 
diff --git a/test/unit/technique/test_weight_windows.py b/test/unit/technique/test_weight_windows.py
index a9fdaa5d3..d9a7b3439 100644
--- a/test/unit/technique/test_weight_windows.py
+++ b/test/unit/technique/test_weight_windows.py
@@ -200,7 +200,6 @@ def test_query_weight_window(prepare_simulation):
 
     program, data = make_ww_model_distinct(prepare_simulation)
     simulation = util.access_simulation(program)
-    simulation["settings"]["neutron_multigroup_mode"] = False
     # hardcode mesh params
     pitch, height, N = 2.0, 10.0, 3
     nx, ny, nz = N, N, N
diff --git a/test/unit/test_config.py b/test/unit/test_config.py
index de10e2abb..210d81150 100644
--- a/test/unit/test_config.py
+++ b/test/unit/test_config.py
@@ -6,6 +6,7 @@
 
 def test_compilation_applies_command_line_overrides(monkeypatch):
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
     monkeypatch.setattr(config, "target", "cpu")
     monkeypatch.setattr(config.args, "N_particle", 100)
     monkeypatch.setattr(config.args, "N_batch", None)
diff --git a/test/unit/test_material.py b/test/unit/test_material.py
index 0915117b4..698b889c3 100644
--- a/test/unit/test_material.py
+++ b/test/unit/test_material.py
@@ -68,6 +68,24 @@ def test_material_accepts_native_multigroup_and_hybrid_data():
             {"neutron_multigroup": object()},
             "neutron_multigroup must be a NeutronMultigroupData object",
         ),
+        (
+            {"neutron_multigroup": mcdc.NeutronMultigroupData()},
+            "must define at least one energy group",
+        ),
+        (
+            {
+                "nuclide_composition": {"H1": 0.1},
+                "neutron_multigroup": mcdc.NeutronMultigroupData(capture=[0.2]),
+            },
+            "requires an explicit neutron multigroup energy_grid",
+        ),
+        (
+            {
+                "element_composition": {"H": 0.1},
+                "neutron_multigroup": mcdc.NeutronMultigroupData(capture=[0.2]),
+            },
+            "requires an explicit neutron multigroup energy_grid",
+        ),
     ],
 )
 def test_material_rejects_invalid_representations(kwargs, expected_message, capsys):
@@ -86,6 +104,7 @@ def compile_nuclide(nuclide, simulation):
     monkeypatch.setattr(Nuclide, "_compile_into_simulation", compile_nuclide)
 
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
     simulation.compile()
     material = Material(nuclide_composition={"H1": 0.1})
 
@@ -103,6 +122,7 @@ def test_shared_mg_is_registered_once_for_multiple_materials():
     material_a = Material(neutron_multigroup=neutron_multigroup)
     material_b = Material(neutron_multigroup=neutron_multigroup)
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
     simulation.compile()
 
     material_a._compile_into_simulation(simulation)
@@ -131,3 +151,10 @@ def test_material_mg_reference_is_packed(prepare_simulation):
     assert packed["neutron_multigroup_ID"] == 1
     assert packed_cell["fill_type"] == FILL_MATERIAL
     assert packed_cell["fill_ID"] == 0
+
+
+def test_multigroup_factory_rejects_zero_group_data(capsys):
+    with pytest.raises(SystemExit):
+        Material.multigroup()
+
+    assert "must define at least one energy group" in capsys.readouterr().out
diff --git a/test/unit/test_object_compilation.py b/test/unit/test_object_compilation.py
index b6ed8de5c..fe3cea66b 100644
--- a/test/unit/test_object_compilation.py
+++ b/test/unit/test_object_compilation.py
@@ -34,6 +34,7 @@ def __init__(self):
 
 def test_simulation_reserves_zero_group_mg_as_id_zero():
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
 
     assert isinstance(simulation.technique, Technique)
 
@@ -84,6 +85,7 @@ def test_mcdc_object_compiles_object_members_and_lists():
     ignored = DataPolynomial(np.array([4.0]))
     simulation = mcdc.Simulation()
     simulation.root_universe = ObjectOwner(child, children, ignored)
+    simulation.root_universe.cells = [mcdc.Cell()]
 
     simulation.compile()
 
@@ -95,6 +97,7 @@ def test_simulation_compiles_objects_owned_by_embedded_configuration():
     mesh = mcdc.MeshUniform()
     weight_windows = np.ones((1, 1, 1, 1, 3))
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
     simulation.technique.weight_windows(weight_windows, mesh=mesh)
 
     simulation.compile()
@@ -110,6 +113,7 @@ def test_embedded_compile_id_prevents_cycles_and_supports_recompilation():
     configuration_a.member = configuration_b
     configuration_b.member = configuration_a
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
     simulation.configuration = configuration_a
 
     simulation.compile()
@@ -136,6 +140,7 @@ def compile_nuclide(nuclide, simulation):
     material_a = mcdc.Material(nuclide_composition={"U235": 1.0})
     material_b = mcdc.Material(nuclide_composition={"U235": 2.0})
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
     simulation.compile()
 
     material_a._compile_into_simulation(simulation)
@@ -152,6 +157,7 @@ def test_simulation_compilation_finalizes_model_wide_state():
     source_a = mcdc.Source(probability=1.0)
     source_b = mcdc.Source(probability=3.0)
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
     simulation.set_sources([source_a, source_b])
     simulation.settings.neutron_eigenvalue_mode = True
     simulation.settings.N_inactive = 2
@@ -169,6 +175,7 @@ def test_simulation_compilation_finalizes_model_wide_state():
 
 def test_simulation_compilation_sets_particle_bank_capacities():
     simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell()])
     simulation.settings.N_particle = 100
     simulation.settings.N_census = 2
     simulation.settings.active_bank_buffer = 11
@@ -183,3 +190,12 @@ def test_simulation_compilation_sets_particle_bank_capacities():
     assert simulation.bank_census.size[0] == 2 * N_work
     assert simulation.bank_source.size[0] == 3 * N_work
     assert simulation.bank_future.size[0] == 4 * N_work
+
+
+def test_simulation_rejects_an_empty_root_universe(capsys):
+    simulation = mcdc.Simulation()
+
+    with pytest.raises(SystemExit):
+        simulation.compile()
+
+    assert "root universe is empty" in capsys.readouterr().out
diff --git a/test/unit/test_print.py b/test/unit/test_print.py
index 5fdad9cb5..3b50de23d 100644
--- a/test/unit/test_print.py
+++ b/test/unit/test_print.py
@@ -10,6 +10,20 @@ def test_print_1d_array():
     assert print_module.print_1d_array(np.arange(6.0)) == "(size=6): [0, 1, ..., 4, 5]"
 
 
+def test_print_bank_uses_runtime_particle_data(capsys):
+    bank = {
+        "size": np.array([1]),
+        "tag": "source",
+        "particle_data": np.array([1.0, 2.0]),
+    }
+
+    print_module.print_bank(bank, show_content=True)
+
+    output = capsys.readouterr().out
+    assert "size : 1 of 2" in output
+    assert "1.0" in output
+
+
 @pytest.mark.parametrize(
     ("duration", "expected"),
     [
diff --git a/test/unit/test_source.py b/test/unit/test_source.py
index 3ffd4d4c2..59140961c 100644
--- a/test/unit/test_source.py
+++ b/test/unit/test_source.py
@@ -35,27 +35,41 @@ def test_energy_distribution(energy):
     np.testing.assert_array_equal(source.energy_pdf.pdf.x, [9_999.0, 10_001.0])
 
 
-@pytest.mark.parametrize("energy_group", [3, np.int64(3)])
-def test_scalar_energy_group(energy_group):
-    source = mcdc.Source(energy_group=energy_group)
+@pytest.mark.parametrize("group", [3, np.int64(3)])
+def test_scalar_group(group):
+    source = mcdc.Source(group=group)
 
-    assert source.mono_energetic
-    assert source.energy_group == 3
+    assert source.mono_group
+    assert source.group == 3
 
 
 @pytest.mark.parametrize(
-    "energy_group",
+    "group",
     [
         [[1, 3], [0.25, 0.75]],
         ([1, 3], [0.25, 0.75]),
         np.array([[1, 3], [0.25, 0.75]]),
     ],
 )
-def test_energy_group_distribution(energy_group):
-    source = mcdc.Source(energy_group=energy_group)
+def test_group_distribution(group):
+    source = mcdc.Source(group=group)
 
-    assert not source.mono_energetic
-    np.testing.assert_array_equal(source.energy_group_pmf.value, [1, 3])
+    assert not source.mono_group
+    np.testing.assert_array_equal(source.group_pmf.value, [1, 3])
+
+
+def test_group_distribution_rejects_noninteger_values(capsys):
+    with pytest.raises(SystemExit):
+        mcdc.Source(group=[[1.5, 3.0], [0.25, 0.75]])
+
+    assert "Group distribution values must be integers" in capsys.readouterr().out
+
+
+def test_energy_and_group_are_stored_independently():
+    source = mcdc.Source(energy=10_000.0, group=3)
+
+    assert source.energy == 10_000.0
+    assert source.group == 3
 
 
 @pytest.mark.parametrize("time", [2, 2.0, np.int64(2), np.float64(2.0)])
@@ -86,8 +100,8 @@ def test_time_interval(time):
     [
         ({"energy": [1.0, 2.0, 3.0]}, "Energy distribution must have shape (2, N)"),
         (
-            {"energy_group": [1, 2, 3]},
-            "Energy-group distribution must have shape (2, N)",
+            {"group": [1, 2, 3]},
+            "Group distribution must have shape (2, N)",
         ),
         ({"time": [1.0, 2.0, 3.0]}, "Source time interval must have shape (2,)"),
     ],
diff --git a/test/unit/test_transport_model_data.py b/test/unit/test_transport_model_data.py
index 6b8ea1193..2c20fe6da 100644
--- a/test/unit/test_transport_model_data.py
+++ b/test/unit/test_transport_model_data.py
@@ -31,6 +31,8 @@ def test_zero_group_placeholder():
     assert (
         neutron_multigroup.energy_representation == NEUTRON_MULTIGROUP_ENERGY_MIDPOINT
     )
+    assert neutron_multigroup._uses_default_energy_grid
+    assert "_uses_default_energy_grid" in neutron_multigroup.non_numba
 
     np.testing.assert_array_equal(neutron_multigroup.energy_grid, [-0.499999])
     np.testing.assert_array_equal(neutron_multigroup.speed, [])
@@ -165,7 +167,9 @@ def test_standalone_mg_registration_and_packing(prepare_simulation):
         energy_grid=[1.0e-5, 1.0, 20.0e6],
     )
 
-    simulation_container, data = prepare_simulation(objects=[neutron_multigroup])
+    simulation_container, data = prepare_simulation(
+        cells=[mcdc.Cell()], objects=[neutron_multigroup]
+    )
     simulation = simulation_container[0]
     reserved = simulation["neutron_multigroup_data"][0]
     packed = simulation["neutron_multigroup_data"][1]
@@ -218,6 +222,7 @@ def test_energy_grid_and_representation(policy, expected):
     )
 
     assert neutron_multigroup.energy_representation == expected
+    assert not neutron_multigroup._uses_default_energy_grid
     np.testing.assert_array_equal(neutron_multigroup.energy_grid, [1.0e-5, 1.0, 20.0e6])
 
 
@@ -244,6 +249,10 @@ def test_energy_grid_and_representation(policy, expected):
             {"capture": [0.1], "energy_representation": "average"},
             "Unknown NeutronMultigroupData energy representation",
         ),
+        (
+            {"capture": [0.1], "energy_representation": "uniform"},
+            "requires an explicit energy_grid",
+        ),
         (
             {"fission": [0.1]},
             "NeutronMultigroupData fission data requires nu_p or nu_d",

From d4b6e0f950f7b1118d05236ff643d7e1e998ec87 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 23:47:55 +0700
Subject: [PATCH 132/202] update api docs

---
 docs/source/_ext/simulation_members.py     | 11 +++++++----
 docs/source/reference/python_api/index.rst |  9 +++++----
 mcdc/object_/cell.py                       |  2 +-
 mcdc/object_/material.py                   |  2 +-
 mcdc/object_/mesh.py                       |  4 ++--
 mcdc/object_/simulation.py                 |  2 +-
 mcdc/object_/source.py                     |  2 +-
 mcdc/object_/surface.py                    |  2 +-
 mcdc/object_/tally.py                      |  2 +-
 mcdc/object_/transport_model_data.py       |  2 +-
 mcdc/object_/universe.py                   |  4 ++--
 11 files changed, 23 insertions(+), 19 deletions(-)

diff --git a/docs/source/_ext/simulation_members.py b/docs/source/_ext/simulation_members.py
index abedab80c..53ca807f8 100644
--- a/docs/source/_ext/simulation_members.py
+++ b/docs/source/_ext/simulation_members.py
@@ -15,6 +15,7 @@
 from mcdc.object_.technique import (
     GlobalWeightRoulette,
     ImplicitCapture,
+    NeutronMultigroupTechnique,
     PopulationControl,
     WeightedEmission,
     WeightWindows,
@@ -36,11 +37,13 @@
 SETTINGS_METHODS = (
     "set_time_census",
     "set_eigenmode",
-    "set_source_file",
+    # TODO: Restore file-backed source setup after its compilation path is enabled.
+    # "set_source_file",
     "set_transported_particles",
 )
 
 TECHNIQUES = (
+    ("neutron_multigroup", NeutronMultigroupTechnique),
     ("implicit_capture", ImplicitCapture),
     ("weighted_emission", WeightedEmission),
     ("global_weight_roulette", GlobalWeightRoulette),
@@ -113,15 +116,15 @@ def run(self):
 
         for name, technique in TECHNIQUES:
             method = technique.__call__
-            public_name = f"Simulation.{name}"
+            public_name = f"Simulation.technique.{name}"
             _append_line(
                 lines,
-                f".. py:method:: {name}{_public_signature(method)}",
+                f".. py:method:: technique.{name}{_public_signature(method)}",
             )
             _append_line(lines, "   :module:")
             _append_line(
                 lines,
-                f"   :canonical: mcdc.Simulation.{name}",
+                f"   :canonical: mcdc.Simulation.technique.{name}",
             )
             _append_line(lines)
             _append_content(
diff --git a/docs/source/reference/python_api/index.rst b/docs/source/reference/python_api/index.rst
index 9617e9d18..8c2edd6c6 100644
--- a/docs/source/reference/python_api/index.rst
+++ b/docs/source/reference/python_api/index.rst
@@ -44,8 +44,7 @@ Materials
 ^^^^^^^^^
 
 Materials define the interaction data used by cells. :class:`mcdc.Material`
-accepts native compositions and particle-specific transport-mode data.
-:class:`mcdc.NeutronMultigroupData` stores reduced multigroup neutron data.
+accepts native compositions and particle-specific transport-model data (e.g., neutron multigroup cross-sections).
 
 .. autosummary::
    :toctree: generated
@@ -76,7 +75,7 @@ universes, and universes and lattices organize repeated geometry.
 Sources
 ^^^^^^^
 
-Sources describe the initial particle population.
+Sources describe the distribution of the initial particle population in the simulation.
 
 .. autosummary::
    :toctree: generated
@@ -133,7 +132,9 @@ Transport techniques
 ^^^^^^^^^^^^^^^^^^^^
 
 Transport techniques are grouped under ``simulation.technique``. For example,
-enable implicit capture with ``simulation.technique.implicit_capture()``. See
+enable implicit capture with ``simulation.technique.implicit_capture()`` or
+allow material-local neutron group structures with
+``simulation.technique.neutron_multigroup(multigrid=True)``. See
 :class:`mcdc.Simulation` for the ownership model and examples.
 
 Compiling and running
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 8a598d88e..67825623f 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -96,7 +96,7 @@ def __repr__(self):
 
 
 class Cell(MCDCObject):
-    """Define a geometric region and the object that fills it.
+    """Material- or universe-filled regions of the simulation geometry.
 
     Parameters
     ----------
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index e52a6c4fb..22c78abc1 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -18,7 +18,7 @@
 
 
 class Material(MCDCObject):
-    """Define a material from native compositions and/or multigroup data.
+    """Particle-interaction properties assigned to simulation cells.
 
     Parameters
     ----------
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index 3ce0b574e..fde373205 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -48,7 +48,7 @@ def __repr__(self):
 
 
 class MeshUniform(MeshBase):
-    """Define a Cartesian mesh with uniform spacing on each axis.
+    """Uniform spatial bins for simulation tallies and transport techniques.
 
     Parameters
     ----------
@@ -134,7 +134,7 @@ def __repr__(self):
 
 
 class MeshStructured(MeshBase):
-    """Define a Cartesian mesh from explicit grid boundaries.
+    """Structured spatial bins for simulation tallies and transport techniques.
 
     Parameters
     ----------
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 97a93cc04..27aa13b88 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -43,7 +43,7 @@
 
 
 class Simulation(MCDCBase):
-    """Own a complete MC/DC model, settings, techniques, and runtime state.
+    """The complete model and configuration for one MC/DC calculation.
 
     Parameters
     ----------
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 78675fe3f..ff3caa921 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -26,7 +26,7 @@
 
 
 class Source(MCDCObject):
-    """Define a particle source.
+    """Distributions of particles introduced into the simulation.
 
     A source specifies the position, direction, energy, time, particle type,
     transport-mode group, and relative sampling probability for emitted particles.
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 261fee5b1..cf1daa671 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -41,7 +41,7 @@
 
 
 class Surface(MCDCObject):
-    """Implicit surface used to bound cells.
+    """Geometric boundaries of simulation cells.
 
     Surfaces are created with class methods such as :meth:`PlaneX`,
     :meth:`CylinderZ`, and :meth:`Sphere`. Unary ``+`` and ``-`` return the
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 43b41e585..8f29baf01 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -50,7 +50,7 @@
 
 
 class Tally(MCDCPolymorphic):
-    """Create a tally and select its estimator from the requested scores.
+    """Quantities measured during the simulation.
 
     Parameters
     ----------
diff --git a/mcdc/object_/transport_model_data.py b/mcdc/object_/transport_model_data.py
index 3c2dd57ca..a64f1a9c6 100644
--- a/mcdc/object_/transport_model_data.py
+++ b/mcdc/object_/transport_model_data.py
@@ -27,7 +27,7 @@
 
 
 class NeutronMultigroupData(MCDCObject):
-    """Store the cross-section data for multigroup neutron transport.
+    """Multigroup neutron-interaction properties assigned to a material.
 
     Materials may use ``NeutronMultigroupData`` alone for multigroup transport or
     alongside a native composition over the energy range defined by
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index c838fa8c1..bc1019712 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -24,7 +24,7 @@
 
 
 class Universe(MCDCObject):
-    """Group cells into a reusable geometry.
+    """Reusable collections of cells in the simulation geometry.
 
     Parameters
     ----------
@@ -96,7 +96,7 @@ def __repr__(self):
 
 
 class Lattice(MCDCObject):
-    """Arrange universes on a uniform Cartesian lattice.
+    """Repeated arrangements of universes in the simulation geometry.
 
     Parameters
     ----------

From 5a6d4cbbc9288793365ca2a74b71bac190ac3547 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 23:56:05 +0700
Subject: [PATCH 133/202] update dev docs

---
 .../developer_guide/extending/extending_the_object_model.rst  | 4 ++--
 .../extending/writing_numba_compatible_transport_code.rst     | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index 77ba246be..7bc882f6f 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -168,9 +168,9 @@ The layer generator interprets annotations according to the field's role:
    * - ``move_velocities: Annotated[NDArray[float64], ("N_move", 3)]``
      - Offset, length, and shape metadata plus flattened values
      - ``mcdc_get.surface.move_velocities(move, axis, surface, data)``
-   * - ``energy_group_pmf: DistributionPMF``
+   * - ``group_pmf: DistributionPMF``
      - Simulation-local object ID
-     - ``simulation["distributions"][source["energy_group_pmf_ID"]]``
+     - ``simulation["distributions"][source["group_pmf_ID"]]``
    * - ``collision_tallies: list[TallyCollision]``
      - Count and offset to IDs stored in ``data``
      - ``mcdc_get.cell.collision_tally_IDs(index, cell, data)``
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index 23ec078db..32f2827a4 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -101,10 +101,10 @@ For example, recover a prepared distribution by simulation-local ID instead of p
 .. code-block:: python
 
    # Python model construction
-   source_object.energy_group_pmf = distribution_object
+   source_object.group_pmf = distribution_object
 
    # Portable transport representation
-   distribution = simulation["distributions"][source["energy_group_pmf_ID"]]
+   distribution = simulation["distributions"][source["group_pmf_ID"]]
 
 Keep Types Stable
 ^^^^^^^^^^^^^^^^^

From 43a1c342d03c29e7757c610375c049ddbc251a84 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Thu, 6 Aug 2026 23:59:19 +0700
Subject: [PATCH 134/202] update user docs

---
 .../getting_started/first_simulation.rst      |   2 +-
 docs/source/user_guide/index.rst              |   1 +
 .../user_guide/materials_and_multigroup.rst   | 109 ++++++++++++++++++
 docs/source/user_guide/tallies.rst            |  49 +++++++-
 4 files changed, 159 insertions(+), 2 deletions(-)
 create mode 100644 docs/source/user_guide/materials_and_multigroup.rst

diff --git a/docs/source/user_guide/getting_started/first_simulation.rst b/docs/source/user_guide/getting_started/first_simulation.rst
index 7e51719c5..84e1eb7a7 100644
--- a/docs/source/user_guide/getting_started/first_simulation.rst
+++ b/docs/source/user_guide/getting_started/first_simulation.rst
@@ -153,7 +153,7 @@ first cell:
    source = mcdc.Source(
        z=[0.0, 2.0],
        isotropic=True,
-       energy_group=0,
+       group=0,
    )
    simulation.set_sources([source])
 
diff --git a/docs/source/user_guide/index.rst b/docs/source/user_guide/index.rst
index 626496cdd..a4479e4c1 100644
--- a/docs/source/user_guide/index.rst
+++ b/docs/source/user_guide/index.rst
@@ -33,6 +33,7 @@ changing selected inputs.
    :maxdepth: 1
 
    simulation_lifecycle
+   materials_and_multigroup
    iterative_simulations
    tallies
 
diff --git a/docs/source/user_guide/materials_and_multigroup.rst b/docs/source/user_guide/materials_and_multigroup.rst
new file mode 100644
index 000000000..76a85304e
--- /dev/null
+++ b/docs/source/user_guide/materials_and_multigroup.rst
@@ -0,0 +1,109 @@
+.. _user_materials_and_multigroup:
+
+========================================
+Materials and Neutron Multigroup Data
+========================================
+
+A :class:`mcdc.Material` may contain a native nuclide or element composition,
+neutron multigroup data, or both.
+
+Native Materials
+----------------
+
+Define a native material with either nuclide or element atomic densities:
+
+.. code-block:: python
+
+   fuel = mcdc.Material(
+       name="UO2",
+       nuclide_composition={
+           "U235": 5.0e-4,
+           "U238": 2.2e-2,
+           "O16": 4.5e-2,
+       },
+       temperature=293.6,
+   )
+
+Multigroup Materials
+--------------------
+
+:class:`mcdc.NeutronMultigroupData` stores macroscopic neutron cross sections,
+group speeds, fission spectra, and delayed-precursor data. For a material that
+uses only this transport model, :meth:`mcdc.Material.multigroup` is the concise
+entry point:
+
+.. code-block:: python
+
+   moderator = mcdc.Material.multigroup(
+       name="Moderator",
+       capture=np.array([0.1, 0.2]),
+       scatter=np.array([
+           [0.7, 0.1],
+           [0.2, 0.5],
+       ]),
+       energy_grid=np.array([1.0e-5, 1.0, 20.0e6]),
+   )
+
+Energy Grids and Representation
+-------------------------------
+
+An explicit ``energy_grid`` contains ``G + 1`` boundaries. Group ``g`` covers
+``energy_grid[g] <= E < energy_grid[g + 1]``. The grid both maps continuous
+energy to a group and bounds continuous energy reconstructed from a group.
+
+When no grid is supplied, MC/DC creates the group-coordinate grid
+``[1.0e-6 - 0.5, 0.5, 1.5, 2.5, ...]`` with
+``energy_representation="midpoint"``. An explicit grid also supports
+``"log_midpoint"``, ``"uniform"``, and ``"log_uniform"`` reconstruction.
+
+Hybrid Materials
+----------------
+
+A material can combine native and neutron multigroup data:
+
+.. code-block:: python
+
+   hybrid_fuel = mcdc.Material(
+       name="Hybrid fuel",
+       nuclide_composition={"U235": 5.0e-4, "U238": 2.2e-2},
+       neutron_multigroup=mcdc.NeutronMultigroupData(
+           capture=np.array([0.10]),
+           fission=np.array([0.20]),
+           nu_p=np.array([2.50]),
+           energy_grid=np.array([1.0e-5, 20.0e6]),
+       ),
+   )
+
+The explicit energy grid is required whenever a native composition and neutron
+multigroup data are combined. Its bounds identify the energy interval where
+the multigroup transport model is available.
+
+Shared and Material-local Grids
+-------------------------------
+
+Neutron multigroup datasets use one shared energy grid by default. Enable the
+multigrid option for material-local group structures:
+
+.. code-block:: python
+
+   simulation.technique.neutron_multigroup(multigrid=True)
+
+Source Energy and Group
+-----------------------
+
+A particle carries continuous ``energy`` and an integer ``group`` as separate
+state. :class:`mcdc.Source` accepts an independent continuous energy
+distribution and discrete group distribution:
+
+.. code-block:: python
+
+   source = mcdc.Source(
+       energy=1.0e6,
+       group=([0, 1], [0.25, 0.75]),
+   )
+
+``group`` is a general transport-mode state; neutron multigroup transport uses
+it as the neutron energy-group index. If both variables are supplied, the
+group takes precedence over energy only for shared-grid neutron multigroup
+transport. The tally equivalents are the separate ``group`` and ``energy``
+filters described in :doc:`tallies`.
diff --git a/docs/source/user_guide/tallies.rst b/docs/source/user_guide/tallies.rst
index d8dd20bcc..c08edd92c 100644
--- a/docs/source/user_guide/tallies.rst
+++ b/docs/source/user_guide/tallies.rst
@@ -13,11 +13,58 @@ snippets assume NumPy has been imported as ``np``.
 Each tally combines:
 
 - one or more scores, such as flux, collision rate, or current;
-- optional spatial, angular, energy, time, surface, or cell filters; and
+- optional particle, spatial, angular, group, energy, time, surface, or cell
+  filters; and
 - a name used to identify the tally in the output file.
 
 Only tallies passed to ``simulation.set_tallies(...)`` are scored.
 
+Particle, Group, and Energy Filters
+-----------------------------------
+
+The ``particle_type``, ``group``, and ``energy`` filters are independent. If
+``particle_type`` is omitted, a tally accepts any transported particle type.
+Set it explicitly when one tally should score only neutrons, electrons, or
+protons:
+
+.. code-block:: python3
+
+   neutron_flux = mcdc.Tally(
+       name="neutron_flux",
+       scores=["flux"],
+       particle_type="neutron",
+       energy=[0.0, 1.0e6, 20.0e6],
+   )
+
+``energy`` contains continuous-energy bin boundaries in eV. ``group`` contains
+boundaries for the independent integer group state used by a transport mode.
+For neutron multigroup transport, the group state is the neutron energy-group
+index; tally boundaries can coarsen several transport groups into one bin:
+
+.. code-block:: python3
+
+   collapsed_group_flux = mcdc.Tally(
+       name="collapsed_group_flux",
+       scores=["flux"],
+       particle_type="neutron",
+       group=[-0.5, 1.5, 3.5],
+   )
+
+Use ``group="all"`` to create one tally bin per neutron energy group during
+simulation compilation:
+
+.. code-block:: python3
+
+   group_flux = mcdc.Tally(
+       name="group_flux",
+       scores=["flux"],
+       group="all",
+   )
+
+The ``"all"`` shortcut supports neutron groups when every material contains
+neutron multigroup data on one shared energy grid. ``particle_type`` may be
+omitted or set to ``"neutron"``.
+
 Mesh Tallies
 ------------
 

From 90ed629663f5f9699e232f0af83a79f2740eac4e Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 03:48:42 +0700
Subject: [PATCH 135/202] Update mcdc/code_factory/numba_objects_generator.py

Co-authored-by: Nathan Glaser <123763273+nglaser3@users.noreply.github.com>
---
 mcdc/code_factory/numba_objects_generator.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/mcdc/code_factory/numba_objects_generator.py b/mcdc/code_factory/numba_objects_generator.py
index 3702421fc..b38d0870f 100644
--- a/mcdc/code_factory/numba_objects_generator.py
+++ b/mcdc/code_factory/numba_objects_generator.py
@@ -26,7 +26,7 @@
 )
 from mcdc.object_.particle import Particle, ParticleBank, ParticleData
 from mcdc.object_.tally import Tally
-from mcdc.print_ import print_error, print_structure
+from mcdc.print_ import print_error
 from mcdc.util import flatten
 
 type_map = {

From 0d8cd1b96ff3bcb785b440bd7e243cd78cb589dd Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 04:04:36 +0700
Subject: [PATCH 136/202] update docstrings for Simulation.set_*

---
 mcdc/object_/simulation.py | 11 ++++++++---
 1 file changed, 8 insertions(+), 3 deletions(-)

diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 051e431af..f4433f42c 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -300,7 +300,12 @@ def _reset_model(self) -> None:
     # ==================================================================================
 
     def set_model(self, cells: Sequence[Cell]) -> None:
-        """Set the cells in the root universe and invalidate compiled state.
+        """Set the root cells that define a complete model (geometry and materials) of
+        the simulation.
+
+        Pass only cells that belong directly to the root universe. Do not include
+        cells nested inside subuniverses; they are discovered automatically during
+        model traversal as long as they are reachable through the root cells.
 
         Parameters
         ----------
@@ -317,7 +322,7 @@ def set_model(self, cells: Sequence[Cell]) -> None:
         self.compiled = False
 
     def set_sources(self, sources: Sequence[Source]) -> None:
-        """Set particle sources and invalidate compiled state.
+        """Set particle sources for the simulation.
 
         Parameters
         ----------
@@ -334,7 +339,7 @@ def set_sources(self, sources: Sequence[Source]) -> None:
         self.compiled = False
 
     def set_tallies(self, tallies: Sequence[Tally]) -> None:
-        """Set requested tallies and invalidate compiled state.
+        """Set requested tallies for the simulation.
 
         Parameters
         ----------

From e5baad1b3095e3942da409cf40d993d95b567c92 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 04:15:41 +0700
Subject: [PATCH 137/202] specify the returned boolean in
 _compile_into_simulation

---
 mcdc/object_/base.py | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index ca50a6ef2..c3c359458 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -36,6 +36,13 @@ def _compile_into_simulation(self, simulation) -> bool:
         Embedded ``MCDCBase`` objects participate in compilation without being
         registered in a simulation object collection. Registered
         :class:`MCDCObject` subclasses extend this lifecycle with an object ID.
+
+        Returns
+        -------
+        bool
+            ``True`` if the object was compiled for the current simulation
+            compilation, or ``False`` if it had already been compiled and was
+            skipped.
         """
         # Compile each embedded object once per simulation compilation
         if self.compile_ID == simulation.compile_ID:

From 47ea2d006b833d8c9b3ec41883d5c6cdc652ba03 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 04:19:05 +0700
Subject: [PATCH 138/202] specify else behavior in member value compilation

---
 mcdc/object_/base.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index c3c359458..808d868c5 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -83,6 +83,10 @@ def _compile_member_value(value, simulation) -> None:
             for item in value:
                 MCDCBase._compile_member_value(item, simulation)
 
+        # Scalar, array, and other non-object members require no compilation.
+        else:
+            return
+
 
 class MCDCObject(MCDCBase):
     """Base class for model objects registered during simulation compilation.

From 50230fc5278fc2e11feaa72625f4ece3cbbe3c21 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 04:23:12 +0700
Subject: [PATCH 139/202] Update mcdc/object_/base.py

Co-authored-by: Nathan Glaser <123763273+nglaser3@users.noreply.github.com>
---
 mcdc/object_/base.py | 6 +-----
 1 file changed, 1 insertion(+), 5 deletions(-)

diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index 808d868c5..e7266c4f3 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -71,11 +71,7 @@ def _compile_members_into_simulation(self, simulation) -> None:
     @staticmethod
     def _compile_member_value(value, simulation) -> None:
         # Register direct object members
-        if isinstance(value, MCDCObject):
-            value._compile_into_simulation(simulation)
-
-        # Compile embedded configuration objects
-        elif isinstance(value, MCDCBase):
+        if isinstance(value, MCDCBase):
             value._compile_into_simulation(simulation)
 
         # Compile object members stored in lists

From 37b10b25495c9f21411e8838d8c52fc8fe0446d9 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 04:29:08 +0700
Subject: [PATCH 140/202] update CHANGELOG

---
 CHANGELOG.md | 9 +++------
 1 file changed, 3 insertions(+), 6 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 17ec3adcd..06e7b6ab9 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -11,12 +11,9 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/2.0.0/),
 ### Changed
 
 - Move regression tests from the custom `run.py` harness to pytest-based collection and reporting from [@massimolarsen]
-- **Breaking:** Redesign model construction around explicit `mcdc.Simulation`
-  instances, replacing the global simulation, settings, run, and visualization
-  interfaces. Each simulation now owns and compiles its complete object graph,
-  handles associated input and output workflows, and can be independently
-  visualized or run. Regression problems, public API documentation, and unit
-  tests have been updated for the new workflow from [@ilhamv]
+- **Breaking:** Encapsulate MC/DC model building and execution within an explicit
+  `mcdc.Simulation` instance, replacing the global simulation state and interface
+  from [@ilhamv]
 
 ### Deprecated
 

From a2230cfc8d2831d02030eb6c4c0eb3f0b344ed1f Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 04:47:44 +0700
Subject: [PATCH 141/202] update key API class summary

---
 docs/source/reference/python_api/index.rst      | 2 +-
 docs/source/user_guide/simulation_lifecycle.rst | 4 ++++
 mcdc/object_/cell.py                            | 2 +-
 mcdc/object_/material.py                        | 4 ++--
 mcdc/object_/mesh.py                            | 4 ++--
 mcdc/object_/simulation.py                      | 2 +-
 mcdc/object_/source.py                          | 2 +-
 mcdc/object_/surface.py                         | 2 +-
 mcdc/object_/tally.py                           | 2 +-
 mcdc/object_/universe.py                        | 4 ++--
 10 files changed, 16 insertions(+), 12 deletions(-)

diff --git a/docs/source/reference/python_api/index.rst b/docs/source/reference/python_api/index.rst
index 6e1584618..269ffa002 100644
--- a/docs/source/reference/python_api/index.rst
+++ b/docs/source/reference/python_api/index.rst
@@ -76,7 +76,7 @@ universes, and universes and lattices organize repeated geometry.
 Sources
 ^^^^^^^
 
-Sources describe the initial particle population.
+Sources describe the distribution of the initial particle population in the simulation.
 
 .. autosummary::
    :toctree: generated
diff --git a/docs/source/user_guide/simulation_lifecycle.rst b/docs/source/user_guide/simulation_lifecycle.rst
index 8bcd598ac..4eba5284f 100644
--- a/docs/source/user_guide/simulation_lifecycle.rst
+++ b/docs/source/user_guide/simulation_lifecycle.rst
@@ -107,6 +107,10 @@ modify an attached object after explicitly compiling or visualizing the model,
 call ``simulation.compile()`` again before inspecting or visualizing the
 change.
 
+Compilation finalizes some user-facing values in place.
+In particular, source probabilities are normalized, tally limits may reduce ``settings.time_boundary``, and particle-bank buffer ratios may be adjusted for the selected run mode.
+Set new raw values explicitly before recompiling when an iterative workflow changes one of these inputs.
+
 4. Visualize or Run
 -------------------
 
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index a27027ac6..6fc08b13d 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -96,7 +96,7 @@ def __repr__(self):
 
 
 class Cell(MCDCObject):
-    """Define a geometric region and the object that fills it.
+    """Material- or universe-filled regions of the simulation geometry.
 
     Parameters
     ----------
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index dda0762b5..06c92c652 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -55,7 +55,7 @@ def __repr__(self):
 
 
 class Material(MaterialBase):
-    """Define a continuous-energy material from a data-library composition.
+    """Continuous-energy particle-interaction properties assigned to simulation cells.
 
     Parameters
     ----------
@@ -236,7 +236,7 @@ def __repr__(self):
 
 
 class MaterialMG(MaterialBase):
-    """Define a material with multigroup neutron data.
+    """Multigroup neutron-interaction properties assigned to simulation cells.
 
     Parameters
     ----------
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index 3ce0b574e..fde373205 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -48,7 +48,7 @@ def __repr__(self):
 
 
 class MeshUniform(MeshBase):
-    """Define a Cartesian mesh with uniform spacing on each axis.
+    """Uniform spatial bins for simulation tallies and transport techniques.
 
     Parameters
     ----------
@@ -134,7 +134,7 @@ def __repr__(self):
 
 
 class MeshStructured(MeshBase):
-    """Define a Cartesian mesh from explicit grid boundaries.
+    """Structured spatial bins for simulation tallies and transport techniques.
 
     Parameters
     ----------
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 5db1fc6f5..f6647a7ee 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -47,7 +47,7 @@
 
 
 class Simulation(MCDCBase):
-    """Own a complete MC/DC model, settings, techniques, and runtime state.
+    """The complete model and configuration for one MC/DC calculation.
 
     Parameters
     ----------
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 8b4b513b1..76912e1b7 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -26,7 +26,7 @@
 
 
 class Source(MCDCObject):
-    """Define a particle source.
+    """Distributions of particles introduced into the simulation.
 
     A source specifies the initial position, direction, energy, time, particle
     type, and relative sampling probability for emitted particles.
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 261fee5b1..cf1daa671 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -41,7 +41,7 @@
 
 
 class Surface(MCDCObject):
-    """Implicit surface used to bound cells.
+    """Geometric boundaries of simulation cells.
 
     Surfaces are created with class methods such as :meth:`PlaneX`,
     :meth:`CylinderZ`, and :meth:`Sphere`. Unary ``+`` and ``-`` return the
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index d7f89a4e9..26f7bcc30 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -46,7 +46,7 @@
 
 
 class Tally(MCDCPolymorphic):
-    """Create a tally and select its estimator from the requested scores.
+    """Quantities measured during the simulation.
 
     Parameters
     ----------
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index 0252af10c..eada06a20 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -24,7 +24,7 @@
 
 
 class Universe(MCDCObject):
-    """Group cells into a reusable geometry.
+    """Reusable collections of cells in the simulation geometry.
 
     Parameters
     ----------
@@ -94,7 +94,7 @@ def __repr__(self):
 
 
 class Lattice(MCDCObject):
-    """Arrange universes on a uniform Cartesian lattice.
+    """Repeated arrangements of universes in the simulation geometry.
 
     Parameters
     ----------

From 81603bf9d91d7e75af6b19fe6ed6a37e01140075 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 06:51:52 +0700
Subject: [PATCH 142/202] update favicon

---
 docs/source/conf.py                     |  2 +-
 docs/source/images/home/mcdc_square.svg | 24 ++++++++++++++++++++++++
 2 files changed, 25 insertions(+), 1 deletion(-)
 create mode 100644 docs/source/images/home/mcdc_square.svg

diff --git a/docs/source/conf.py b/docs/source/conf.py
index dc9b6fdf7..77980240d 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -61,7 +61,7 @@
 html_theme = "pydata_sphinx_theme"
 html_title = "MC/DC Documentation"
 html_logo = "images/home/mcdc.svg"
-html_favicon = "images/home/mcdc.svg"
+html_favicon = "images/home/mcdc_square.svg"
 
 # Read the Docs provides the active version slug during hosted builds. Use the
 # development docs as the local-build default.
diff --git a/docs/source/images/home/mcdc_square.svg b/docs/source/images/home/mcdc_square.svg
new file mode 100644
index 000000000..70a892ed6
--- /dev/null
+++ b/docs/source/images/home/mcdc_square.svg
@@ -0,0 +1,24 @@
+<?xml version="1.0"?>
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="450" height="450" viewBox="0 0 450 450" xml:space="preserve" overflow="hidden">
+  <defs>
+    <clipPath id="clip0">
+      <rect x="535" y="3231" width="450" height="162"/>
+    </clipPath>
+    <clipPath id="clip1">
+      <rect x="-0.313683" y="-6096.31" width="2.74344e+06" height="999831"/>
+    </clipPath>
+    <image width="1016" height="540" 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apTUf+/5s9t6uJa61Edn6tRKWbyr7Xh8T1AFiG7BftVSeqHCv7bt9ykoE/c8vlR5+Xfb9viesW8/L73vv87NyaiWrHyr7b9QxGu5+I65EYDoePZ4O6TXnLW97yBVG3tbKBUTNRayGTg81fzZ7dxcSVisvOrpmodazsu31IXA+ARWS/YNdI1DmR7Pt9ykkH/kwbx+myE1ct5vyV3S/Mzq2ZqHYi2fe7nsFo/PG4HjfIBnXbElVbLRsXNRO1FjY5uOsns+d3LXGd4rKzayZqnUj2/T4krgfAaWS/WNdKVDqx7Bl9yTwDf+bL3ty+gbrMxDWL6frAn8me0fVM//fg/4vrEYbD4Y9ng7ptibqtlg2LmolaS3Ftf/P7szO6lLhKcdnZNRO1Tix7Rh8S1wNgHtkv1DUTteaSPacPmXfgz7xs+O4vyp7Vh8QVi+nDwJ96RvacrifuRsjGdNsSVVsvGxU1E7WWZvLhrb+YndOVxDWKy86umag1l+w5XU9cDYCT2tgZP5L9Ml0zUW1u2bO6ntMM/JmXDd/fy5Ef1yumJwN/plcjP+7EdbJB3bZE1dbLRkXNRK2lmuxvvik7qwuJKxSXnV0zUWtu2bO6mrgSAPPo08CfyZ7X5Zx24M+85J6Hvzh7ZpcTVyumRwP/zJk3vPOzs+d1LXEbrpON6bZlOBz+btRtvWxY1EzUWrrJh19zPjuv7Yn6xWVn10zUOpXseV1LXAWAefVt4M9kz+xqFhn4My++/OiXZM/tauJaxfRq4E/d+o6HPjd7ZlcS1+AG2aBuW6JqJ2TjomaiVhHXDl77ouzMNieqF5edXTNR69SyZ3YlcQUATqOPA38me24Xs+jAn3lVj0Z+XKmYvg38mRfc/c7Pz57b9kR9bjAcDifZoG5bom4nZAOjZqJWMZN/8rovyM5ta6J2cdnZNRO1FpI9t+2J6gCcVl8H/kz27K5lGQN/5tYHHnpB9vyuJa5TTB8H/szZjv0HL0ZtEtmYblu2t7f/aNTthGxk1EzUKmryK7d+bnZ2GxOVi8vOrpmotbDs2W1NVAZgEX0e+DPZ87uUZQ38mVtGu1+andGlxFWK6evAn7nl8nd/Wfb8tiXqkhgOh7+dDeq2Jep2RjY0aiZqFXftnWc+Kzu/bYm6xWVn10zUWors+W1LVAVgUX0f+DPZGV3JMgf+zK3v+N5O/5P8uEYxfR74M7c/+PCrsjPakqjJEbIx3cZE3c7IxkbNRK2VyTq0KVGzuOzsmolaS5Od0ZZERQCWYR0G/kx2They7IE/0+V/kh9XKKbvA3/m/P17r8nOqZ2oxxHuueeeV2Vjum258847Pycqd0Y2OGomaq1U1qMtiYrFZWfXTNRaquyc2olqACzLugz8meystqfEwJ/5iuH7X5id1/ZE/WLWYeDPnBvtvik7q1aiFjeRjek2Jup2SjY6aiZqrVzWpQ2JesVlZ9dM1Fqqtv1/y4haACzTOg38mey8NqfUwJ/5iv+0eyM/qhezLgN/5vzO+P7svFUn6nCMbEy3MVG3U7LhUTNRq4qsT+1EteKys2smai3dtYOzz8rOW3WiDgDLtm4DfyY7s60pOfBnzr7tkRdl57Y1UbuYdRr4M4PR3l/IzlxVogbHyIZ0GxN1OycbHzUTtarJOtVM1CouO7tmolYR137hzudkZ64qUQOAEtZx4M9k57YxpQf+zO2X3vPi7Ow2JioXs24Df+b85d13ZeeWThzPCWRjuo2Jup2TDZCaiVrVZJ1qJmoVl51dM1GrmMkvbT03O7d04ngASlnXgT+Tnd22rGLgz9x+aa8TIz/qFrOOA39msDP+oezsUoljOYHt7e1PZmO6bZn2fH9U7pxshNRM1Kom61QzUau47OyaiVpFTX72tV+cnV0qcSwAJa3zwJ/Jzm9TVjXwZ277Mw+/JOvQpkTVYtZ14M9sjMY/n52/7MRxnFA2ptuYqNtJ2RCpmahVTdapZqJWcdnZNRO1ipv84uu+Ijt/2YnjACht3Qf+TNahLVnlwJ955b3vfmnWoy2JmsWs88CfGYz2fjXrsIwMRuNJHMMJbW9v/2fZmG5jonInZWOkZqJWNVmnmolaxWVn10zUWonJR157LuuwrMQxAKyCgf9pWY82ZNUDf+aV945bO/KjYjHrPvBnpkP8N7Iei2Qw2nsiHs8csiHdxmxvbz83KndSNkhqJmpVk3WqmahVXHZ2zUStlZl89HUXsx6LJh4PwKoY+E/JutROjYE/c+uDD70s61M7Ua8YA//TLozGn8i6nCaD0fjxeCxzysZ0GxN1OysbJTUTtarJOtVM1CouO7tmotZKTR57/ddmXU6beCwAq2TgN2V9aqbWwJ95xf1X/3DWqWaiWjEG/lOyLvNmMNo17k8pG9JtTVTurGyY1EzUqibrVDNRq7js7JqJWit37WDzctZn3sTjAFg1A78p61MzNQf+TNapZqJWMQZ+U9bnpBmMxp+Mx3AK2ZBuY6Jup2XjpGaiVjVZp5qJWsVlZ9dM1Kpisr/1l7NOJ008BoAaDPymrE/NGPjNRK1iDPynyzodl+m4/0R8nVPY3t5+IhvTbUxU7rRsoNRM1Kom61QzUau47OyaiVrVTPY335P1Oi7xdQBqMfCbsj41Y+A3E7WKMfBzWa+jMh33vxtf45SyId3GDIfD34zKnZaNlJqJWtVknWomahWXnV0zUauqyf7W38u6HZX4GgA1GfhNWZ+aMfCbiVrFGPhHy7rdmI3R+N/Exzml7e3tH8vGdBsTlTsvGyo1E7WqyTrVTNQqLju7ZqJWdZODzR/J+t2Y+DgAtRn4TVmfmjHwm4laxRj4N5f1O8x03H8sPsYCsiHd1kTlzsvGSs1ErWqyTjUTtYrLzq6ZqNUKk/2tn806HiY+BkAbGPhNWZ+aMfCbiVrFGPjHyzpujPY+En/MgrIh3cbcd999F6Ny52WDpWaiVjVZp5qJWsVlZ9dM1GqNycHWY13oCbD2DPymrE/NGPjNRK1iDPyTub7fYGfvR+Ivs6BsSLc1UbkXstFSM1GrmqxTzUSt4rKzayZqtcrkYPOft70jwNoz8JuyPjVj4DcTtYox8E9u1m1jZ/cH4n9kCbIh3dZE5V64frC0IVGrmqxTzUSt4rKzayZqtc7kYOu32twPYO0Z+E1Zn5ox8JuJWsUY+NQyHA4n2ZBuY97whjd8dtTuhRuHVe1ErWqyTjUTtYrLzq6ZqAUA8zHwm7I+NWPgNxO1ijHwqSUb0m1NVO6NbFzVTNSqJutUM1GruOzsmolaADAfA78p61MzBn4zUasYA58aZv998tmQbmuidm9k46pmolY1WaeaiVrFZWfXTNQCgPkY+E1Zn5ox8JuJWsUY+NSQjei2Jir3SjauaiZqVZN1qpmoVVx2ds1ELQCYj4HflPWpGQO/mahVjIHPqt1zzz2vyoZ0WxO1eyUbVzUTtarJOtVM1CouO7tmohYAzMfAb8r61IyB30zUKsbAZ9WyEd3WbG9vPxK1eyUbVzUTtarJOtVM1CouO7tmohYAzMfAb8r61IyB30zUKsbAZ9WyId3WROXeycZVzUStarJONRO1isvOrpmoBQDzMfCbsj41Y+A3E7WKMfBZpWxEtzlRu3eycVUzUauarFPNRK3isrNrJmoBwHwM/KasT80Y+M1ErWIMfFYpG9Ftzfb29nOjdu9k46pmolY1WaeaiVrFZWfXTNQCgPkY+E1Zn5ox8JuJWsUY+KzKcDh8PBvSbU3U7qVsXNVM1Kom61QzUau47OyaiVoAMB8DvynrUzMGfjNRqxgDn1XJRnSbE7V7KRtXNRO1qsk61UzUKi47u2aiFgDMx8BvyvrUjIHfTNQqxsBnFS5duvS2bES3NVG7t7JxVTNRq5qsU81EreKys2smagHAfAz8pqxPzRj4zUStYgx8ViEb0W1O1O6tbFzVTNSqJutUM1GruOzsmolaADAfA78p61MzBn4zUasYA59VyEZ0WzMcDv911O6tbFzVTNSqJutUM1GruOzsmolaADAfA78p61MzBn4zUasYA5/SshHd5kTtXsvGVc1ErWqyTjUTtYrLzq6ZqAUA8zHwm7I+NWPgNxO1ijHwKS0b0W1O1O61bFzVTNSqJutUM1GruOzsmolaADAfA78p61MzBn4zUasYA5+ShsPhE9mIbmvuv//+rajea9m4qpmoVU3WqWaiVnHZ2TUTtQBgPgZ+U9anZgz8ZqJWMQY+JWUjus2J2r2XjauaiVrVZJ1qJmoVl51dM1ELAOZj4DdlfWrGwG8mahVj4FPKcDj88WxEtzlRvfeycVUzUauarFPNRK3isrNrJmoBwHwM/KasT80Y+M1ErWIMfErJBnSbc/fddz8zqvdeNq5qJmpVk3WqmahVXHZ2zUQtAJiPgd+U9akZA7+ZqFWMgU8hz8xGdJsTvddCNq5qJmpVk3WqmahVXHZ2zUQtAJiPgd+U9akZA7+ZqFWMgU8J2YBue6L6WsjGVc1ErWqyTjUTtYrLzq6ZqAUA8zHwm7I+NWPgNxO1ijHwKSEb0G1O1F4b2biqmahVTdapZqJWcdnZNRO1AGA+Bn5T1qdmDPxmolYxBj7LNhwOJ9mIbnOi+trIxlXNRK1qsk41E7WKy86umagFAPMx8JuyPjVj4DcTtYox8Fm2bEC3Odvb2w9H9bWRjauaiVrVZJ1qJmoVl51dM1ELAOZj4DdlfWrGwG8mahVj4LNMw+Hwt7MR3eZE9bWSjauaiVrVZJ1qJmoVl51dM1ELAOZj4DdlfWrGwG8mahVj4LNM2YBue6L6WsnGVc1ErWqyTjUTtYrLzq6ZqAUA8zHwm7I+NWPgNxO1ijHwWZZ77733FdmAbnPe9KY3PSfqr5VsXNVM1Kom61QzUau47OyaiVoAMB8DvynrUzMGfjNRqxgDn2XJBnTbE9XXTjauaiZqVZN1qpmoVVx2ds1ELQCYj4HflPWpGQO/mahVjIHPsmQDuu3Z3t7+jtqZ9vimeIUrk42rmola1WSdaiZqFZedXTNRCwDmY+A3ZX1qxsBvJmoVY+CzDDcOZzl54hWuVDauaiZqVZN1qpmoVVx2ds1ELQCYj4HflPWpGQO/mahVjIHPMmTDVY5PvL6Vy8ZVzUStarJONRO1isvOrpmoBQDzMfCbsj41Y+A3E7WKMfBZ1HA4fCIbr3LzvPWtb/3SeIUrl42rmola1WSdaiZqFZedXTNRCwDmY+A3ZX1qxsBvJmoVY+CzqGy8yvGJ11dFNq5qJmpVk3WqmahVXHZ2zUQtAJiPgd+U9akZA7+ZqFWMgc8iHnjggT+bjVe5eeL1VZONq5qJWtVknWomahWXnV0zUQsA5mPgN2V9asbAbyZqFWPgs4hsvMrNE6+uqmxc1UzUqibrVDNRq7js7JqJWgAwHwO/KetTMwZ+M1GrGAOfRWQDVm6aH45XV1U2rmomalWTdaqZqFVcdnbNRC0AmI+B35T1qRkDv5moVYyBz2kl41WOSby66rJxVTNRq5qsU81EreKys2smagHAfAz8pqxPzRj4zUStYgx8TisbsHJ04rW1QjauaiZqVZN1qpmoVVx2ds1ELQCYj4HflPWpGQO/mahVjIHPaQyHw0k2YiXPm970pufEq2uFbFzVTNSqJutUM1GruOzsmolaADAfA78p61MzBn4zUasYA5/TyEasHJ14ba2RjauaiVrVZJ1qJmoVl51dM1ELAOZj4DdlfWrGwG8mahVj4DOv4XD4U9mIlTzx2lolG1c1E7WqyTrVTNQqLju7ZqIWAMzHwG/K+tSMgd9M1CrGwGde2YiVPPHKWicbVzUTtarJOtVM1CouO7tmohYAzMfAb8r61IyB30zUKsbAZx533333s7IhK0/PcDj83nhtrZONq5qJWtVknWomahWXnV0zUQsA5mPgN2V9asbAbyZqFWPgM49syEqeeGWtlI2rmola1WSdaiZqFZedXTNRCwDmY+A3ZX1qxsBvJmoVY+Azj2zIytMTr6u1snFVM1GrmqxTzUSt4rKzayZqAcB8DPymrE/NGPjNRK1iDHxOKhuy8vS88Y1v/Nx4Za2VjauaiVrVZJ1qJmoVl51dM1ELAOZj4DdlfWrGwG8mahVj4HNS2ZiVZobD4RPxulotG1c1E7WqyTrVTNQqLju7ZqIWAMzHwG/K+tSMgd9M1CrGwOckpsP149mglWbidbVeNq5qJmpVk3WqmahVXHZ2zUQtAJiPgd+U9akZA7+ZqFWMgc9JZGNWmolX1QnZuKqZqFVN1qlmolZx2dk1E7UAYD4GflPWp2YM/GaiVjEGPsd54IEHbskGrTyV4XD4V+J1dUI2rmomalWTdaqZqFVcdnbNRC0AmI+B35T1qRkDv5moVYyBz3GyQSvNxKvqjGxc1UzUqibrVDNRq7js7JqJWgAwHwO/KetTMwZ+M1GrGAOf42SDVp5KvKZOycZVzUStarJONRO1isvOrpmoBQDzMfCbsj41Y+A3E7WKMfC5mWzQylO58847PydeVadk46pmolY1WaeaiVrFZWfXTNQCgPkY+E1Zn5ox8JuJWsUY+NxMNmrl0xkOh5+I19Q52biqmahVTdapZqJWcdnZNRO1AGA+Bn5T1qdmDPxmolYxBj5HyUatPJV4TZ2UjauaiVrVZJ1qJmoVl51dM1ELAOZj4DdlfWrGwG8mahVj4HOUbNTKpxOvqLOycVUzUauarFPNRK3isrNrJmoBwHwM/KasT80Y+M1ErWIMfDLb29t/Phu28mTujdfUWdm4qpmoVU3WqWaiVnHZ2TUTtQBgPgZ+U9anZgz8ZqJWMQY+mWTUSiReUadl46pmolY1WaeaiVrFZWfXTNQCgPkY+E1Zn5ox8JuJWsUY+GSyYSv9GPcz2biqmahVTdapZqJWcdnZNRO1AGA+Bn5T1qdmDPxmolYxBj43yoatPDnun/HpN9R92biqmahVTdapZqJWcdnZNRO1AGA+Bn5T1qdmDPxmolYxBj43ysbtumc4HH48Xk8vZOOqZqJWNVmnmolaxWVn10zUAoD5GPhNWZ+aMfCbiVrFGPhcLxu30p9/a/6hbFzVTNSqJutUM1GruOzsmolaADAfA78p61MzBn4zUasYA5/rZeN23ROvpleycVUzUauarFPNRK3isrNrJmoBwHwM/KasT80Y+M1ErWIMfA4Nh8OfywbuOue+++67GK+nV7JxVTNRq5qsU81EreKys2smagHAfAz8pqxPzRj4zUStYgx8DmUDd90Tr6Z3snFVM1GrmqxTzUSt4rKzayZqAcB8DPymrE/NGPjNRK1iDHzaJBvZtRKVeikbVzUTtarJOtVM1CouO7tmohYAzMfAb8r61IyB30zUKsbApy2Gw+EnsqFdI1Gpt7JxVTNRq5qsU81EreKys2smagHAfAz8pqxPzRj4zUStYgx82iIb2pXye1Gpt7JxVTNRq5qsU81EreKys2smagHAfAz8pqxPzRj4zUStYgx82iIZ2lUSdXotG1c1E7WqyTrVTNQqLju7ZqIWAMzHwG/K+tSMgd9M1CrGwKcNhsPhp7KxvepEnd7LxlXNRK1qsk41E7WKy86umagFAPMx8JuyPjVj4DcTtYox8GmDbGyvOm95y1teFnV6LxtXNRO1qsk61UzUKi47u2aiFgDMx8BvyvrUjIHfTNQqxsCnDbLBvepElbWQjauaiVrVZJ1qJmoVl51dM1ELAOZj4DdlfWrGwG8mahVj4FPbcDh8PBvcq0xUWRvZuKqZqFVN1qlmolZx2dk1E7UAYD4GflPWp2YM/GaiVjEGPrVlg3uViRprJRtXNRO1qsk61UzUKi47u2aiFgDMx8BvyvrUjIHfTNQqxsA/uVm3wWj8+/E/siTZ6F5hfiNqrJVsXNVM1Kom61QzUau47OyaiVqtM9nfmrS5H8DaM/Cbsj41Y+A3E7WKMfBP5vp+g529j8dfZkHD4XCSjO6VJWqsnRuHVe1ErWqyTjUTtYrLzq6ZqNUq03H/RNs7Aqw9A78p61MzBn4zUasYA/94WceN0fiT8ccsIBvdq0pUWEvXD5Y2JGpVk3WqmahVXHZ2zUSt1rhx3Le1J8DaM/Cbsj41Y+A3E7WKMfBvLut3mOnIfzw+xillw3sVefOb3/yFUWEtZaOlZqJWNVmnmolaxWVn10zUaoXJwdbjWcfDxMcAaAMDvynrUzMGfjNRqxgD/2hZtxszGI0n8XHmlA3vVSUqrK1ssNRM1Kom61QzUau47OyaiVrVTcf9p7J+NyY+DkBtBn5T1qdmDPxmolYxBn4u63VUjPzTyYb3KhLHr7VsrNRM1Kom61QzUau47OyaiVpVTfZPNu4PE18DoCYDvynrUzMGfjNRqxgD/+myTsfFyJ/P2bNnn5WN79KJ49deNlRqJmpVk3WqmahVXHZ2zUStaqbj/hNZr+MSXwegFgO/KetTMwZ+M1GrGAO/Ketz0hj5J5eN7xXkg3H82stGSs1ErWqyTjUTtYrLzq6ZqFXFacf9YeIxANRg4DdlfWrGwG8mahVj4D8l6zJvjPyTScZ38cTRTGUDpWaiVjVZp5qJWsVlZ9dM1Fq5ycHW72V95k08DoBVM/Cbsj41Y+A3E7WKMfA/Letx2hj5N/fAAw98dTbASyaOJmTjpGaiVjVZp5qJWsVlZ9dM1Fqpyf5yxv1h4rEArJKB35T1qRkDv5moVYyBX+5nHo/nBtkAL5m77777eXE0IRsmNRO1qsk61UzUKi47u2ai1spc29/8nazHoonHA7AqBn5T1qdmDPxmolYx6z7ws/OXmTiG62QjvGTiWK6TjZKaiVrVZJ1qJmoVl51dM1FrJSYHm/8m67CsxDEArIKB35T1qRkDv5moVcw6D/zs7BKJ45iaDu733DjASyaO5QbZIKmZqFVN1qlmolZx2dk1E7WKmxxs/UZ2/rITxwFQmoHflPWpGQO/mahVzLoO/Ozckolj1142wksljiSRjZGaiVrVZJ1qJmoVl51dM1GrqMn+1seys0sljgWgJAO/KetTMwZ+M1GrmHUc+NmZq0gcv9ayIV4i29vbfzeOJJENkZqJWtVknWomahWXnV0zUauY6bj/tezc0onjASjFwG/K+tSMgd9M1Cpm3QZ+dt4qEzXW0nA4/NVsjJdIHMkRshFSM1GrmqxTzUSt4rKzayZqFTF5bPOj2ZmrStQAoAQDvynrUzMGfjNRq5h1GvjZWTUSddZONsRLJI7jJrIBUjNRq4qsT+1EteKys2smai3ddNx/JDtv1Yk6ACybgd+U9akZA7+ZqFXMugz87JyaiVprJRvjy87ly5efE8dxE9n4qJmotXJZlzYk6hWXnV0zUWupJgdbP5edVStRC4BlMvCbsj41Y+A3E7WKWYeBn53RhkS9tTAcDn8/G+TLThzHMbLhUTNRa6WyHm1JVCwuO7tmotbSTPa3fjY7p3aiHgDLYuA3ZX1qxsBvJmoV0/eBnz2/TYmavZeN8WUnjuIEstFRM1FrZbIObUrULC47u2ai1lJMHtv6seyMtiRqArAMBn5T1qdmDPxmolYxfR742bPbmKjba9kgX2biGE4oGxw1E7VWIju/bYmqxWVn10zUWtjksc3/LXt+2xJ1AViUgd+U9akZA7+ZqFVMGwf+LFHv1LJntjlRu5eGw+Hj2ShfVqbP//Y4ihPKxkbNRK3isrPbmKhbXHZ27US1U5scbP0P2XPbmqgNwCIM/KasT80Y+M1ErWLaOvBniYpzG4zGT2TPa3uifu9ko3yZiWOYQzY0aiZqFZWd29ZE5eKys9uQqDe3yUe2/mb2vLYn6gNwWgZ+U9anZgz8ZqJWMW0e+LNEzRMbXBk/nj2nK4lr9Eo2ypeVOII5ZSOjZqJWMdmZbU7ULi47uzW5duazouaJTA62vjd9TkcS1wDgNAz8pqxPzRj4zUStYto+8GeJqscajMafyr7ftcR1emE4HD6RDfNl5A1veMNnxzHMKRsYNRO1isjOa3uienHZ2W3K5NcvPjuq3tTkYPO92fe7lrgOAPMy8JuyPjVj4DcTtYrpwsCfJeoeaXBl/Mnse11NXKvzsmG+rMQRnEI2Lmomai1ddlYXEvWLy85uWya/cusXRN3UZH/z3dn3OptrZ54RVwPgpAz8pqxPzRj4zUStYroy8GeJyk8zGI1/P/t8V3NH5f8dWKZsmC8j8XhOKR0WFRO1lio7pyuJKxSXnd3GTD76mhdH5YbJRze/Nft8VzPZ3/yDuBoA8zDwm7I+NWPgNxO1iunSwJ8lan9G38b9+Z3xN8XVOm84HE6ycb5o4vEsIBsXNRO1lmLyMxefnZ3RpcRVisvObm1+efP2qP2kyUc2vyX9XEczOdj67bgaAPMy8JuyPjVj4DcTtYrp2sCfJapPx/3e72Z/3tXcsTP+j+JqvZCN80UzHA7fHo9nAdnAqJmotbDJhy6+NHt+1xLXKS47u82ZfOS1f2zWe3Jw8e3Zn3c1xj3Aggz8pqxPzRj4zUStYro48GcZjMa9GvfnLu/9x/Ej6Y1soC+aeDQLykZGzUSthUxH3+uyZ3cxcaXisrPbnsljWx/I/npXY9wDLIGB35T1qRkDv5moVUxXB36fsjF69D+JH0dvZON80cSjWYJsaNRM1Dq1yUc3vzl7blcT1youO1tWl+m4/7fxowBgEQZ+U9anZgz8ZqJWMQZ+3dxxae9Pxo+iV7KBvkimj/SfLL1E2diomah1KpODu/6L7JldTlytuOxsWU0m+1u/GT8GABaV/ZJdO2fuvvuZUW+lXrkzfmnWp3ai3soNroz/j6xP7US9YrIzpXzOXd77uvgR9Mo3f/M3f0k20hfIJ+LRLEk2OGomas1tOpK+N3te1xPXK276/n40O1/KZnJg3AMsTfZLdluy6pHf1nF/mKi5MoPR7s9kPdqSqFlMdqaUy/md8TfEq++dZKAvlHgsS5SNjpqJWnOZPLb1D7Jn9SFxxZUw8lebyf7mb8WrB2BR2S/ZbcuqRv5t2x94SXZ+2xJ1i7twZfens/PblqhbTHamLD/ntx/5E/HKeykb6adNPJIly4ZHzUStE5uO0v3sOX1JXHNlpu/zx7IestxM3/PH4pUDsKjsl+y2pvTI/yPbD3di3B8mahdzYTT+qezctiZqF5OdKcvL+Uu7Xx2vupe2t7e/Phvqp8nsWfFYlmg6Mp7IxkfNRLUTmfb/l9kz+pS46kpNDrb+x6yLLCfT9/tr8aoBWFT2S3bbU2rk39axcX+YqL90gyt7P5md1/ZE/WKyM2XxDC5d/Zp4xb2VDfXTJh7JEk3H8SQbH7UT9Y41Odj87ez7fUtcd+Um+5v/U9ZHFot/cg+wRNkv2V3Jskf+7Zf2Xpyd05XENZZmMBr/79k5XUlco5jsTDl9zl26uhWvtteyoX6axONYomx4tCVR8aYmB3f9fvbdviWuW42Rv9xMDrZ+KV4tAIvKfsnuWpY18rs+7g8T11nYdNz/RPb8riWuU0x2psyfwc74rnilvba9vf3+bKzPm+mj/FfiLVk2PNqUqHmk6Uj6ZPa9viWuW9105P9A1k/mi3EPsETZL9ldzZl3vvOz4lqncvul9/Ri3B8mrnVqF0bjH8+e29XEtYrJzpSTZ+Ntj35lvMrey8b6vBkOh78Tj2NJsuHRtkTV1GR/6/HsO31LXLc1piP/72Q95WSZ7N/1y/EqAVhU9kt213Pakd+3cX+YuN7cNnb6Ne4PE9crJjtTjs/5Sw+/Jl7hWsgG+7yJR7Ek2fBoY6Lu07T1PzNg2Ynrts505P/drK8ck/2tX4hXCMCisl+y+5J5R/7Ztz3youw5fUlc88QGo/GPZs/pS+KaxWRnytE5f2X3znh1a2E4HP6LbLDPk3gUS5IOj5YmKjdkn+tj4rqtNTnYupr1ljyT/a1/Gq8OgEVlv2T3LScd+X0f94eJ6x5rsDP+kez7fUtct5jsTHl67rj88B+NV7Y2ssE+T+6///61+A8hXJVseLQ5Ufszss/0MXHd1ps8trmb9ZdmpuP+g/HKAFhU9kt2X3PcyF+XcX+YuPaRBqPdf5h9r6+JaxeTnSlP5dyVq6+NV7VWstE+T+IxLEE2PNqeqP6k7M/7mLhuZ0z2N8fZPeTTmezf9fPxqgBYVPZLdt9z1Mg/e996jfvDxPWfZnBl/A+yz/c9cf1isjNl9k/uH709XtFaGQ6Hn8hG+0kTj2EJsuHRhUR9477lJvsXvy27z7pnsr/5U/GKAFhU9kv2uuTGkX/H8P0vzD63LonX8BmD0fiHs8+tS+I1FJOduc45N7z66ng1aycb7SdNPIIlyIZHV9L1/vPkyR9Wh13b3/r27F7rmsnB5k/HqwFgUdkv2euWeBUzz8j+fN0S7+LMxmj3r2d/vm6J11FMduY65uwDD52NV7KWsuF+ksz+g/niESwoGx7SvsSPq/Mmj21+Z3a/dcvkYOsfxysBYFmyX7bXJS9867s+L17Dkwb3jl+afW5dEq/hMwaj8c9ln1uXxGsobnBl/Mns/HXJYGf85fEq1tJ0pE+y8X6SxCNYUDY8pH2JH1dvTPY3vyW757pkev9/GK8CgGXLfunue158+dHnxPUbzt1/9Q9nn+974vpPMx35P599vu+J66/Muo78dR/3M9lwP0ni6ywoGx7SvsSPq3cmB5vfmt2375mO+x+JVwBAKdkv333Nxg3/5P5GZ4eP3Jp9r6+Jax9pOj5/IfteXxPXXrnBaPyprE9fs/H27/mKuPpay8b7CfKq+DoLyIaHtC/x4+qtyWNb78zu3ddM9rd+NK4OQGnZL+F9y3Hj/tDtD37Pq7Lv9y1x3WMNRrv/NPt+3xLXrWYw2vuDrFffsjHa/dK48lo77b89P77OgrLxIe1K/Kh6b3Jw8c9m9+9bJvub/3NcGYBVyX4Z70tOOu4PnXtgPMie05fENU9ssDP+YPacviSuWV3fR/4dw+9+YVx17WXj/bjEV1mSbIRIOxI/orUxOdj6c9l76EsmB5v/S1wVgFXLfinveuYd94fOP7h7Z/a8rieuN7eN0fhD2fO6nrhea/R15M/+qyjjikxlA/5mia+xZNkYkbqJH83amexv/vnsfXQ9k4OLPxRXBKCW7Jfzrua04/7QuZ3xXdlzu5q41qn1beTHtVpnOvJ/N+vb1bz8vvc+P67G1Lz/9vzt7e0PxVcpIBslUifxI1lb1w42L2fvpauZHGz9t3E1AGrLfknvWjbe+rcXGveH7rhy9Q3Z87uWuM7CNkZ7v5g9v2uJ67RWX0b+LZcffV5ciZCN+JslvkZB2TiR1SZ+FGtvcnDXTvZ+upbJweZ/F1cCoC2yX9a7krN3P/L5cY2luGNn/LXZOV1JXGNpBqPxh7NzupK4RutN3/O/y/p3Jf7JfS4b8UclvkJh166deWY2UmQ1iR8DYbK/dSV7T13J5GDrB+MqALRN9kt723P2bcsd94fO74y/ITuv7Yn6Szcdn49l57U9Ub8zBqO9f5vdo+0x7nPZiD8q99xzzxfH11iBa//szudlY0XKJl4/N5g8tvXW7H21Pvtb/31cAYC2yn55b2tKjftD05H/zdm5bU3ULmZwZW8/O7etidqd07WR//L7vu8PRXVukA35oxJfYYUmBxdvTUeLFEm8do4w2d+8J3tvbc207/dFdQDaLvslvm0pPe4PbYwe2c7Ob1uibnEbo/FBdn7bEnU7azAa/1Z2r7bFuD/a9vb2S7IhnyW+QgWTX9z8qmy8yHITr5tjTPYv3pu9v9Zlf/P7ozIAHfGM7Jf5tmRV4/7QYGf89qxHWxI1V2ZjtPuRrEdbEjU778Jo719m92tLjPuby4Z8lvg4FU32X/+n0xEjS0m8Zk5o8tGL35i9x9Zkf8u4B+ioVo7827a/47nRb6Wmo/YvZX1qJ+qt3GA0/mjWp3aiXm9M3/O/yu5ZO2fe8M7PjoocIRvzN2Y4HP5IfJzKJvtbfyEdM7JQPv12mdf078dW/j86TR67+EhUBKCT7r77mdkv97VSa9wfOr8z/qtZr1qJWtW0beRHrd6ZvuePZfetFeP+eNvb2/dkg/7GxMdpiel4uZqNGjld4rVySpODzW/K3mutTB7buhrVAOi0loz827Y/UHXcHxrs7H1X1m/ViTrVTcfnL2X9Vp2o01vT9/zPs3uvOsb9yWRj/sbER2mZ6aj6wWzcyHyJ18mCJh/d+prs/a46k8c2d6MSAL1w9zuflf2yv6q0ZdwfGuyM35f1XFWiRmsMrox/Oeu5qkSN3tu4svdr2f1XlajBCWSD/vrceeednxMfpYWu7W/9RDZy5GSJ18iSTA4uvjF7zyvL/ta3RxUAeqXSyL/1LQ99QTRolY3R3vdlfUsnjm+dwWj8f2Z9SyeOXxuDK3X+HRNxPCcwHA5/MBv11yc+SotNDrZ+KR07ctPE62PJJh95/X+Qve/SmRxsfkdUAKCPXvZN73529st/qbR13B+ajvy/k/UulTi2tTZGu7+S9S6VOHbtrPo/+yCO5YSyQX994mN0wHTk/0Y2eiRPvDYKmXzo4l3Zey+V6bj/zjgagD574Vvf9XnZCFh22j7uDw12xj+U9V924rjWm47P/yvrv+zEcWtrVf/ZB3Ecc8hG/WHiI3TItf2t38nGjzQTr4vCrv3i678ye//LzmR/67+MIwFYB7fc/e3Py8bAstKVcX9oYzT++9k9lpU4pjOm4/NXs3ssK3HM2hvs7H0wez/LShzDHKYj/jdvHPWHGQ6Hfy8+RsdMx87HsxEkn068JlZk8uHX/XvZz2FZmXx46y/HUQCsk7PDd39RNgoWza3v6Na4PzTYGf9Udp9FE4/vnOnI/2fZfRZNPJ4wGO39YvaeFk08njllw/4w8RE6ajryP5WNoXVPvB5WbPLY6zeyn8eimXx481viCADW0a0PPPSCbBycNrdc/vbnxaM7aWO099PZvU6beGxnTUf+Uv+r3eKx3GD6nj+cva/TJh7LKWTDfpb4YzpuOvIfz0bRuiZeC5VMPvi6QfZzOW0mj21+azwagHV22/bDL8lGwrzp+rg/dGE0/l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+    <clipPath id="clip3">
+      <path d="M577150 437165 3.32059e+06 437165 3.32059e+06 1.42447e+06 577150 1.42447e+06Z" fill-rule="evenodd" clip-rule="evenodd"/>
+    </clipPath>
+  </defs>
+  <g transform="translate(0 144)">
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+          <use width="100%" height="100%" xlink:href="#img2" transform="scale(3890.83 3890.83)"/>
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+</svg>

From bf207ab3a9de3124f1c7a50d33ed452e403e7c1d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 07:41:50 +0700
Subject: [PATCH 143/202] update docstrings

---
 mcdc/object_/material.py             | 33 ++++++++++++++--------------
 mcdc/object_/particle.py             |  4 ++--
 mcdc/object_/source.py               | 17 +++++++-------
 mcdc/object_/tally.py                |  7 +++---
 mcdc/object_/transport_model_data.py | 19 ++++++++--------
 5 files changed, 41 insertions(+), 39 deletions(-)

diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index 22c78abc1..b9d91fec2 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -32,21 +32,20 @@ class Material(MCDCObject):
         Material temperature in kelvin. Each nuclide uses the closest
         temperature available in the data library.
     neutron_multigroup : NeutronMultigroupData, optional
-        Multigroup cross sections for neutron transport. When supplied with a
-        native composition, an explicit ``energy_grid`` is required and defines
-        the energy range over which multigroup physics applies.
+        Groupwise macroscopic cross sections and related data for neutron
+        multigroup transport, where neutron energy is represented by discrete
+        groups. When supplied with a native composition, its explicit
+        ``energy_grid`` defines the energy range where the multigroup treatment
+        applies.
 
     Notes
     -----
-    At least one native composition or multigroup dataset must be supplied.
-    Nuclide and element compositions cannot both be specified because they are
-    alternative native representations of the same material. A native
-    composition may be supplied together with ``neutron_multigroup`` for hybrid
-    neutron physics.
-
-    Nuclide and element objects are created immediately; their data-library
-    properties are loaded when the material is compiled into a simulation.
-    Construction therefore does not access the data library.
+    A nuclide or element composition connects the material to MC/DC's native
+    data libraries. Particle-specific data can augment native interaction data
+    or support specialized and reduced transport treatments.
+    ``NeutronMultigroupData`` describes discrete neutron energy groups and
+    their macroscopic interaction, production, and timing data. It can be used
+    alone or alongside a native composition.
 
     Examples
     --------
@@ -196,13 +195,13 @@ def multigroup(
         energy_grid: ArrayLike | NoneType = None,
         energy_representation: str | int = "midpoint",
     ) -> Self:
-        """Construct a material containing only multigroup neutron data.
+        """Create a material for neutron multigroup transport.
 
-        The transport arguments are forwarded to :class:`NeutronMultigroupData`.
-        Use the regular constructor when combining multigroup data with a
-        native nuclide or element composition.
+        The supplied arguments define groupwise macroscopic interaction and
+        production data. This helper stores them in
+        :class:`NeutronMultigroupData` and attaches the data to the material.
         """
-        # Build the transport-mode data while preserving Material as the sole type
+        # Build the neutron multigroup data while preserving Material as the sole type
         neutron_multigroup = NeutronMultigroupData(
             capture=capture,
             scatter=scatter,
diff --git a/mcdc/object_/particle.py b/mcdc/object_/particle.py
index 3b9c4ec8a..4855c9227 100644
--- a/mcdc/object_/particle.py
+++ b/mcdc/object_/particle.py
@@ -15,8 +15,8 @@
 class ParticleData(MCDCBase):
     """Serializable phase-space state stored in particle banks.
 
-    ``group`` is an integer state interpreted by the active transport mode. Neutron
-    multigroup transport uses it as the neutron energy-group index.
+    ``group`` is an auxiliary integer state available to transport physics.
+    Neutron multigroup transport uses it as the neutron energy-group index.
     """
 
     # MC/DC framework metadata
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index ff3caa921..848847649 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -29,7 +29,8 @@ class Source(MCDCObject):
     """Distributions of particles introduced into the simulation.
 
     A source specifies the position, direction, energy, time, particle type,
-    transport-mode group, and relative sampling probability for emitted particles.
+    auxiliary group state, and relative sampling probability for emitted
+    particles.
 
     Parameters
     ----------
@@ -68,13 +69,13 @@ class Source(MCDCObject):
         second row contains their probability density. Defaults to a
         mono-energetic source at **1 MeV**.
     group : int or array_like, optional
-        Transport-mode group number. A Python or NumPy integer defines a
-        mono-group source. An array-like value with shape ``(2, N)`` defines a
-        discrete probability mass function: the first row contains integer
-        group numbers and the second row contains their probabilities. The
-        interpretation belongs to the active transport mode; neutron
-        multigroup transport interprets it as an energy-group index. The
-        default is **group 0**.
+        Auxiliary integer state assigned to an emitted particle. A Python or
+        NumPy integer defines a mono-group source. An array-like value with
+        shape ``(2, N)`` defines a discrete probability mass function: the
+        first row contains integer group values and the second row contains
+        their probabilities. The physics using the group determines its
+        meaning; neutron multigroup transport interprets it as an energy-group
+        index. The default is **group 0**.
     time : real or array_like of float, optional
         Emission time in seconds. A real scalar, including a NumPy scalar,
         defines a discrete emission time. An array-like value with shape
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 8f29baf01..c0fea001e 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -79,9 +79,10 @@ class Tally(MCDCPolymorphic):
         Particle type selected by the tally. If omitted, the tally accepts any
         transported particle type.
     group : sequence of float or "all", optional
-        Transport-mode group-bin boundaries. These bins may collapse several
-        transport groups into one tally bin. ``"all"`` creates one tally bin
-        per neutron energy group during compilation.
+        Bin boundaries for the auxiliary integer group state. The physics using
+        the group determines its meaning. For neutron multigroup transport,
+        these bins may collapse several energy groups into one tally bin, and
+        ``"all"`` creates one bin per neutron energy group during compilation.
     energy : sequence of float, optional
         Continuous-energy bin boundaries in eV.
     time : sequence of float, optional
diff --git a/mcdc/object_/transport_model_data.py b/mcdc/object_/transport_model_data.py
index a64f1a9c6..ff3f78aa9 100644
--- a/mcdc/object_/transport_model_data.py
+++ b/mcdc/object_/transport_model_data.py
@@ -27,11 +27,14 @@
 
 
 class NeutronMultigroupData(MCDCObject):
-    """Multigroup neutron-interaction properties assigned to a material.
+    """Groupwise macroscopic interaction data for neutron multigroup transport.
 
-    Materials may use ``NeutronMultigroupData`` alone for multigroup transport or
-    alongside a native composition over the energy range defined by
-    ``energy_grid``.
+    Neutron multigroup transport represents neutron energy with discrete groups
+    and describes interactions using groupwise cross sections, production
+    spectra, speeds, and delayed-precursor data. For a multigroup-only material,
+    :meth:`mcdc.Material.multigroup` provides the convenient entry point.
+    Construct ``NeutronMultigroupData`` directly to attach it alongside a native
+    composition over the energy range defined by ``energy_grid``.
 
     Parameters
     ----------
@@ -86,11 +89,9 @@ class NeutronMultigroupData(MCDCObject):
 
     Notes
     -----
-    ``G`` is inferred from ``capture``, ``scatter``, or ``fission``. Calling
-    ``NeutronMultigroupData()`` without any cross sections creates the reserved
-    zero-group placeholder used by materials without multigroup data. Cross
-    sections are macroscopic and use inverse-length units. The generated default
-    energy grid supports only the default ``"midpoint"`` representation.
+    ``G`` is inferred from ``capture``, ``scatter``, or ``fission``. Cross
+    sections are macroscopic and use inverse-length units. The generated
+    default energy grid uses the default ``"midpoint"`` representation.
 
     Examples
     --------

From e33117ab649bdd5118f48c7d349e102e9fb41b9f Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 08:56:20 +0700
Subject: [PATCH 144/202] update docs

---
 docs/source/contributing/index.rst            |  2 +-
 docs/source/reference/python_api/index.rst    | 10 ++-
 .../getting_started/first_simulation.rst      | 20 ++---
 .../user_guide/materials_and_multigroup.rst   | 83 ++++++++++++-------
 .../user_guide/simulation_lifecycle.rst       |  6 +-
 docs/source/user_guide/tallies.rst            | 24 +++---
 mcdc/object_/material.py                      | 13 ++-
 mcdc/object_/simulation.py                    | 19 ++++-
 mcdc/object_/source.py                        |  4 +-
 mcdc/object_/surface.py                       | 15 ++--
 mcdc/object_/tally.py                         |  4 +-
 mcdc/object_/technique.py                     |  4 +-
 mcdc/object_/transport_model_data.py          | 44 +++++-----
 mcdc/visualize.py                             | 13 +--
 14 files changed, 164 insertions(+), 97 deletions(-)

diff --git a/docs/source/contributing/index.rst b/docs/source/contributing/index.rst
index 591dbc1c4..221456e95 100644
--- a/docs/source/contributing/index.rst
+++ b/docs/source/contributing/index.rst
@@ -123,7 +123,7 @@ input-related locations include:
 
 #. ``mcdc/object_/settings.py`` — simulation settings and k-eigenvalue parameters
 #. ``mcdc/object_/material.py`` — material and composition definition
-#. ``mcdc/object_/transport_model_data.py`` — particle-specific transport-model data
+#. ``mcdc/object_/transport_model_data.py`` — particle-specific transport data
 #. ``mcdc/object_/surface.py`` — surface geometry (``Surface`` class methods)
 #. ``mcdc/object_/cell.py`` — cell definitions (``Cell``)
 #. ``mcdc/object_/source.py`` — source specifications (``Source``)
diff --git a/docs/source/reference/python_api/index.rst b/docs/source/reference/python_api/index.rst
index 8c2edd6c6..126673efd 100644
--- a/docs/source/reference/python_api/index.rst
+++ b/docs/source/reference/python_api/index.rst
@@ -43,8 +43,14 @@ Model building blocks
 Materials
 ^^^^^^^^^
 
-Materials define the interaction data used by cells. :class:`mcdc.Material`
-accepts native compositions and particle-specific transport-model data (e.g., neutron multigroup cross-sections).
+Materials describe the physical media that fill cells. A
+:ref:`native composition <user_native_transport>` connects
+:class:`mcdc.Material` to MC/DC's data libraries, while optional
+particle-specific data augments native interaction data or supports specialized
+and reduced transport treatments. :class:`mcdc.NeutronMultigroupData`
+represents neutron energy with discrete groups and stores groupwise macroscopic
+cross sections and related production data. :meth:`mcdc.Material.multigroup`
+provides its convenient material interface.
 
 .. autosummary::
    :toctree: generated
diff --git a/docs/source/user_guide/getting_started/first_simulation.rst b/docs/source/user_guide/getting_started/first_simulation.rst
index 84e1eb7a7..90fa0e5a9 100644
--- a/docs/source/user_guide/getting_started/first_simulation.rst
+++ b/docs/source/user_guide/getting_started/first_simulation.rst
@@ -90,10 +90,9 @@ The ``Simulation`` instance collects the model and controls its execution:
 Materials
 ~~~~~~~~~
 
-``NeutronMultigroupData`` stores the underlying multigroup neutron data.
-``Material.multigroup()`` conveniently constructs that model and attaches it to
-a ``Material``. A one-element capture array and a :math:`1 \times 1` scattering
-matrix define one-group neutron data:
+``Material.multigroup()`` creates a material for neutron multigroup transport
+and attaches the underlying ``NeutronMultigroupData``. A one-element capture
+array and a :math:`1 \times 1` scattering matrix define one-group neutron data:
 
 .. code-block:: python3
 
@@ -106,9 +105,9 @@ matrix define one-group neutron data:
        scatter=np.array([[0.3]]),
    )
 
-Native compositions use the same :class:`mcdc.Material` interface and require
-an MC/DC nuclear-data library. See :ref:`install-data-library` for configuration
-instructions.
+:ref:`Native compositions <user_native_transport>` use the same
+:class:`mcdc.Material` interface and require an MC/DC nuclear-data library. See
+:ref:`install-data-library` for configuration instructions.
 
 Geometry
 ~~~~~~~~
@@ -160,8 +159,8 @@ first cell:
 Tallies
 ~~~~~~~
 
-The structured mesh divides the domain into 60 equal spatial bins. The tally
-scores the track-length estimate of flux in each bin:
+The structured mesh divides the 6 cm domain into 60 equal spatial bins. The
+tally scores the track-length estimate of flux in each bin:
 
 .. code-block:: python3
 
@@ -207,7 +206,8 @@ Visualizing the Model
 ---------------------
 
 Before running transport, insert the following call immediately before
-``simulation.run()`` to render an x-z slice of the material geometry:
+``simulation.run()`` to render an x-z slice of the material geometry. Spatial
+coordinates are in cm and snapshot times are in seconds:
 
 .. code-block:: python3
 
diff --git a/docs/source/user_guide/materials_and_multigroup.rst b/docs/source/user_guide/materials_and_multigroup.rst
index 76a85304e..ccfb63a37 100644
--- a/docs/source/user_guide/materials_and_multigroup.rst
+++ b/docs/source/user_guide/materials_and_multigroup.rst
@@ -1,16 +1,26 @@
 .. _user_materials_and_multigroup:
 
-========================================
-Materials and Neutron Multigroup Data
-========================================
+============================
+Materials and Transport Data
+============================
 
-A :class:`mcdc.Material` may contain a native nuclide or element composition,
-neutron multigroup data, or both.
+A :class:`mcdc.Material` describes a physical medium. A nuclide or element
+composition establishes its :ref:`native transport data <user_native_transport>`.
+Materials can also carry particle-specific data that augments native
+interaction data, for example with semi-empirical information, or supports
+specialized and reduced transport treatments.
 
-Native Materials
-----------------
+.. _user_native_transport:
 
-Define a native material with either nuclide or element atomic densities:
+Native Composition and Data
+---------------------------
+
+In MC/DC, *native* refers to data-library-backed transport physics derived from
+a material's nuclide or element composition. The composition identifies the
+physical constituents whose library records provide the interaction data.
+
+Define a native material with either nuclide or element atomic densities in
+atoms/(barn cm). Material temperature is specified in K:
 
 .. code-block:: python
 
@@ -24,13 +34,24 @@ Define a native material with either nuclide or element atomic densities:
        temperature=293.6,
    )
 
-Multigroup Materials
---------------------
+Particle-specific Transport Data
+--------------------------------
+
+Particle-specific transport data is attached to the material that uses it. The
+transport physics determines when and how each dataset contributes to a
+particle interaction.
 
-:class:`mcdc.NeutronMultigroupData` stores macroscopic neutron cross sections,
-group speeds, fission spectra, and delayed-precursor data. For a material that
-uses only this transport model, :meth:`mcdc.Material.multigroup` is the concise
-entry point:
+Neutron Multigroup Transport
+----------------------------
+
+Neutron multigroup transport represents neutron energy with discrete groups
+and describes interactions using groupwise macroscopic data. It is widely used
+in general transport pedagogy and in nuclear engineering applications.
+:meth:`mcdc.Material.multigroup` creates a material with
+:class:`mcdc.NeutronMultigroupData`, which holds the cross sections, group
+speeds, production spectra, and delayed-precursor data. Macroscopic cross
+sections use cm\ :sup:`-1`, group speeds use cm/s, and precursor decay rates use
+s\ :sup:`-1`:
 
 .. code-block:: python
 
@@ -44,22 +65,24 @@ entry point:
        energy_grid=np.array([1.0e-5, 1.0, 20.0e6]),
    )
 
-Energy Grids and Representation
--------------------------------
+Multigroup Energy Grids and Representation
+------------------------------------------
 
-An explicit ``energy_grid`` contains ``G + 1`` boundaries. Group ``g`` covers
-``energy_grid[g] <= E < energy_grid[g + 1]``. The grid both maps continuous
-energy to a group and bounds continuous energy reconstructed from a group.
+An explicit ``energy_grid`` contains ``G + 1`` physical energy boundaries in
+eV. Group ``g`` covers ``energy_grid[g] <= E < energy_grid[g + 1]``. The grid
+both maps continuous energy to a group and bounds continuous energy
+reconstructed from a group.
 
 When no grid is supplied, MC/DC creates the group-coordinate grid
 ``[1.0e-6 - 0.5, 0.5, 1.5, 2.5, ...]`` with
 ``energy_representation="midpoint"``. An explicit grid also supports
 ``"log_midpoint"``, ``"uniform"``, and ``"log_uniform"`` reconstruction.
 
-Hybrid Materials
-----------------
+Combining Native and Multigroup Data
+------------------------------------
 
-A material can combine native and neutron multigroup data:
+Construct :class:`mcdc.NeutronMultigroupData` directly when attaching it to a
+material with a :ref:`native composition <user_native_transport>`:
 
 .. code-block:: python
 
@@ -91,9 +114,9 @@ multigrid option for material-local group structures:
 Source Energy and Group
 -----------------------
 
-A particle carries continuous ``energy`` and an integer ``group`` as separate
-state. :class:`mcdc.Source` accepts an independent continuous energy
-distribution and discrete group distribution:
+A particle carries continuous ``energy`` and an auxiliary integer ``group`` as
+separate state. :class:`mcdc.Source` accepts an independent continuous energy
+distribution in eV and discrete group distribution:
 
 .. code-block:: python
 
@@ -102,8 +125,8 @@ distribution and discrete group distribution:
        group=([0, 1], [0.25, 0.75]),
    )
 
-``group`` is a general transport-mode state; neutron multigroup transport uses
-it as the neutron energy-group index. If both variables are supplied, the
-group takes precedence over energy only for shared-grid neutron multigroup
-transport. The tally equivalents are the separate ``group`` and ``energy``
-filters described in :doc:`tallies`.
+The physics using ``group`` determines its meaning. Neutron multigroup
+transport uses it as the neutron energy-group index. If both variables are
+supplied, the group takes precedence over energy only for shared-grid neutron
+multigroup transport. The tally equivalents are the separate ``group`` and
+``energy`` filters described in :doc:`tallies`.
diff --git a/docs/source/user_guide/simulation_lifecycle.rst b/docs/source/user_guide/simulation_lifecycle.rst
index f28dcb5b1..271f4d015 100644
--- a/docs/source/user_guide/simulation_lifecycle.rst
+++ b/docs/source/user_guide/simulation_lifecycle.rst
@@ -23,7 +23,8 @@ the required compilation and runtime preparation automatically.
 --------------------------
 
 Materials, surfaces, cells, sources, meshes, and tallies are ordinary Python
-objects:
+objects. Here, the macroscopic cross sections are in cm\ :sup:`-1` and surface
+positions are in cm:
 
 .. code-block:: python
 
@@ -114,7 +115,8 @@ Set new raw values explicitly before recompiling when an iterative workflow chan
 4. Visualize or Run
 -------------------
 
-Visualization is a useful geometry check before transport:
+Visualization is a useful geometry check before transport. Spatial coordinates
+are in cm and snapshot times are in seconds:
 
 .. code-block:: python
 
diff --git a/docs/source/user_guide/tallies.rst b/docs/source/user_guide/tallies.rst
index c08edd92c..6deba4e1b 100644
--- a/docs/source/user_guide/tallies.rst
+++ b/docs/source/user_guide/tallies.rst
@@ -37,9 +37,10 @@ protons:
    )
 
 ``energy`` contains continuous-energy bin boundaries in eV. ``group`` contains
-boundaries for the independent integer group state used by a transport mode.
-For neutron multigroup transport, the group state is the neutron energy-group
-index; tally boundaries can coarsen several transport groups into one bin:
+boundaries for the independent auxiliary integer group state. The physics using
+the group determines its meaning. For neutron multigroup transport, it is the
+neutron energy-group index, and tally boundaries can coarsen several energy
+groups into one bin:
 
 .. code-block:: python3
 
@@ -80,7 +81,8 @@ The introductory example scores flux over a structured z mesh:
    )
    simulation.set_tallies([flux_tally])
 
-The 61 grid points define 60 spatial bins. Track-length scores include
+The grid points are positions in cm; these 61 points define 60 spatial bins.
+Track-length scores include
 ``"flux"``, ``"density"``, ``"collision"``, ``"capture"``, and
 ``"fission"``.
 
@@ -99,9 +101,10 @@ Add polar-cosine boundaries to retain angular information:
    )
    simulation.set_tallies([angular_flux_tally])
 
-The resulting tally contains 32 polar-angle bins in each spatial bin. A
-reference direction can be supplied with ``polar_reference``; its default is
-the positive z direction.
+The dimensionless polar-cosine boundaries produce 32 angular bins in each
+spatial bin. Azimuthal boundaries, when supplied with ``azi``, are in radians.
+A reference direction can be supplied with ``polar_reference``; its default is
+the positive z direction. Time-filter boundaries are in seconds.
 
 Surface-crossing Tallies
 ------------------------
@@ -205,9 +208,10 @@ Load and normalize the mesh flux with h5py:
    flux /= dz
    flux_sdev /= dz
 
-The score arrays contain values integrated over their bins. Divide by the
-applicable spatial, angular, energy, or time widths when a differential result
-is required.
+The score arrays contain values integrated over their bins. Spatial grids in
+the output retain cm, angular grids use radians or dimensionless polar cosine,
+energy grids use eV, and time grids use seconds. Divide by the applicable bin
+widths when a differential result is required.
 
 Reducing an Angular Tally
 -------------------------
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index b9d91fec2..ba89de081 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -34,15 +34,17 @@ class Material(MCDCObject):
     neutron_multigroup : NeutronMultigroupData, optional
         Groupwise macroscopic cross sections and related data for neutron
         multigroup transport, where neutron energy is represented by discrete
-        groups. When supplied with a native composition, its explicit
+        groups. When supplied with a
+        :ref:`native composition <user_native_transport>`, its explicit
         ``energy_grid`` defines the energy range where the multigroup treatment
         applies.
 
     Notes
     -----
     A nuclide or element composition connects the material to MC/DC's native
-    data libraries. Particle-specific data can augment native interaction data
-    or support specialized and reduced transport treatments.
+    transport physics through its data libraries. Particle-specific data can
+    augment native interaction data or support specialized and reduced
+    transport treatments.
     ``NeutronMultigroupData`` describes discrete neutron energy groups and
     their macroscopic interaction, production, and timing data. It can be used
     alone or alongside a native composition.
@@ -65,7 +67,7 @@ class Material(MCDCObject):
     ...     name="Absorber", capture=np.array([1.0])
     ... )
 
-    Attach native and multigroup neutron data to the same material:
+    Attach native data and multigroup neutron data to the same material:
 
     >>> hybrid_fuel = mcdc.Material(
     ...     name="Hybrid fuel",
@@ -200,6 +202,9 @@ def multigroup(
         The supplied arguments define groupwise macroscopic interaction and
         production data. This helper stores them in
         :class:`NeutronMultigroupData` and attaches the data to the material.
+        Macroscopic cross sections use ``cm^-1``, group speeds use cm/s,
+        precursor decay rates use ``s^-1``, and explicit physical energy
+        boundaries use eV.
         """
         # Build the neutron multigroup data while preserving Material as the sole type
         neutron_multigroup = NeutronMultigroupData(
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index e7a532279..be9c51c33 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -494,9 +494,26 @@ def visualize_model(
     ) -> None:
         """Render a two-dimensional material map of the compiled model.
 
-        Parameters are forwarded to :func:`mcdc.visualize.visualize_model`.
         The model is compiled first when necessary.
 
+        Parameters
+        ----------
+        vis_plane : {"xy", "xz", "yz", "yx", "zx", "zy"}
+            Coordinate plane to render. Its order sets the horizontal and
+            vertical axes.
+        x, y, z : float or sequence of 2 float
+            Slice position for the axis normal to ``vis_plane``, or plotting
+            range for an axis contained in the plane, in cm.
+        pixels : sequence of 2 int
+            Number of pixels along the two plotted axes.
+        colors : dict of Material to color or None
+            Optional material-color mapping. Matplotlib color specifications
+            are accepted.
+        time : sequence of float
+            Geometry snapshot times in seconds.
+        save_as : str or path-like or None
+            Output file name. If omitted, display the rendered image.
+
         Examples
         --------
         Render an x-z slice of the model:
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 848847649..2bfe444e7 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -66,8 +66,8 @@ class Source(MCDCObject):
         Source energy in eV. A real scalar, including a NumPy scalar, defines a
         mono-energetic source. An array-like value with shape ``(2, N)`` defines
         a tabulated distribution: the first row contains energy values and the
-        second row contains their probability density. Defaults to a
-        mono-energetic source at **1 MeV**.
+        second row contains their probability density in ``eV^-1``. Defaults
+        to a mono-energetic source at **1 MeV**.
     group : int or array_like, optional
         Auxiliary integer state assigned to an emitted particle. A Python or
         NumPy integer defines a mono-group source. An array-like value with
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index cf1daa671..343c38174 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -374,7 +374,8 @@ def Plane(
         """Create a general plane ``A*x + B*y + C*z + D = 0``.
 
         The coefficients are normalized internally. ``(A, B, C)`` must be a
-        nonzero normal vector.
+        nonzero normal vector. Coordinates are evaluated in cm, so ``D`` must
+        use the corresponding length scaling.
         """
         type_ = SURFACE_PLANE
         surface = cls(type_, name, boundary_condition)
@@ -694,7 +695,8 @@ def Quadric(
 
         The coefficients define
         ``A*x**2 + B*y**2 + C*z**2 + D*x*y + E*x*z + F*y*z
-        + G*x + H*y + I*z + J = 0``.
+        + G*x + H*y + I*z + J = 0``. Coordinates are evaluated in cm; the
+        coefficients must therefore use mutually consistent units.
         """
         type_ = SURFACE_QUADRIC
         surface = cls(type_, name, boundary_condition)
@@ -729,7 +731,8 @@ def TorusX(
     ):
         """Create a torus centered at ``(A, B, C)`` and aligned with x.
 
-        ``R`` is the major radius and ``r`` the minor radius, both in cm.
+        ``(A, B, C)`` gives the center in cm. ``R`` is the major radius and
+        ``r`` the minor radius, both in cm.
         """
         type_ = SURFACE_TORUS_X
         surface = cls(type_, name, boundary_condition)
@@ -760,7 +763,8 @@ def TorusY(
     ):
         """Create a torus centered at ``(A, B, C)`` and aligned with y.
 
-        ``R`` is the major radius and ``r`` the minor radius, both in cm.
+        ``(A, B, C)`` gives the center in cm. ``R`` is the major radius and
+        ``r`` the minor radius, both in cm.
         """
         type_ = SURFACE_TORUS_Y
         surface = cls(type_, name, boundary_condition)
@@ -791,7 +795,8 @@ def TorusZ(
     ):
         """Create a torus centered at ``(A, B, C)`` and aligned with z.
 
-        ``R`` is the major radius and ``r`` the minor radius, both in cm.
+        ``(A, B, C)`` gives the center in cm. ``R`` is the major radius and
+        ``r`` the minor radius, both in cm.
         """
         type_ = SURFACE_TORUS_Z
         surface = cls(type_, name, boundary_condition)
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index c0fea001e..9a4fef065 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -60,8 +60,8 @@ class Tally(MCDCPolymorphic):
         Scores to accumulate. Track-length scores are ``"flux"``, ``"density"``,
         ``"collision"``, ``"capture"``, and ``"fission"``; surface-crossing
         scores are ``"current-net"``, ``"current-in"``, and ``"current-out"``;
-        the collision score is ``"energy_deposition"``. Scores from different
-        estimator families cannot be mixed.
+        the collision score is ``"energy_deposition"``, scored in eV. Scores
+        from different estimator families cannot be mixed.
     surface : Surface, optional
         Surface filter. Required for a surface-crossing tally unless ``cell`` is
         provided.
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index 0589cfeec..ae4b54619 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -240,7 +240,7 @@ def __call__(self, weight_windows, mesh=None, energy=None):
         mesh : MeshUniform or MeshStructured, optional
             Spatial mesh. The default is one unbounded uniform bin.
         energy : ndarray, optional
-            Strictly increasing energy-group boundaries. The default is one
+            Strictly increasing energy boundaries in eV. The default is one
             all-energy bin.
 
         Examples
@@ -261,7 +261,7 @@ def __call__(self, weight_windows, mesh=None, energy=None):
 
         Configure both energy- and space-dependent windows:
 
-        >>> energy = np.array([0.0, 0.625e-6, 20.0])
+        >>> energy = np.array([0.0, 0.625, 20.0e6])
         >>> windows = np.tile([0.25, 0.5, 1.0], (2, 10, 1, 1, 1))
         >>> simulation.technique.weight_windows(
         ...     windows,
diff --git a/mcdc/object_/transport_model_data.py b/mcdc/object_/transport_model_data.py
index ff3f78aa9..d59dcc2a9 100644
--- a/mcdc/object_/transport_model_data.py
+++ b/mcdc/object_/transport_model_data.py
@@ -33,23 +33,24 @@ class NeutronMultigroupData(MCDCObject):
     and describes interactions using groupwise cross sections, production
     spectra, speeds, and delayed-precursor data. For a multigroup-only material,
     :meth:`mcdc.Material.multigroup` provides the convenient entry point.
-    Construct ``NeutronMultigroupData`` directly to attach it alongside a native
-    composition over the energy range defined by ``energy_grid``.
+    Construct ``NeutronMultigroupData`` directly to attach it alongside a
+    :ref:`native composition <user_native_transport>` over the energy range
+    defined by ``energy_grid``.
 
     Parameters
     ----------
     capture : array_like of float, optional
-        Capture cross section for each incoming energy group, with shape
-        ``(G,)``.
+        Macroscopic capture cross section in ``cm^-1`` for each incoming
+        energy group, with shape ``(G,)``.
     scatter : array_like of float, optional
-        Scattering-production matrix with shape ``(G, G)``, indexed as
-        ``scatter[g_out, g_in]``. Column sums define the scattering cross
-        section for each incoming group. Columns are normalized internally to
-        form the scattering spectrum.
+        Macroscopic scattering-production matrix in ``cm^-1`` with shape
+        ``(G, G)``, indexed as ``scatter[g_out, g_in]``. Column sums define the
+        scattering cross section for each incoming group. Columns are
+        normalized internally to form the scattering spectrum.
     fission : array_like of float, optional
-        Fission cross section for each incoming energy group, with shape
-        ``(G,)``. Supplying fission requires at least one of ``nu_p`` or
-        ``nu_d``.
+        Macroscopic fission cross section in ``cm^-1`` for each incoming
+        energy group, with shape ``(G,)``. Supplying fission requires at least
+        one of ``nu_p`` or ``nu_d``.
     nu_s : array_like of float, optional
         Mean number of neutrons produced per scattering event in each
         incoming group, with shape ``(G,)``. Defaults to one.
@@ -69,15 +70,16 @@ class NeutronMultigroupData(MCDCObject):
         Delayed-fission spectrum with shape ``(G, J)``, indexed as
         ``chi_d[g_out, j]``. Required when ``nu_d`` is supplied and ``G > 1``.
     speed : array_like of float, optional
-        Neutron speed in each energy group, with shape ``(G,)``. Defaults to
-        one.
+        Neutron speed in cm/s for each energy group, with shape ``(G,)``.
+        Defaults to one.
     decay_rate : array_like of float, optional
-        Decay constant for each delayed precursor group, with shape ``(J,)``.
-        Defaults to infinity.
+        Decay constant in ``s^-1`` for each delayed precursor group, with
+        shape ``(J,)``. Defaults to infinity.
     energy_grid : array_like of float, optional
-        Strictly increasing energy-group boundaries with shape ``(G + 1,)``.
-        Group ``g`` spans ``energy_grid[g] <= E < energy_grid[g + 1]``. The
-        default is the group-coordinate grid
+        Strictly increasing physical energy-group boundaries in eV with shape
+        ``(G + 1,)``. Group ``g`` spans
+        ``energy_grid[g] <= E < energy_grid[g + 1]``. The default is the
+        group-coordinate grid
         ``[1.0e-6 - 0.5, 0.5, 1.5, ...]``.
     energy_representation : str or int, optional
         Policy used to reconstruct continuous energy from a group. Midpoint
@@ -89,9 +91,9 @@ class NeutronMultigroupData(MCDCObject):
 
     Notes
     -----
-    ``G`` is inferred from ``capture``, ``scatter``, or ``fission``. Cross
-    sections are macroscopic and use inverse-length units. The generated
-    default energy grid uses the default ``"midpoint"`` representation.
+    ``G`` is inferred from ``capture``, ``scatter``, or ``fission``. The
+    generated default energy grid uses the default ``"midpoint"``
+    representation.
 
     Examples
     --------
diff --git a/mcdc/visualize.py b/mcdc/visualize.py
index b52c66ffa..bf986f349 100644
--- a/mcdc/visualize.py
+++ b/mcdc/visualize.py
@@ -19,16 +19,19 @@ def visualize_model(
 
     Parameters
     ----------
-    vis_plane : {'xy', 'yz', 'xz', 'zx', 'yz', 'zy'}
+    vis_type : {'xy', 'xz', 'yz', 'yx', 'zx', 'zy'}
         Axis plane to visualize
     x : float or array_like
-        Plane x-position (float) for 'yz' plot. Range of x-axis for 'xy' or 'xz' plot.
+        Plane x-position (float) for 'yz' plot. Range of x-axis for 'xy' or
+        'xz' plot, in cm.
     y : float or array_like
-        Plane y-position (float) for 'xz' plot. Range of y-axis for 'xy' or 'yz' plot.
+        Plane y-position (float) for 'xz' plot. Range of y-axis for 'xy' or
+        'yz' plot, in cm.
     z : float or array_like
-        Plane z-position (float) for 'xy' plot. Range of z-axis for 'xz' or 'yz' plot.
+        Plane z-position (float) for 'xy' plot. Range of z-axis for 'xz' or
+        'yz' plot, in cm.
     time : array_like
-        Times at which the geometry snapshots are taken
+        Times in seconds at which the geometry snapshots are taken
     pixels : array_like
         Number of respective pixels in the two axes in vis_plane
     colors : array_like

From 2efeca911afff0e6eed228b74df7a1ffe817faf0 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 09:36:31 +0700
Subject: [PATCH 145/202] update docs

---
 .../user_guide/materials_and_multigroup.rst   | 27 +++++++++----------
 mcdc/object_/transport_model_data.py          |  3 +--
 test/unit/test_transport_model_data.py        |  6 ++---
 3 files changed, 16 insertions(+), 20 deletions(-)

diff --git a/docs/source/user_guide/materials_and_multigroup.rst b/docs/source/user_guide/materials_and_multigroup.rst
index ccfb63a37..d65958cc7 100644
--- a/docs/source/user_guide/materials_and_multigroup.rst
+++ b/docs/source/user_guide/materials_and_multigroup.rst
@@ -42,7 +42,7 @@ transport physics determines when and how each dataset contributes to a
 particle interaction.
 
 Neutron Multigroup Transport
-----------------------------
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 Neutron multigroup transport represents neutron energy with discrete groups
 and describes interactions using groupwise macroscopic data. It is widely used
@@ -66,7 +66,7 @@ s\ :sup:`-1`:
    )
 
 Multigroup Energy Grids and Representation
-------------------------------------------
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 An explicit ``energy_grid`` contains ``G + 1`` physical energy boundaries in
 eV. Group ``g`` covers ``energy_grid[g] <= E < energy_grid[g + 1]``. The grid
@@ -74,12 +74,19 @@ both maps continuous energy to a group and bounds continuous energy
 reconstructed from a group.
 
 When no grid is supplied, MC/DC creates the group-coordinate grid
-``[1.0e-6 - 0.5, 0.5, 1.5, 2.5, ...]`` with
+``[-0.5, 0.5, 1.5, 2.5, ...]`` with
 ``energy_representation="midpoint"``. An explicit grid also supports
 ``"log_midpoint"``, ``"uniform"``, and ``"log_uniform"`` reconstruction.
 
+Neutron multigroup datasets use one shared energy grid by default. Enable the
+multigrid option when materials use different group structures:
+
+.. code-block:: python
+
+   simulation.technique.neutron_multigroup(multigrid=True)
+
 Combining Native and Multigroup Data
-------------------------------------
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 Construct :class:`mcdc.NeutronMultigroupData` directly when attaching it to a
 material with a :ref:`native composition <user_native_transport>`:
@@ -101,19 +108,9 @@ The explicit energy grid is required whenever a native composition and neutron
 multigroup data are combined. Its bounds identify the energy interval where
 the multigroup transport model is available.
 
-Shared and Material-local Grids
+Particle Energy and Group State
 -------------------------------
 
-Neutron multigroup datasets use one shared energy grid by default. Enable the
-multigrid option for material-local group structures:
-
-.. code-block:: python
-
-   simulation.technique.neutron_multigroup(multigrid=True)
-
-Source Energy and Group
------------------------
-
 A particle carries continuous ``energy`` and an auxiliary integer ``group`` as
 separate state. :class:`mcdc.Source` accepts an independent continuous energy
 distribution in eV and discrete group distribution:
diff --git a/mcdc/object_/transport_model_data.py b/mcdc/object_/transport_model_data.py
index d59dcc2a9..a6ae685a1 100644
--- a/mcdc/object_/transport_model_data.py
+++ b/mcdc/object_/transport_model_data.py
@@ -80,7 +80,7 @@ class NeutronMultigroupData(MCDCObject):
         ``(G + 1,)``. Group ``g`` spans
         ``energy_grid[g] <= E < energy_grid[g + 1]``. The default is the
         group-coordinate grid
-        ``[1.0e-6 - 0.5, 0.5, 1.5, ...]``.
+        ``[-0.5, 0.5, 1.5, ...]``.
     energy_representation : str or int, optional
         Policy used to reconstruct continuous energy from a group. Midpoint
         policies select the arithmetic or geometric midpoint; uniform policies
@@ -259,7 +259,6 @@ def __init__(
                     "energy_representation is not 'midpoint'."
                 )
             self.energy_grid = np.arange(self.G + 1, dtype=float64) - 0.5
-            self.energy_grid[0] += 1.0e-6
         else:
             if not np.all(np.isfinite(energy_grid)):
                 print_error("NeutronMultigroupData energy grid entries must be finite.")
diff --git a/test/unit/test_transport_model_data.py b/test/unit/test_transport_model_data.py
index 2c20fe6da..45ca48122 100644
--- a/test/unit/test_transport_model_data.py
+++ b/test/unit/test_transport_model_data.py
@@ -34,7 +34,7 @@ def test_zero_group_placeholder():
     assert neutron_multigroup._uses_default_energy_grid
     assert "_uses_default_energy_grid" in neutron_multigroup.non_numba
 
-    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [-0.499999])
+    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [-0.5])
     np.testing.assert_array_equal(neutron_multigroup.speed, [])
     np.testing.assert_array_equal(neutron_multigroup.decay_rate, [])
     np.testing.assert_array_equal(neutron_multigroup.capture, [])
@@ -58,7 +58,7 @@ def test_capture_only_defaults():
     assert neutron_multigroup.J == 0
     assert not neutron_multigroup.fissionable
 
-    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [-0.499999, 0.5, 1.5])
+    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [-0.5, 0.5, 1.5])
     np.testing.assert_array_equal(neutron_multigroup.speed, [1.0, 1.0])
     np.testing.assert_array_equal(neutron_multigroup.capture, [0.1, 0.2])
     np.testing.assert_array_equal(neutron_multigroup.scatter, [0.0, 0.0])
@@ -182,7 +182,7 @@ def test_standalone_mg_registration_and_packing(prepare_simulation):
     assert packed["G"] == 2
 
     np.testing.assert_array_equal(
-        get_neutron_multigroup_data.energy_grid_all(reserved, data), [-0.499999]
+        get_neutron_multigroup_data.energy_grid_all(reserved, data), [-0.5]
     )
     np.testing.assert_array_equal(
         get_neutron_multigroup_data.energy_grid_all(packed, data),

From 0c276eb173452a22633249f58351de8c9245d678 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 09:40:17 +0700
Subject: [PATCH 146/202] add mg energy rep policy to docs

---
 .../user_guide/materials_and_multigroup.rst   | 20 +++++++++++++++++--
 mcdc/object_/transport_model_data.py          |  7 ++++---
 2 files changed, 22 insertions(+), 5 deletions(-)

diff --git a/docs/source/user_guide/materials_and_multigroup.rst b/docs/source/user_guide/materials_and_multigroup.rst
index d65958cc7..a153096d8 100644
--- a/docs/source/user_guide/materials_and_multigroup.rst
+++ b/docs/source/user_guide/materials_and_multigroup.rst
@@ -75,8 +75,24 @@ reconstructed from a group.
 
 When no grid is supplied, MC/DC creates the group-coordinate grid
 ``[-0.5, 0.5, 1.5, 2.5, ...]`` with
-``energy_representation="midpoint"``. An explicit grid also supports
-``"log_midpoint"``, ``"uniform"``, and ``"log_uniform"`` reconstruction.
+``energy_representation="midpoint"``. Its reconstructed values are therefore
+the integer group coordinates ``0, 1, 2, ...``.
+
+For lower and upper group boundaries :math:`E_g` and :math:`E_{g+1}`, the
+energy-representation policies are:
+
+- ``"midpoint"``: use the arithmetic midpoint,
+  :math:`E=(E_g+E_{g+1})/2`;
+- ``"log_midpoint"``: use the geometric midpoint,
+  :math:`E=\sqrt{E_g E_{g+1}}`;
+- ``"uniform"``: sample :math:`E` uniformly between the two boundaries; and
+- ``"log_uniform"``: sample :math:`\log E` uniformly between their logarithms,
+  equivalently :math:`E=E_g(E_{g+1}/E_g)^\xi` for
+  :math:`\xi\sim\mathcal{U}(0,1)`.
+
+The logarithmic policies require strictly positive energy boundaries. Midpoint
+policies reconstruct one deterministic value per group, while uniform policies
+sample a new value when continuous energy is reconstructed.
 
 Neutron multigroup datasets use one shared energy grid by default. Enable the
 multigrid option when materials use different group structures:
diff --git a/mcdc/object_/transport_model_data.py b/mcdc/object_/transport_model_data.py
index a6ae685a1..f91779cf0 100644
--- a/mcdc/object_/transport_model_data.py
+++ b/mcdc/object_/transport_model_data.py
@@ -82,9 +82,10 @@ class NeutronMultigroupData(MCDCObject):
         group-coordinate grid
         ``[-0.5, 0.5, 1.5, ...]``.
     energy_representation : str or int, optional
-        Policy used to reconstruct continuous energy from a group. Midpoint
-        policies select the arithmetic or geometric midpoint; uniform policies
-        sample uniformly in energy or log-energy. The default is
+        Policy used to reconstruct continuous energy from a group.
+        ``"midpoint"`` uses the arithmetic midpoint, ``"log_midpoint"`` uses
+        the geometric midpoint, ``"uniform"`` samples uniformly in energy,
+        and ``"log_uniform"`` samples uniformly in log-energy. The default is
         ``"midpoint"``. Logarithmic policies require positive boundaries.
         The corresponding ``NEUTRON_MULTIGROUP_ENERGY_*`` integer constants
         are also accepted.

From 59b98d3fddb322040cad5f0be94ac22281aea87b Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 09:48:02 +0700
Subject: [PATCH 147/202] reformat, one-sentence one-line

---
 docs/source/contributing/index.rst            |  45 +++-----
 docs/source/reference/python_api/index.rst    |  64 ++++-------
 .../getting_started/first_simulation.rst      | 106 +++++++-----------
 .../user_guide/materials_and_multigroup.rst   |  91 ++++++---------
 .../user_guide/simulation_lifecycle.rst       |  79 +++++--------
 docs/source/user_guide/tallies.rst            |  85 ++++++--------
 6 files changed, 181 insertions(+), 289 deletions(-)

diff --git a/docs/source/contributing/index.rst b/docs/source/contributing/index.rst
index 221456e95..698db5278 100644
--- a/docs/source/contributing/index.rst
+++ b/docs/source/contributing/index.rst
@@ -4,19 +4,16 @@
 Contributing
 ============
 
-This guide describes the repository workflow and quality checks for
-contributing to MC/DC. It is intended for both occasional contributors and
-project maintainers.
+This guide describes the repository workflow and quality checks for contributing to MC/DC.
+It is intended for both occasional contributors and project maintainers.
 
-Start with the setup steps below. Use :doc:`continuous_integration` to
-understand automated checks and :doc:`container_development` when developing in
-the project container. Use :doc:`example_validation` when changing the public
-API or example problems. Read :doc:`pull_requests` before preparing a
-contribution. For software architecture and documentation practices, see the
-:doc:`../developer_guide/index`.
+Start with the setup steps below.
+Use :doc:`continuous_integration` to understand automated checks and :doc:`container_development` when developing in the project container.
+Use :doc:`example_validation` when changing the public API or example problems.
+Read :doc:`pull_requests` before preparing a contribution.
+For software architecture and documentation practices, see the :doc:`../developer_guide/index`.
 
-For implementation guidance specific to compiled transport functions, see
-:doc:`../developer_guide/extending/writing_numba_compatible_transport_code`.
+For implementation guidance specific to compiled transport functions, see :doc:`../developer_guide/extending/writing_numba_compatible_transport_code`.
 
 Contributions target the ``dev`` branch. To prepare a development checkout:
 
@@ -36,10 +33,8 @@ Development Workflow
    example_validation
    pull_requests
 
-MC/DC documentation is an important part of the project and evolves alongside
-the codebase. The :doc:`../developer_guide/documentation/index` guide describes
-the documentation philosophy, writing guidelines, and the tools used to build
-and maintain the documentation.
+MC/DC documentation is an important part of the project and evolves alongside the codebase.
+The :doc:`../developer_guide/documentation/index` guide describes the documentation philosophy, writing guidelines, and the tools used to build and maintain the documentation.
 
 Please note our `code of conduct <https://github.com/mcdc-project/mcdc/blob/dev/CODE_OF_CONDUCT.md>`_, which we take seriously.
 
@@ -115,11 +110,9 @@ However if absolutely required by users numba does allow for some `cache sharing
 Adding a New Input
 ------------------
 
-For architectural guidance on adding a model field, embedded configuration,
-registered object category, or polymorphic subtype, see
-:doc:`../developer_guide/extending/extending_the_object_model`. Public model
-classes and configuration are primarily defined in ``mcdc/object_/``. Common
-input-related locations include:
+For architectural guidance on adding a model field, embedded configuration, registered object category, or polymorphic subtype, see :doc:`../developer_guide/extending/extending_the_object_model`.
+Public model classes and configuration are primarily defined in ``mcdc/object_/``.
+Common input-related locations include:
 
 #. ``mcdc/object_/settings.py`` — simulation settings and k-eigenvalue parameters
 #. ``mcdc/object_/material.py`` — material and composition definition
@@ -135,8 +128,7 @@ input-related locations include:
 Testing
 -------
 
-See :doc:`continuous_integration` for more information on how we run these
-tests automatically.
+See :doc:`continuous_integration` for more information on how we run these tests automatically.
 
 MC/DC has a robust testing suite that your changes must be able to pass before a PR is accepted.
 Unit tests for functions that have them are ran in a pure python from.
@@ -198,10 +190,7 @@ If you are wondering accommodations.
 Adding Documentation
 --------------------
 
-Documentation is a core part of MC/DC. Contributions that introduce new
-features, modify existing behavior, or change developer workflows should update
-the relevant documentation accordingly.
+Documentation is a core part of MC/DC.
+Contributions that introduce new features, modify existing behavior, or change developer workflows should update the relevant documentation accordingly.
 
-See the :doc:`../developer_guide/documentation/index` guide for documentation
-philosophy, writing
-guidelines, and instructions for contributing to the documentation.
+See the :doc:`../developer_guide/documentation/index` guide for documentation philosophy, writing guidelines, and instructions for contributing to the documentation.
diff --git a/docs/source/reference/python_api/index.rst b/docs/source/reference/python_api/index.rst
index 126673efd..ad2f78eb3 100644
--- a/docs/source/reference/python_api/index.rst
+++ b/docs/source/reference/python_api/index.rst
@@ -4,12 +4,10 @@
 Python API
 ==========
 
-The MC/DC public API is centered on :class:`mcdc.Simulation`. A simulation owns
-the model geometry and material, sources, tallies, settings, transport
-techniques, and runtime state needed for one calculation.
+The MC/DC public API is centered on :class:`mcdc.Simulation`.
+A simulation owns the model geometry and material, sources, tallies, settings, transport techniques, and runtime state needed for one calculation.
 
-Build the model with the public objects listed below, attach its root cells,
-sources, and tallies to a simulation, and then visualize or run that simulation:
+Build the model with the public objects listed below, attach its root cells, sources, and tallies to a simulation, and then visualize or run that simulation:
 
 .. code-block:: python
 
@@ -20,10 +18,8 @@ sources, and tallies to a simulation, and then visualize or run that simulation:
    simulation.settings.N_particle = 10_000
    simulation.run()
 
-The complete public interfaces and additional examples are documented on each
-linked API page. For a task-oriented explanation of how these objects move
-through construction, compilation, execution, and output, see
-:doc:`../../user_guide/simulation_lifecycle`.
+The complete public interfaces and additional examples are documented on each linked API page.
+For a task-oriented explanation of how these objects move through construction, compilation, execution, and output, see :doc:`../../user_guide/simulation_lifecycle`.
 
 
 Simulation
@@ -43,14 +39,10 @@ Model building blocks
 Materials
 ^^^^^^^^^
 
-Materials describe the physical media that fill cells. A
-:ref:`native composition <user_native_transport>` connects
-:class:`mcdc.Material` to MC/DC's data libraries, while optional
-particle-specific data augments native interaction data or supports specialized
-and reduced transport treatments. :class:`mcdc.NeutronMultigroupData`
-represents neutron energy with discrete groups and stores groupwise macroscopic
-cross sections and related production data. :meth:`mcdc.Material.multigroup`
-provides its convenient material interface.
+Materials describe the physical media that fill cells.
+A :ref:`native composition <user_native_transport>` connects :class:`mcdc.Material` to MC/DC's data libraries, while optional particle-specific data augments native interaction data or supports specialized and reduced transport treatments.
+:class:`mcdc.NeutronMultigroupData` represents neutron energy with discrete groups and stores groupwise macroscopic cross sections and related production data.
+:meth:`mcdc.Material.multigroup` provides its convenient material interface.
 
 .. autosummary::
    :toctree: generated
@@ -64,8 +56,7 @@ provides its convenient material interface.
 Geometry
 ^^^^^^^^
 
-Surfaces bound spatial regions, cells pair those regions with materials or
-universes, and universes and lattices organize repeated geometry.
+Surfaces bound spatial regions, cells pair those regions with materials or universes, and universes and lattices organize repeated geometry.
 
 .. autosummary::
    :toctree: generated
@@ -94,8 +85,7 @@ Sources describe the distribution of the initial particle population in the simu
 Tallies
 ^^^^^^^
 
-Tallies define the quantities to score and the filters over which those scores
-are accumulated.
+Tallies define the quantities to score and the filters over which those scores are accumulated.
 
 .. autosummary::
    :toctree: generated
@@ -108,8 +98,7 @@ are accumulated.
 Meshes
 ^^^^^^
 
-Meshes provide spatial bins for mesh-filtered tallies and transport
-techniques.
+Meshes provide spatial bins for mesh-filtered tallies and transport techniques.
 
 .. autosummary::
    :toctree: generated
@@ -127,31 +116,22 @@ Simulation settings
 ^^^^^^^^^^^^^^^^^^^
 
 Each :class:`mcdc.Simulation` owns its settings at ``simulation.settings``.
-Settings control particle histories, batches, random-number generation,
-transport modes, census times, particle banks, output, and GPU execution.
-Specialized modes are configured through methods such as
-``simulation.settings.set_eigenmode(...)`` and
-``simulation.settings.set_time_census(...)``. See :class:`mcdc.Simulation` for
-the complete settings interface.
+Settings control particle histories, batches, random-number generation, transport modes, census times, particle banks, output, and GPU execution.
+Specialized modes are configured through methods such as ``simulation.settings.set_eigenmode(...)`` and ``simulation.settings.set_time_census(...)``.
+See :class:`mcdc.Simulation` for the complete settings interface.
 
 Transport techniques
 ^^^^^^^^^^^^^^^^^^^^
 
-Transport techniques are grouped under ``simulation.technique``. For example,
-enable implicit capture with ``simulation.technique.implicit_capture()`` or
-allow material-local neutron group structures with
-``simulation.technique.neutron_multigroup(multigrid=True)``. See
-:class:`mcdc.Simulation` for the ownership model and examples.
+Transport techniques are grouped under ``simulation.technique``.
+For example, enable implicit capture with ``simulation.technique.implicit_capture()`` or allow material-local neutron group structures with ``simulation.technique.neutron_multigroup(multigrid=True)``.
+See :class:`mcdc.Simulation` for the ownership model and examples.
 
 Compiling and running
 ^^^^^^^^^^^^^^^^^^^^^
 
-Calling ``simulation.run()`` compiles the current Python object graph when
-needed, executes particle transport, and writes the configured output.
-``simulation.visualize_model(...)`` similarly compiles when needed before
-rendering the model. Use ``simulation.compile()`` when an explicit compiled
-snapshot is required before either operation.
+Calling ``simulation.run()`` compiles the current Python object graph when needed, executes particle transport, and writes the configured output.
+``simulation.visualize_model(...)`` similarly compiles when needed before rendering the model.
+Use ``simulation.compile()`` when an explicit compiled snapshot is required before either operation.
 
-The internal compilation and packing stages are documented in
-:doc:`../../developer_guide/architecture/simulation_compilation` and
-:doc:`../../developer_guide/architecture/runtime_data_layout`.
+The internal compilation and packing stages are documented in :doc:`../../developer_guide/architecture/simulation_compilation` and :doc:`../../developer_guide/architecture/runtime_data_layout`.
diff --git a/docs/source/user_guide/getting_started/first_simulation.rst b/docs/source/user_guide/getting_started/first_simulation.rst
index 90fa0e5a9..66e9e67d0 100644
--- a/docs/source/user_guide/getting_started/first_simulation.rst
+++ b/docs/source/user_guide/getting_started/first_simulation.rst
@@ -4,20 +4,16 @@
 First MC/DC Simulation
 ======================
 
-This tutorial constructs and runs a one-group shielding calculation. It assumes
-familiarity with the basic concepts of Monte Carlo radiation transport.
+This tutorial constructs and runs a one-group shielding calculation.
+It assumes familiarity with the basic concepts of Monte Carlo radiation transport.
 
-Monte Carlo transport inputs are generally assembled from the same core
-components: materials, geometry, particle sources, tallies, and simulation
-settings. In MC/DC, these components are represented by Python objects and
-assembled into a :class:`mcdc.Simulation`.
+Monte Carlo transport inputs are generally assembled from the same core components: materials, geometry, particle sources, tallies, and simulation settings.
+In MC/DC, these components are represented by Python objects and assembled into a :class:`mcdc.Simulation`.
 
-This tutorial applies the general :doc:`../simulation_lifecycle` to one
-complete problem.
+This tutorial applies the general :doc:`../simulation_lifecycle` to one complete problem.
 
-The example uses multigroup data defined directly in the input, so it does not
-require an external nuclear-data library. Its complete, executable source is
-available in ``examples/slab_shielding``.
+The example uses multigroup data defined directly in the input, so it does not require an external nuclear-data library.
+Its complete, executable source is available in ``examples/slab_shielding``.
 
 MC/DC Workflow
 --------------
@@ -32,9 +28,8 @@ An MC/DC calculation follows five main steps:
 
 .. important::
 
-   Validate the geometry, source distribution, tally definitions, and settings
-   before interpreting simulation results. A successfully executed calculation
-   is not necessarily a correctly specified physical model.
+   Validate the geometry, source distribution, tally definitions, and settings before interpreting simulation results.
+   A successfully executed calculation is not necessarily a correctly specified physical model.
 
 Problem Description
 -------------------
@@ -44,9 +39,8 @@ The model contains two adjacent slab regions:
 - A mostly scattering source region over :math:`0 < z < 2` cm.
 - A more strongly absorbing shield over :math:`2 < z < 6` cm.
 
-Both outer boundaries are vacuum. Particles are emitted isotropically
-throughout the source region, and a mesh tally records the flux across the
-entire domain.
+Both outer boundaries are vacuum.
+Particles are emitted isotropically throughout the source region, and a mesh tally records the flux across the entire domain.
 
 .. list-table:: One-group material data
    :header-rows: 1
@@ -66,8 +60,7 @@ entire domain.
      - 0.3
 
 The total cross section is :math:`1.0\ \text{cm}^{-1}` in both regions.
-Changing the capture-to-scatter ratio isolates the effect of the shield on the
-flux distribution.
+Changing the capture-to-scatter ratio isolates the effect of the shield on the flux distribution.
 
 Building the Input
 ------------------
@@ -90,9 +83,8 @@ The ``Simulation`` instance collects the model and controls its execution:
 Materials
 ~~~~~~~~~
 
-``Material.multigroup()`` creates a material for neutron multigroup transport
-and attaches the underlying ``NeutronMultigroupData``. A one-element capture
-array and a :math:`1 \times 1` scattering matrix define one-group neutron data:
+``Material.multigroup()`` creates a material for neutron multigroup transport and attaches the underlying ``NeutronMultigroupData``.
+A one-element capture array and a :math:`1 \times 1` scattering matrix define one-group neutron data:
 
 .. code-block:: python3
 
@@ -105,15 +97,14 @@ array and a :math:`1 \times 1` scattering matrix define one-group neutron data:
        scatter=np.array([[0.3]]),
    )
 
-:ref:`Native compositions <user_native_transport>` use the same
-:class:`mcdc.Material` interface and require an MC/DC nuclear-data library. See
-:ref:`install-data-library` for configuration instructions.
+:ref:`Native compositions <user_native_transport>` use the same :class:`mcdc.Material` interface and require an MC/DC nuclear-data library.
+See :ref:`install-data-library` for configuration instructions.
 
 Geometry
 ~~~~~~~~
 
-Three z-planes define the two slab regions. The outer planes use vacuum
-boundary conditions; the plane at :math:`z=2` cm is an internal interface:
+Three z-planes define the two slab regions.
+The outer planes use vacuum boundary conditions; the plane at :math:`z=2` cm is an internal interface:
 
 .. code-block:: python3
 
@@ -121,9 +112,8 @@ boundary conditions; the plane at :math:`z=2` cm is an internal interface:
    interface = mcdc.Surface.PlaneZ(z=2.0)
    right = mcdc.Surface.PlaneZ(z=6.0, boundary_condition="vacuum")
 
-A cell combines a region with the material that fills it. A positive
-half-space selects points above a ``PlaneZ``, while a negative half-space
-selects points below it:
+A cell combines a region with the material that fills it.
+A positive half-space selects points above a ``PlaneZ``, while a negative half-space selects points below it:
 
 .. code-block:: python3
 
@@ -137,15 +127,13 @@ selects points below it:
    )
    simulation.set_model([source_cell, shield_cell])
 
-The cells are the roots of the geometry. MC/DC reaches their materials and
-surfaces when it compiles the simulation, so those objects do not require
-separate setter calls.
+The cells are the roots of the geometry.
+MC/DC reaches their materials and surfaces when it compiles the simulation, so those objects do not require separate setter calls.
 
 Source
 ~~~~~~
 
-The source emits group-0 particles isotropically and uniformly throughout the
-first cell:
+The source emits group-0 particles isotropically and uniformly throughout the first cell:
 
 .. code-block:: python3
 
@@ -159,8 +147,8 @@ first cell:
 Tallies
 ~~~~~~~
 
-The structured mesh divides the 6 cm domain into 60 equal spatial bins. The
-tally scores the track-length estimate of flux in each bin:
+The structured mesh divides the 6 cm domain into 60 equal spatial bins.
+The tally scores the track-length estimate of flux in each bin:
 
 .. code-block:: python3
 
@@ -172,15 +160,13 @@ tally scores the track-length estimate of flux in each bin:
    )
    simulation.set_tallies([flux_tally])
 
-Naming the tally makes its location in the output file predictable:
-``tallies/slab_flux``.
+Naming the tally makes its location in the output file predictable: ``tallies/slab_flux``.
 
 Settings and Execution
 ~~~~~~~~~~~~~~~~~~~~~~
 
-This example runs 1,000 particle histories in each of 10 statistically
-independent batches. Multiple batches allow MC/DC to estimate the standard
-deviation of each tally bin:
+This example runs 1,000 particle histories in each of 10 statistically independent batches.
+Multiple batches allow MC/DC to estimate the standard deviation of each tally bin:
 
 .. code-block:: python3
 
@@ -195,8 +181,7 @@ The calculation writes its results to ``slab_shielding.h5``.
 Complete Input
 --------------
 
-The complete runnable input is embedded directly from
-``examples/slab_shielding/input.py``:
+The complete runnable input is embedded directly from ``examples/slab_shielding/input.py``:
 
 .. literalinclude:: ../../../../examples/slab_shielding/input.py
    :language: python
@@ -205,9 +190,8 @@ The complete runnable input is embedded directly from
 Visualizing the Model
 ---------------------
 
-Before running transport, insert the following call immediately before
-``simulation.run()`` to render an x-z slice of the material geometry. Spatial
-coordinates are in cm and snapshot times are in seconds:
+Before running transport, insert the following call immediately before ``simulation.run()`` to render an x-z slice of the material geometry.
+Spatial coordinates are in cm and snapshot times are in seconds:
 
 .. code-block:: python3
 
@@ -222,8 +206,8 @@ coordinates are in cm and snapshot times are in seconds:
        save_as="slab_shielding_geometry",
    )
 
-The image is saved as ``slab_shielding_geometry.png``. Visualization compiles
-the current model when necessary.
+The image is saved as ``slab_shielding_geometry.png``.
+Visualization compiles the current model when necessary.
 
 Running the Example
 -------------------
@@ -235,33 +219,28 @@ Enter the problem directory, then run the input in pure Python mode:
    cd examples/slab_shielding
    python input.py
 
-Pure Python mode avoids compilation overhead and is suitable for checking a
-small model. For accelerated or parallel calculations, see
-:doc:`../execution/cpu`, :doc:`../execution/gpu`, and
-:doc:`../execution/batch_systems`.
+Pure Python mode avoids compilation overhead and is suitable for checking a small model.
+For accelerated or parallel calculations, see :doc:`../execution/cpu`, :doc:`../execution/gpu`, and :doc:`../execution/batch_systems`.
 
 Post-processing
 ---------------
 
-MC/DC writes tally results and runtime information to HDF5. The companion
-script reads the spatial grid, normalizes the flux and standard deviation by
-the mesh-bin widths, and plots the result:
+MC/DC writes tally results and runtime information to HDF5.
+The companion script reads the spatial grid, normalizes the flux and standard deviation by the mesh-bin widths, and plots the result:
 
 .. literalinclude:: ../../../../examples/slab_shielding/process-output.py
    :language: python
    :linenos:
 
-After the transport calculation finishes, run the companion script from the
-same problem directory:
+After the transport calculation finishes, run the companion script from the same problem directory:
 
 .. code-block:: sh
 
    python process-output.py
 
-The script writes ``slab_shielding_flux.png``. The dashed line marks the
-material interface at :math:`z=2` cm. The flux is expected to decrease more
-rapidly in the shield because capture accounts for a larger fraction of its
-total cross section.
+The script writes ``slab_shielding_flux.png``.
+The dashed line marks the material interface at :math:`z=2` cm.
+The flux is expected to decrease more rapidly in the shield because capture accounts for a larger fraction of its total cross section.
 
 Next Steps
 ----------
@@ -274,5 +253,4 @@ After running the original problem, useful variations include:
 - Add an energy group or another spatial region.
 - Add a surface-crossing tally at the material interface.
 
-See :doc:`../../examples/index` for examples involving lattices, moving geometry,
-time-dependent transport, and reactor benchmarks.
+See :doc:`../../examples/index` for examples involving lattices, moving geometry, time-dependent transport, and reactor benchmarks.
diff --git a/docs/source/user_guide/materials_and_multigroup.rst b/docs/source/user_guide/materials_and_multigroup.rst
index a153096d8..265e4067d 100644
--- a/docs/source/user_guide/materials_and_multigroup.rst
+++ b/docs/source/user_guide/materials_and_multigroup.rst
@@ -4,23 +4,20 @@
 Materials and Transport Data
 ============================
 
-A :class:`mcdc.Material` describes a physical medium. A nuclide or element
-composition establishes its :ref:`native transport data <user_native_transport>`.
-Materials can also carry particle-specific data that augments native
-interaction data, for example with semi-empirical information, or supports
-specialized and reduced transport treatments.
+A :class:`mcdc.Material` describes a physical medium.
+A nuclide or element composition establishes its :ref:`native transport data <user_native_transport>`.
+Materials can also carry particle-specific data that augments native interaction data, for example with semi-empirical information, or supports specialized and reduced transport treatments.
 
 .. _user_native_transport:
 
 Native Composition and Data
 ---------------------------
 
-In MC/DC, *native* refers to data-library-backed transport physics derived from
-a material's nuclide or element composition. The composition identifies the
-physical constituents whose library records provide the interaction data.
+In MC/DC, *native* refers to data-library-backed transport physics derived from a material's nuclide or element composition.
+The composition identifies the physical constituents whose library records provide the interaction data.
 
-Define a native material with either nuclide or element atomic densities in
-atoms/(barn cm). Material temperature is specified in K:
+Define a native material with either nuclide or element atomic densities in atoms/(barn cm).
+Material temperature is specified in K:
 
 .. code-block:: python
 
@@ -37,21 +34,16 @@ atoms/(barn cm). Material temperature is specified in K:
 Particle-specific Transport Data
 --------------------------------
 
-Particle-specific transport data is attached to the material that uses it. The
-transport physics determines when and how each dataset contributes to a
-particle interaction.
+Particle-specific transport data is attached to the material that uses it.
+The transport physics determines when and how each dataset contributes to a particle interaction.
 
 Neutron Multigroup Transport
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-Neutron multigroup transport represents neutron energy with discrete groups
-and describes interactions using groupwise macroscopic data. It is widely used
-in general transport pedagogy and in nuclear engineering applications.
-:meth:`mcdc.Material.multigroup` creates a material with
-:class:`mcdc.NeutronMultigroupData`, which holds the cross sections, group
-speeds, production spectra, and delayed-precursor data. Macroscopic cross
-sections use cm\ :sup:`-1`, group speeds use cm/s, and precursor decay rates use
-s\ :sup:`-1`:
+Neutron multigroup transport represents neutron energy with discrete groups and describes interactions using groupwise macroscopic data.
+It is widely used in general transport pedagogy and in nuclear engineering applications.
+:meth:`mcdc.Material.multigroup` creates a material with :class:`mcdc.NeutronMultigroupData`, which holds the cross sections, group speeds, production spectra, and delayed-precursor data.
+Macroscopic cross sections use cm\ :sup:`-1`, group speeds use cm/s, and precursor decay rates use s\ :sup:`-1`:
 
 .. code-block:: python
 
@@ -68,34 +60,25 @@ s\ :sup:`-1`:
 Multigroup Energy Grids and Representation
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-An explicit ``energy_grid`` contains ``G + 1`` physical energy boundaries in
-eV. Group ``g`` covers ``energy_grid[g] <= E < energy_grid[g + 1]``. The grid
-both maps continuous energy to a group and bounds continuous energy
-reconstructed from a group.
+An explicit ``energy_grid`` contains ``G + 1`` physical energy boundaries in eV.
+Group ``g`` covers ``energy_grid[g] <= E < energy_grid[g + 1]``.
+The grid both maps continuous energy to a group and bounds continuous energy reconstructed from a group.
 
-When no grid is supplied, MC/DC creates the group-coordinate grid
-``[-0.5, 0.5, 1.5, 2.5, ...]`` with
-``energy_representation="midpoint"``. Its reconstructed values are therefore
-the integer group coordinates ``0, 1, 2, ...``.
+When no grid is supplied, MC/DC creates the group-coordinate grid ``[-0.5, 0.5, 1.5, 2.5, ...]`` with ``energy_representation="midpoint"``.
+Its reconstructed values are therefore the integer group coordinates ``0, 1, 2, ...``.
 
-For lower and upper group boundaries :math:`E_g` and :math:`E_{g+1}`, the
-energy-representation policies are:
+For lower and upper group boundaries :math:`E_g` and :math:`E_{g+1}`, the energy-representation policies are:
 
-- ``"midpoint"``: use the arithmetic midpoint,
-  :math:`E=(E_g+E_{g+1})/2`;
-- ``"log_midpoint"``: use the geometric midpoint,
-  :math:`E=\sqrt{E_g E_{g+1}}`;
+- ``"midpoint"``: use the arithmetic midpoint, :math:`E=(E_g+E_{g+1})/2`;
+- ``"log_midpoint"``: use the geometric midpoint, :math:`E=\sqrt{E_g E_{g+1}}`;
 - ``"uniform"``: sample :math:`E` uniformly between the two boundaries; and
-- ``"log_uniform"``: sample :math:`\log E` uniformly between their logarithms,
-  equivalently :math:`E=E_g(E_{g+1}/E_g)^\xi` for
-  :math:`\xi\sim\mathcal{U}(0,1)`.
+- ``"log_uniform"``: sample :math:`\log E` uniformly between their logarithms, equivalently :math:`E=E_g(E_{g+1}/E_g)^\xi` for :math:`\xi\sim\mathcal{U}(0,1)`.
 
-The logarithmic policies require strictly positive energy boundaries. Midpoint
-policies reconstruct one deterministic value per group, while uniform policies
-sample a new value when continuous energy is reconstructed.
+The logarithmic policies require strictly positive energy boundaries.
+Midpoint policies reconstruct one deterministic value per group, while uniform policies sample a new value when continuous energy is reconstructed.
 
-Neutron multigroup datasets use one shared energy grid by default. Enable the
-multigrid option when materials use different group structures:
+Neutron multigroup datasets use one shared energy grid by default.
+Enable the multigrid option when materials use different group structures:
 
 .. code-block:: python
 
@@ -104,8 +87,7 @@ multigrid option when materials use different group structures:
 Combining Native and Multigroup Data
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-Construct :class:`mcdc.NeutronMultigroupData` directly when attaching it to a
-material with a :ref:`native composition <user_native_transport>`:
+Construct :class:`mcdc.NeutronMultigroupData` directly when attaching it to a material with a :ref:`native composition <user_native_transport>`:
 
 .. code-block:: python
 
@@ -120,16 +102,14 @@ material with a :ref:`native composition <user_native_transport>`:
        ),
    )
 
-The explicit energy grid is required whenever a native composition and neutron
-multigroup data are combined. Its bounds identify the energy interval where
-the multigroup transport model is available.
+The explicit energy grid is required whenever a native composition and neutron multigroup data are combined.
+Its bounds identify the energy interval where the multigroup transport model is available.
 
 Particle Energy and Group State
 -------------------------------
 
-A particle carries continuous ``energy`` and an auxiliary integer ``group`` as
-separate state. :class:`mcdc.Source` accepts an independent continuous energy
-distribution in eV and discrete group distribution:
+A particle carries continuous ``energy`` and an auxiliary integer ``group`` as separate state.
+:class:`mcdc.Source` accepts an independent continuous energy distribution in eV and discrete group distribution:
 
 .. code-block:: python
 
@@ -138,8 +118,7 @@ distribution in eV and discrete group distribution:
        group=([0, 1], [0.25, 0.75]),
    )
 
-The physics using ``group`` determines its meaning. Neutron multigroup
-transport uses it as the neutron energy-group index. If both variables are
-supplied, the group takes precedence over energy only for shared-grid neutron
-multigroup transport. The tally equivalents are the separate ``group`` and
-``energy`` filters described in :doc:`tallies`.
+The physics using ``group`` determines its meaning.
+Neutron multigroup transport uses it as the neutron energy-group index.
+If both variables are supplied, the group takes precedence over energy only for shared-grid neutron multigroup transport.
+The tally equivalents are the separate ``group`` and ``energy`` filters described in :doc:`tallies`.
diff --git a/docs/source/user_guide/simulation_lifecycle.rst b/docs/source/user_guide/simulation_lifecycle.rst
index 271f4d015..a1b342086 100644
--- a/docs/source/user_guide/simulation_lifecycle.rst
+++ b/docs/source/user_guide/simulation_lifecycle.rst
@@ -4,9 +4,8 @@
 Simulation Lifecycle
 ====================
 
-An MC/DC calculation is owned by a :class:`mcdc.Simulation`. The simulation
-collects one model, its sources and tallies, its settings and techniques, and
-the runtime state needed to visualize or execute it.
+An MC/DC calculation is owned by a :class:`mcdc.Simulation`.
+The simulation collects one model, its sources and tallies, its settings and techniques, and the runtime state needed to visualize or execute it.
 
 The normal workflow has five stages:
 
@@ -16,15 +15,14 @@ The normal workflow has five stages:
 #. Visualize or run the prepared model.
 #. Generate and post-process output.
 
-Most inputs call only ``visualize_model`` or ``run`` explicitly. MC/DC performs
-the required compilation and runtime preparation automatically.
+Most inputs call only ``visualize_model`` or ``run`` explicitly.
+MC/DC performs the required compilation and runtime preparation automatically.
 
 1. Construct Model Objects
 --------------------------
 
-Materials, surfaces, cells, sources, meshes, and tallies are ordinary Python
-objects. Here, the macroscopic cross sections are in cm\ :sup:`-1` and surface
-positions are in cm:
+Materials, surfaces, cells, sources, meshes, and tallies are ordinary Python objects.
+Here, the macroscopic cross sections are in cm\ :sup:`-1` and surface positions are in cm:
 
 .. code-block:: python
 
@@ -36,14 +34,13 @@ positions are in cm:
    right = mcdc.Surface.PlaneZ(z=2.0, boundary_condition="vacuum")
    cell = mcdc.Cell(region=+left & -right, fill=material)
 
-Objects can refer to other objects. In this example the cell retains its
-region, the region retains its surfaces, and the cell retains its material.
+Objects can refer to other objects.
+In this example the cell retains its region, the region retains its surfaces, and the cell retains its material.
 
 2. Attach Roots to a Simulation
 -------------------------------
 
-Create a simulation and attach the roots from which MC/DC can discover the
-complete model:
+Create a simulation and attach the roots from which MC/DC can discover the complete model:
 
 .. code-block:: python
 
@@ -52,13 +49,11 @@ complete model:
    simulation.set_sources([source])
    simulation.set_tallies([tally])
 
-``set_model`` accepts the cells in the root universe. Materials, surfaces,
-child universes, lattices, and meshes that are reachable from those cells do
-not need separate registration calls.
+``set_model`` accepts the cells in the root universe.
+Materials, surfaces, child universes, lattices, and meshes that are reachable from those cells do not need separate registration calls.
 
-Sources and tallies are explicit roots because they are not necessarily
-reachable from the geometry. Settings and techniques belong directly to the
-simulation:
+Sources and tallies are explicit roots because they are not necessarily reachable from the geometry.
+Settings and techniques belong directly to the simulation:
 
 .. code-block:: python
 
@@ -72,27 +67,22 @@ Process Ownership
 ^^^^^^^^^^^^^^^^^
 
 MC/DC runs one active simulation context at a time within a Python process.
-Objects may be shared within one model—for example, several cells may use the
-same material—but the same object instance should not be attached to different
-``Simulation`` instances.
+Objects may be shared within one model—for example, several cells may use the same material—but the same object instance should not be attached to different ``Simulation`` instances.
 
-Multiple simulations can be constructed in one process when they have
-independent object graphs and are run serially. For concurrent calculations,
-construct each model and run its simulation in a separate process. A Python
-driver, workflow system, or batch scheduler can manage those processes.
+Multiple simulations can be constructed in one process when they have independent object graphs and are run serially.
+For concurrent calculations, construct each model and run its simulation in a separate process.
+A Python driver, workflow system, or batch scheduler can manage those processes.
 
 3. Compile the Object Graph
 ---------------------------
 
-Compilation discovers every object reachable from the simulation, registers
-shared objects once, and assigns simulation-local IDs. Normally it is
-automatic:
+Compilation discovers every object reachable from the simulation, registers shared objects once, and assigns simulation-local IDs.
+Normally it is automatic:
 
 - ``simulation.visualize_model(...)`` compiles when needed.
 - ``simulation.run()`` compiles when needed.
 
-Call ``simulation.compile()`` directly only when you need to inspect the
-compiled object lists or IDs before visualization or execution:
+Call ``simulation.compile()`` directly only when you need to inspect the compiled object lists or IDs before visualization or execution:
 
 .. code-block:: python
 
@@ -100,13 +90,11 @@ compiled object lists or IDs before visualization or execution:
    print(simulation.cells)
    print(material.ID)
 
-Compiled IDs describe one snapshot and may change after recompilation. Do not
-use them as persistent identifiers in an input or post-processing workflow.
+Compiled IDs describe one snapshot and may change after recompilation.
+Do not use them as persistent identifiers in an input or post-processing workflow.
 
-The three setter methods invalidate the current snapshot. If you directly
-modify an attached object after explicitly compiling or visualizing the model,
-call ``simulation.compile()`` again before inspecting or visualizing the
-change.
+The three setter methods invalidate the current snapshot.
+If you directly modify an attached object after explicitly compiling or visualizing the model, call ``simulation.compile()`` again before inspecting or visualizing the change.
 
 Compilation finalizes some user-facing values in place.
 In particular, source probabilities are normalized, tally limits may reduce ``settings.time_boundary``, and particle-bank buffer ratios may be adjusted for the selected run mode.
@@ -115,8 +103,8 @@ Set new raw values explicitly before recompiling when an iterative workflow chan
 4. Visualize or Run
 -------------------
 
-Visualization is a useful geometry check before transport. Spatial coordinates
-are in cm and snapshot times are in seconds:
+Visualization is a useful geometry check before transport.
+Spatial coordinates are in cm and snapshot times are in seconds:
 
 .. code-block:: python
 
@@ -160,9 +148,8 @@ See :doc:`execution/cpu` and :doc:`execution/gpu` for operational guidance.
 5. Process Output
 -----------------
 
-``simulation.run()`` writes the configured HDF5 output. Use stable tally names
-and a companion post-processing script so the relationship between an input
-and its analysis remains clear:
+``simulation.run()`` writes the configured HDF5 output.
+Use stable tally names and a companion post-processing script so the relationship between an input and its analysis remains clear:
 
 .. code-block:: python
 
@@ -176,16 +163,14 @@ and its analysis remains clear:
 
 The tally is then available under ``tallies/slab_flux`` in ``slab.h5``.
 
-For workflows that reuse most of a model while changing selected inputs between
-runs, continue with :doc:`iterative_simulations`.
+For workflows that reuse most of a model while changing selected inputs between runs, continue with :doc:`iterative_simulations`.
 
 Complete Workflows
 ------------------
 
 The example suite demonstrates the lifecycle in complete inputs:
 
-- :ref:`example_slab_shielding` — fixed-source execution, model
-  visualization, and output processing.
+- :ref:`example_slab_shielding` — fixed-source execution, model visualization, and output processing.
 - :ref:`example_iterative_source_reweighting` — partial model updates and
   repeated compilation within one simulation.
 - :ref:`example_moving_source` — transient fixed-source transport.
@@ -193,6 +178,4 @@ The example suite demonstrates the lifecycle in complete inputs:
 - :ref:`example_c5g7_transient` — a larger reactor transient.
 
 For exact public signatures, use the :doc:`../reference/python_api/index`.
-For framework implementation details, continue with
-:doc:`../developer_guide/architecture/simulation_compilation` and
-:doc:`../developer_guide/architecture/runtime_data_layout`.
+For framework implementation details, continue with :doc:`../developer_guide/architecture/simulation_compilation` and :doc:`../developer_guide/architecture/runtime_data_layout`.
diff --git a/docs/source/user_guide/tallies.rst b/docs/source/user_guide/tallies.rst
index 6deba4e1b..5a6dcd92a 100644
--- a/docs/source/user_guide/tallies.rst
+++ b/docs/source/user_guide/tallies.rst
@@ -4,17 +4,14 @@
 Tallies and Post-processing
 =============================
 
-Tallies specify which transport quantities MC/DC records and how those
-quantities are divided into bins. This page extends the model from
-:doc:`getting_started/first_simulation`; add the examples below before
-``simulation.run()``. The code
-snippets assume NumPy has been imported as ``np``.
+Tallies specify which transport quantities MC/DC records and how those quantities are divided into bins.
+This page extends the model from :doc:`getting_started/first_simulation`; add the examples below before ``simulation.run()``.
+The code snippets assume NumPy has been imported as ``np``.
 
 Each tally combines:
 
 - one or more scores, such as flux, collision rate, or current;
-- optional particle, spatial, angular, group, energy, time, surface, or cell
-  filters; and
+- optional particle, spatial, angular, group, energy, time, surface, or cell filters; and
 - a name used to identify the tally in the output file.
 
 Only tallies passed to ``simulation.set_tallies(...)`` are scored.
@@ -22,10 +19,9 @@ Only tallies passed to ``simulation.set_tallies(...)`` are scored.
 Particle, Group, and Energy Filters
 -----------------------------------
 
-The ``particle_type``, ``group``, and ``energy`` filters are independent. If
-``particle_type`` is omitted, a tally accepts any transported particle type.
-Set it explicitly when one tally should score only neutrons, electrons, or
-protons:
+The ``particle_type``, ``group``, and ``energy`` filters are independent.
+If ``particle_type`` is omitted, a tally accepts any transported particle type.
+Set it explicitly when one tally should score only neutrons, electrons, or protons:
 
 .. code-block:: python3
 
@@ -36,11 +32,10 @@ protons:
        energy=[0.0, 1.0e6, 20.0e6],
    )
 
-``energy`` contains continuous-energy bin boundaries in eV. ``group`` contains
-boundaries for the independent auxiliary integer group state. The physics using
-the group determines its meaning. For neutron multigroup transport, it is the
-neutron energy-group index, and tally boundaries can coarsen several energy
-groups into one bin:
+``energy`` contains continuous-energy bin boundaries in eV.
+``group`` contains boundaries for the independent auxiliary integer group state.
+The physics using the group determines its meaning.
+For neutron multigroup transport, it is the neutron energy-group index, and tally boundaries can coarsen several energy groups into one bin:
 
 .. code-block:: python3
 
@@ -51,8 +46,7 @@ groups into one bin:
        group=[-0.5, 1.5, 3.5],
    )
 
-Use ``group="all"`` to create one tally bin per neutron energy group during
-simulation compilation:
+Use ``group="all"`` to create one tally bin per neutron energy group during simulation compilation:
 
 .. code-block:: python3
 
@@ -62,9 +56,8 @@ simulation compilation:
        group="all",
    )
 
-The ``"all"`` shortcut supports neutron groups when every material contains
-neutron multigroup data on one shared energy grid. ``particle_type`` may be
-omitted or set to ``"neutron"``.
+The ``"all"`` shortcut supports neutron groups when every material contains neutron multigroup data on one shared energy grid.
+``particle_type`` may be omitted or set to ``"neutron"``.
 
 Mesh Tallies
 ------------
@@ -82,9 +75,7 @@ The introductory example scores flux over a structured z mesh:
    simulation.set_tallies([flux_tally])
 
 The grid points are positions in cm; these 61 points define 60 spatial bins.
-Track-length scores include
-``"flux"``, ``"density"``, ``"collision"``, ``"capture"``, and
-``"fission"``.
+Track-length scores include ``"flux"``, ``"density"``, ``"collision"``, ``"capture"``, and ``"fission"``.
 
 Angular Filters
 ---------------
@@ -101,10 +92,10 @@ Add polar-cosine boundaries to retain angular information:
    )
    simulation.set_tallies([angular_flux_tally])
 
-The dimensionless polar-cosine boundaries produce 32 angular bins in each
-spatial bin. Azimuthal boundaries, when supplied with ``azi``, are in radians.
-A reference direction can be supplied with ``polar_reference``; its default is
-the positive z direction. Time-filter boundaries are in seconds.
+The dimensionless polar-cosine boundaries produce 32 angular bins in each spatial bin.
+Azimuthal boundaries, when supplied with ``azi``, are in radians.
+A reference direction can be supplied with ``polar_reference``; its default is the positive z direction.
+Time-filter boundaries are in seconds.
 
 Surface-crossing Tallies
 ------------------------
@@ -119,9 +110,8 @@ A surface filter scores net current across a particular surface:
        scores=["current-net"],
    )
 
-The current sign follows the orientation of the surface normal. For the
-``PlaneZ`` at the material interface, crossings toward increasing z contribute
-positively and crossings toward decreasing z contribute negatively.
+The current sign follows the orientation of the surface normal.
+For the ``PlaneZ`` at the material interface, crossings toward increasing z contribute positively and crossings toward decreasing z contribute negatively.
 
 A cell filter can score current across every boundary of a cell:
 
@@ -133,11 +123,9 @@ A cell filter can score current across every boundary of a cell:
        scores=["current-net", "current-in", "current-out"],
    )
 
-``"current-in"`` and ``"current-out"`` are positive partial currents;
-``"current-net"`` retains the crossing sign.
+``"current-in"`` and ``"current-out"`` are positive partial currents; ``"current-net"`` retains the crossing sign.
 
-Combining cell and surface filters restricts the tally to one surface while
-using the cell to classify incoming and outgoing crossings:
+Combining cell and surface filters restricts the tally to one surface while using the cell to classify incoming and outgoing crossings:
 
 .. code-block:: python3
 
@@ -171,10 +159,9 @@ MC/DC estimates tally uncertainty from statistically independent batches:
    simulation.settings.N_particle = 1_000
    simulation.settings.N_batch = 10
 
-``N_particle`` is the number of histories per batch. Increasing
-``N_particle`` reduces the noise within each batch, while ``N_batch`` controls
-how many independent batch results contribute to the reported standard
-deviation. At least two batches are required for a nonzero estimate.
+``N_particle`` is the number of histories per batch.
+Increasing ``N_particle`` reduces the noise within each batch, while ``N_batch`` controls how many independent batch results contribute to the reported standard deviation.
+At least two batches are required for a nonzero estimate.
 
 Reading Tally Output
 --------------------
@@ -208,17 +195,15 @@ Load and normalize the mesh flux with h5py:
    flux /= dz
    flux_sdev /= dz
 
-The score arrays contain values integrated over their bins. Spatial grids in
-the output retain cm, angular grids use radians or dimensionless polar cosine,
-energy grids use eV, and time grids use seconds. Divide by the applicable bin
-widths when a differential result is required.
+The score arrays contain values integrated over their bins.
+Spatial grids in the output retain cm, angular grids use radians or dimensionless polar cosine, energy grids use eV, and time grids use seconds.
+Divide by the applicable bin widths when a differential result is required.
 
 Reducing an Angular Tally
 -------------------------
 
-For the angular tally above, sum the angle-bin contributions to recover scalar
-flux. Weighting by the polar-cosine midpoint gives a midpoint approximation of
-the z-directed current:
+For the angular tally above, sum the angle-bin contributions to recover scalar flux.
+Weighting by the polar-cosine midpoint gives a midpoint approximation of the z-directed current:
 
 .. code-block:: python3
 
@@ -240,9 +225,8 @@ the z-directed current:
        axis=0,
    ) / dz
 
-The exact array-axis order follows the active filters and is recorded by the
-corresponding grids in the tally group. Inspect the output shapes before
-performing reductions.
+The exact array-axis order follows the active filters and is recorded by the corresponding grids in the tally group.
+Inspect the output shapes before performing reductions.
 
 Verification
 ------------
@@ -255,5 +239,4 @@ Before drawing conclusions from a tally:
 - Use current tallies to check particle balance where appropriate.
 - Compare against an analytic or benchmark solution when one is available.
 
-The :class:`mcdc.Tally` API reference documents all supported scores and filter
-combinations.
+The :class:`mcdc.Tally` API reference documents all supported scores and filter combinations.

From e67e0eeda8559f718bae463fc7cab106dd8fe7db Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 10:00:10 +0700
Subject: [PATCH 148/202] update source

---
 mcdc/transport/source.py | 34 +++++++++++++++----------------
 test/unit/test_source.py | 44 ++++++++++++++++++++++++++++++++++++++++
 2 files changed, 60 insertions(+), 18 deletions(-)

diff --git a/mcdc/transport/source.py b/mcdc/transport/source.py
index bc133733c..68fb89eab 100644
--- a/mcdc/transport/source.py
+++ b/mcdc/transport/source.py
@@ -62,25 +62,23 @@ def source_particle(particle_container, seed, simulation, data):
             particle_container,
         )
 
+    # Group
+    if source["mono_group"]:
+        group = source["group"]
+    else:
+        ID = source["group_pmf_ID"]
+        sub_ID = simulation["distributions"][ID]["sub_ID"]
+        pmf = simulation["pmf_distributions"][sub_ID]
+        group = sample_pmf(pmf, particle_container, data)
+
     # Energy
-    if simulation["settings"]["neutron_multigroup_mode"]:
-        E = 0.0
-        if source["mono_energetic"]:
-            g = source["energy_group"]
-        else:
-            ID = source["energy_group_pmf_ID"]
-            sub_ID = simulation["distributions"][ID]["sub_ID"]
-            pmf = simulation["pmf_distributions"][sub_ID]
-            g = sample_pmf(pmf, particle_container, data)
+    if source["mono_energetic"]:
+        E = source["energy"]
     else:
-        g = 0
-        if source["mono_energetic"]:
-            E = source["energy"]
-        else:
-            ID = source["energy_pdf_ID"]
-            sub_ID = simulation["distributions"][ID]["sub_ID"]
-            table = simulation["tabulated_distributions"][sub_ID]
-            E = sample_tabulated(table, particle_container, simulation, data)
+        ID = source["energy_pdf_ID"]
+        sub_ID = simulation["distributions"][ID]["sub_ID"]
+        table = simulation["tabulated_distributions"][sub_ID]
+        E = sample_tabulated(table, particle_container, simulation, data)
 
     # Time
     if source["discrete_time"]:
@@ -135,7 +133,7 @@ def source_particle(particle_container, seed, simulation, data):
     particle["ux"] = ux
     particle["uy"] = uy
     particle["uz"] = uz
-    particle["g"] = g
+    particle["group"] = group
     particle["E"] = E
     particle["w"] = 1.0
     particle["particle_type"] = source["particle_type"]
diff --git a/test/unit/test_source.py b/test/unit/test_source.py
index 59140961c..7c6b5c0a7 100644
--- a/test/unit/test_source.py
+++ b/test/unit/test_source.py
@@ -2,6 +2,8 @@
 import pytest
 
 import mcdc
+import mcdc.numba_types as type_
+from mcdc.transport.source import source_particle
 
 
 @pytest.mark.parametrize(
@@ -72,6 +74,48 @@ def test_energy_and_group_are_stored_independently():
     assert source.group == 3
 
 
+def test_transport_source_sets_energy_and_group_independently(prepare_simulation):
+    source = mcdc.Source(
+        position=[0.0, 0.0, 0.0],
+        direction=[0.0, 0.0, 1.0],
+        energy=10_000.0,
+        group=3,
+    )
+    simulation_container, data = prepare_simulation(sources=[source])
+    particle_container = np.zeros(1, dtype=type_.particle)
+
+    source_particle(
+        particle_container,
+        np.uint64(1),
+        simulation_container[0],
+        data,
+    )
+
+    assert particle_container[0]["E"] == 10_000.0
+    assert particle_container[0]["group"] == 3
+
+
+def test_transport_source_samples_energy_and_group_independently(prepare_simulation):
+    source = mcdc.Source(
+        position=[0.0, 0.0, 0.0],
+        direction=[0.0, 0.0, 1.0],
+        energy=([9_999.0, 10_001.0], [0.5, 0.5]),
+        group=([3], [1.0]),
+    )
+    simulation_container, data = prepare_simulation(sources=[source])
+    particle_container = np.zeros(1, dtype=type_.particle)
+
+    source_particle(
+        particle_container,
+        np.uint64(1),
+        simulation_container[0],
+        data,
+    )
+
+    assert 9_999.0 <= particle_container[0]["E"] <= 10_001.0
+    assert particle_container[0]["group"] == 3
+
+
 @pytest.mark.parametrize("time", [2, 2.0, np.int64(2), np.float64(2.0)])
 def test_scalar_time(time):
     source = mcdc.Source(time=time)

From 116f41b4bf6254a268bbeacf72b2455e84485e42 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 10:04:58 +0700
Subject: [PATCH 149/202] update particle

---
 mcdc/transport/particle.py |  2 +-
 test/unit/test_particle.py | 31 +++++++++++++++++++++++++++++++
 2 files changed, 32 insertions(+), 1 deletion(-)
 create mode 100644 test/unit/test_particle.py

diff --git a/mcdc/transport/particle.py b/mcdc/transport/particle.py
index e524e1c21..4297fa920 100644
--- a/mcdc/transport/particle.py
+++ b/mcdc/transport/particle.py
@@ -29,7 +29,7 @@ def copy(target_particle_container, source_particle_container):
     target_particle["ux"] = source_particle["ux"]
     target_particle["uy"] = source_particle["uy"]
     target_particle["uz"] = source_particle["uz"]
-    target_particle["g"] = source_particle["g"]
+    target_particle["group"] = source_particle["group"]
     target_particle["E"] = source_particle["E"]
     target_particle["w"] = source_particle["w"]
     target_particle["particle_type"] = source_particle["particle_type"]
diff --git a/test/unit/test_particle.py b/test/unit/test_particle.py
new file mode 100644
index 000000000..df04e987d
--- /dev/null
+++ b/test/unit/test_particle.py
@@ -0,0 +1,31 @@
+import numpy as np
+
+import mcdc.numba_types as type_
+from mcdc.transport.particle import copy
+
+
+def test_copy_particle_data_to_active_particle():
+    source = np.zeros(1, dtype=type_.particle_data)
+    target = np.zeros(1, dtype=type_.particle)
+
+    values = {
+        "x": 1.0,
+        "y": 2.0,
+        "z": 3.0,
+        "t": 4.0,
+        "ux": 0.1,
+        "uy": 0.2,
+        "uz": 0.3,
+        "group": 7,
+        "E": 8.0,
+        "w": 9.0,
+        "particle_type": 10,
+        "rng_seed": 11,
+    }
+    for field, value in values.items():
+        source[0][field] = value
+
+    copy(target, source)
+
+    for field, value in values.items():
+        assert target[0][field] == value

From 867c760202851d449b5562b74641bf8c1631ccb6 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 11:02:50 +0700
Subject: [PATCH 150/202] consolidate inspect_geometry and locate_particle

---
 mcdc/transport/geometry/interface.py | 242 ++++++++++++---------------
 mcdc/transport/simulation.py         |  15 +-
 2 files changed, 117 insertions(+), 140 deletions(-)

diff --git a/mcdc/transport/geometry/interface.py b/mcdc/transport/geometry/interface.py
index 55f844ddc..93193b80d 100644
--- a/mcdc/transport/geometry/interface.py
+++ b/mcdc/transport/geometry/interface.py
@@ -15,7 +15,7 @@
 from mcdc.transport.geometry.surface import get_distance, check_sense
 
 # ======================================================================================
-# Geometry inspection
+# Geometry traversal
 # ======================================================================================
 
 
@@ -30,36 +30,23 @@ def inspect_geometry(particle_container, simulation, data):
     """
     particle = particle_container[0]
 
-    # Store particle global coordinate
-    # (particle will be temporarily translated and rotated)
-    x_global = particle["x"]
-    y_global = particle["y"]
-    z_global = particle["z"]
-    t_global = particle["t"]
-    ux_global = particle["ux"]
-    uy_global = particle["uy"]
-    uz_global = particle["uz"]
+    # Preserve global coordinates while traversing nested geometry.
+    global_coordinates = _save_global_coordinates(particle_container)
     speed = physics.particle_speed(particle_container, simulation, data)
 
     # Default returns
     distance = INF
     event = EVENT_NONE
 
-    # Find top cell from root universe if unknown
-    if particle["cell_ID"] == -1:
-        particle["cell_ID"] = get_cell(
-            particle_container, UNIVERSE_ROOT, simulation, data
-        )
-
-        # Particle is lost?
-        if particle["cell_ID"] == -1:
-            event = EVENT_LOST
-
-    # The top cell
-    cell = simulation["cells"][particle["cell_ID"]]
+    # Find the top cell from the root universe if it is unknown.
+    cell_ID = _get_top_cell_ID(particle_container, simulation, data)
+    if cell_ID == -1:
+        event = EVENT_LOST
 
     # Recursively check cells until material cell is found (or the particle is lost)
     while event != EVENT_LOST:
+        cell = simulation["cells"][cell_ID]
+
         # Distance to nearest surface
         d_surface, surface_ID = distance_to_nearest_surface(
             particle_container, cell, simulation, data
@@ -86,24 +73,10 @@ def inspect_geometry(particle_container, simulation, data):
 
         else:
             # Cell is filled with universe or lattice
-
-            # Apply translation
-            if cell["fill_translated"]:
-                particle["x"] -= cell["translation"][0]
-                particle["y"] -= cell["translation"][1]
-                particle["z"] -= cell["translation"][2]
-
-            # Apply rotation
-            if cell["fill_rotated"]:
-                _rotate_particle(particle_container, cell["rotation"])
-
-            # Universe cell?
-            if cell["fill_type"] == FILL_UNIVERSE:
-                # Get universe ID
-                universe_ID = cell["fill_ID"]
+            _apply_fill_transform(particle_container, cell)
 
             # Lattice cell?
-            elif cell["fill_type"] == FILL_LATTICE:
+            if cell["fill_type"] == FILL_LATTICE:
                 # Get lattice
                 lattice = simulation["lattices"][cell["fill_ID"]]
 
@@ -124,37 +97,19 @@ def inspect_geometry(particle_container, simulation, data):
                     if not event & EVENT_LATTICE_CROSSING:
                         event += EVENT_LATTICE_CROSSING
 
-                # Get universe
-                ix, iy, iz = mesh.uniform.get_indices(particle_container, lattice)
-                if ix == -1 or iy == -1 or iz == -1:
-                    event = EVENT_LOST
-                    continue
-                universe_ID = mcdc_get.lattice.universe_IDs(ix, iy, iz, lattice, data)
-
-                # Lattice-translate the particle
-                particle["x"] -= lattice["x0"] + (ix + 0.5) * lattice["dx"]
-                particle["y"] -= lattice["y0"] + (iy + 0.5) * lattice["dy"]
-                particle["z"] -= lattice["z0"] + (iz + 0.5) * lattice["dz"]
-
-            else:
-                # Unreached
-                universe_ID = -1
+            # Find the filled universe and enter its local coordinates.
+            universe_ID = _enter_fill(particle_container, cell, simulation, data)
+            if universe_ID == -1:
+                event = EVENT_LOST
+                continue
 
             # Get inner cell
             cell_ID = get_cell(particle_container, universe_ID, simulation, data)
-            if cell_ID > -1:
-                cell = simulation["cells"][cell_ID]
-            else:
+            if cell_ID == -1:
                 event = EVENT_LOST
 
-    # Reassign the global coordinate
-    particle["x"] = x_global
-    particle["y"] = y_global
-    particle["z"] = z_global
-    particle["t"] = t_global
-    particle["ux"] = ux_global
-    particle["uy"] = uy_global
-    particle["uz"] = uz_global
+    # Restore the particle after traversal through local coordinates.
+    _restore_global_coordinates(particle_container, global_coordinates)
 
     # Report lost particle
     if event == EVENT_LOST:
@@ -177,33 +132,20 @@ def locate_particle(particle_container, simulation, data):
     """
     particle = particle_container[0]
 
-    # Store particle global coordinate
-    # (particle will be temporarily translated and rotated)
-    x_global = particle["x"]
-    y_global = particle["y"]
-    z_global = particle["z"]
-    t_global = particle["t"]
-    ux_global = particle["ux"]
-    uy_global = particle["uy"]
-    uz_global = particle["uz"]
+    # Preserve global coordinates while traversing nested geometry.
+    global_coordinates = _save_global_coordinates(particle_container)
 
     particle_is_lost = False
 
-    # Find top cell from root universe if unknown
-    if particle["cell_ID"] == -1:
-        particle["cell_ID"] = get_cell(
-            particle_container, UNIVERSE_ROOT, simulation, data
-        )
-
-        # Particle is lost?
-        if particle["cell_ID"] == -1:
-            particle_is_lost = True
-
-    # The top cell
-    cell = simulation["cells"][particle["cell_ID"]]
+    # Find the top cell from the root universe if it is unknown.
+    cell_ID = _get_top_cell_ID(particle_container, simulation, data)
+    if cell_ID == -1:
+        particle_is_lost = True
 
     # Recursively check cells until material cell is found (or the particle is lost)
     while not particle_is_lost:
+        cell = simulation["cells"][cell_ID]
+
         # Material cell?
         if cell["fill_type"] == FILL_MATERIAL:
             particle["material_ID"] = cell["fill_ID"]
@@ -211,58 +153,21 @@ def locate_particle(particle_container, simulation, data):
 
         else:
             # Cell is filled with universe or lattice
+            _apply_fill_transform(particle_container, cell)
 
-            # Apply translation
-            if cell["fill_translated"]:
-                particle["x"] -= cell["translation"][0]
-                particle["y"] -= cell["translation"][1]
-                particle["z"] -= cell["translation"][2]
-
-            # Apply rotation
-            if cell["fill_rotated"]:
-                _rotate_particle(particle_container, cell["rotation"])
-
-            # Universe cell?
-            if cell["fill_type"] == FILL_UNIVERSE:
-                # Get universe ID
-                universe_ID = cell["fill_ID"]
-
-            # Lattice cell?
-            elif cell["fill_type"] == FILL_LATTICE:
-                # Get lattice
-                lattice = simulation["lattices"][cell["fill_ID"]]
-
-                # Get universe
-                ix, iy, iz = mesh.uniform.get_indices(particle_container, lattice)
-                if ix == -1 or iy == -1 or iz == -1:
-                    particle_is_lost = True
-                    continue
-                universe_ID = mcdc_get.lattice.universe_IDs(ix, iy, iz, lattice, data)
-
-                # Lattice-translate the particle
-                particle["x"] -= lattice["x0"] + (ix + 0.5) * lattice["dx"]
-                particle["y"] -= lattice["y0"] + (iy + 0.5) * lattice["dy"]
-                particle["z"] -= lattice["z0"] + (iz + 0.5) * lattice["dz"]
-
-            else:
-                # Unreached
-                universe_ID = -1
+            # Find the filled universe and enter its local coordinates.
+            universe_ID = _enter_fill(particle_container, cell, simulation, data)
+            if universe_ID == -1:
+                particle_is_lost = True
+                continue
 
             # Get inner cell
             cell_ID = get_cell(particle_container, universe_ID, simulation, data)
-            if cell_ID > -1:
-                cell = simulation["cells"][cell_ID]
-            else:
+            if cell_ID == -1:
                 particle_is_lost = True
 
-    # Reassign the global coordinate
-    particle["x"] = x_global
-    particle["y"] = y_global
-    particle["z"] = z_global
-    particle["t"] = t_global
-    particle["ux"] = ux_global
-    particle["uy"] = uy_global
-    particle["uz"] = uz_global
+    # Restore the particle after traversal through local coordinates.
+    _restore_global_coordinates(particle_container, global_coordinates)
 
     # Report lost particle
     if particle_is_lost:
@@ -271,6 +176,81 @@ def locate_particle(particle_container, simulation, data):
     return not particle_is_lost
 
 
+# ======================================================================================
+# Geometry traversal helpers
+# ======================================================================================
+
+
+@njit
+def _save_global_coordinates(particle_container):
+    particle = particle_container[0]
+    return (
+        particle["x"],
+        particle["y"],
+        particle["z"],
+        particle["t"],
+        particle["ux"],
+        particle["uy"],
+        particle["uz"],
+    )
+
+
+@njit
+def _restore_global_coordinates(particle_container, coordinates):
+    particle = particle_container[0]
+    particle["x"] = coordinates[0]
+    particle["y"] = coordinates[1]
+    particle["z"] = coordinates[2]
+    particle["t"] = coordinates[3]
+    particle["ux"] = coordinates[4]
+    particle["uy"] = coordinates[5]
+    particle["uz"] = coordinates[6]
+
+
+@njit
+def _get_top_cell_ID(particle_container, simulation, data):
+    particle = particle_container[0]
+    if particle["cell_ID"] == -1:
+        particle["cell_ID"] = get_cell(
+            particle_container, UNIVERSE_ROOT, simulation, data
+        )
+    return particle["cell_ID"]
+
+
+@njit
+def _apply_fill_transform(particle_container, cell):
+    particle = particle_container[0]
+
+    if cell["fill_translated"]:
+        particle["x"] -= cell["translation"][0]
+        particle["y"] -= cell["translation"][1]
+        particle["z"] -= cell["translation"][2]
+
+    if cell["fill_rotated"]:
+        _rotate_particle(particle_container, cell["rotation"])
+
+
+@njit
+def _enter_fill(particle_container, cell, simulation, data):
+    if cell["fill_type"] == FILL_UNIVERSE:
+        return cell["fill_ID"]
+
+    if cell["fill_type"] == FILL_LATTICE:
+        particle = particle_container[0]
+        lattice = simulation["lattices"][cell["fill_ID"]]
+        ix, iy, iz = mesh.uniform.get_indices(particle_container, lattice)
+        if ix == -1 or iy == -1 or iz == -1:
+            return -1
+
+        universe_ID = mcdc_get.lattice.universe_IDs(ix, iy, iz, lattice, data)
+        particle["x"] -= lattice["x0"] + (ix + 0.5) * lattice["dx"]
+        particle["y"] -= lattice["y0"] + (iy + 0.5) * lattice["dy"]
+        particle["z"] -= lattice["z0"] + (iz + 0.5) * lattice["dz"]
+        return universe_ID
+
+    return -1
+
+
 @njit
 def _rotate_particle(particle_container, rotation):
     # Particle initial coordinate
diff --git a/mcdc/transport/simulation.py b/mcdc/transport/simulation.py
index 92783144a..80f3055d2 100644
--- a/mcdc/transport/simulation.py
+++ b/mcdc/transport/simulation.py
@@ -346,17 +346,14 @@ def move_to_event(particle_container, simulation, data):
     # ==================================================================================
     # Preparation (as needed)
     # ==================================================================================
+
     particle = particle_container[0]
 
-    # Multigroup preparation
-    #   In MG mode, particle speed is material-dependent.
-    if settings["neutron_multigroup_mode"]:
-        # If material is not identified yet, locate the particle
-        if particle["material_ID"] == -1:
-            if not geometry.locate_particle(particle_container, simulation, data):
-                # Particle is lost
-                particle["event"] = EVENT_LOST
-                return
+    # Locate the material before evaluating material-dependent transport data.
+    if particle["material_ID"] == -1:
+        if not geometry.locate_particle(particle_container, simulation, data):
+            particle["event"] = EVENT_LOST
+            return
 
     # ==================================================================================
     # Geometry inspection

From 282e21547a13ab1692f00df0e9adbbbc2bebbc08 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 11:36:32 +0700
Subject: [PATCH 151/202] introduce speed-aware geometry interface variants

---
 mcdc/transport/geometry/interface.py | 47 ++++++++++++++++++++--------
 test/unit/geometry/test_interface.py | 34 ++++++++++++++++++++
 2 files changed, 68 insertions(+), 13 deletions(-)
 create mode 100644 test/unit/geometry/test_interface.py

diff --git a/mcdc/transport/geometry/interface.py b/mcdc/transport/geometry/interface.py
index 93193b80d..b904dbe3f 100644
--- a/mcdc/transport/geometry/interface.py
+++ b/mcdc/transport/geometry/interface.py
@@ -39,7 +39,7 @@ def inspect_geometry(particle_container, simulation, data):
     event = EVENT_NONE
 
     # Find the top cell from the root universe if it is unknown.
-    cell_ID = _get_top_cell_ID(particle_container, simulation, data)
+    cell_ID = _get_top_cell_ID(particle_container, speed, simulation, data)
     if cell_ID == -1:
         event = EVENT_LOST
 
@@ -104,7 +104,9 @@ def inspect_geometry(particle_container, simulation, data):
                 continue
 
             # Get inner cell
-            cell_ID = get_cell(particle_container, universe_ID, simulation, data)
+            cell_ID = _get_cell(
+                particle_container, speed, universe_ID, simulation, data
+            )
             if cell_ID == -1:
                 event = EVENT_LOST
 
@@ -135,10 +137,15 @@ def locate_particle(particle_container, simulation, data):
     # Preserve global coordinates while traversing nested geometry.
     global_coordinates = _save_global_coordinates(particle_container)
 
+    # Use direction alone to resolve surface coincidence during location.
+    # Material-dependent speed is unavailable until location is complete.
+    direction_only_speed = INF
     particle_is_lost = False
 
     # Find the top cell from the root universe if it is unknown.
-    cell_ID = _get_top_cell_ID(particle_container, simulation, data)
+    cell_ID = _get_top_cell_ID(
+        particle_container, direction_only_speed, simulation, data
+    )
     if cell_ID == -1:
         particle_is_lost = True
 
@@ -162,7 +169,13 @@ def locate_particle(particle_container, simulation, data):
                 continue
 
             # Get inner cell
-            cell_ID = get_cell(particle_container, universe_ID, simulation, data)
+            cell_ID = _get_cell(
+                particle_container,
+                direction_only_speed,
+                universe_ID,
+                simulation,
+                data,
+            )
             if cell_ID == -1:
                 particle_is_lost = True
 
@@ -208,11 +221,11 @@ def _restore_global_coordinates(particle_container, coordinates):
 
 
 @njit
-def _get_top_cell_ID(particle_container, simulation, data):
+def _get_top_cell_ID(particle_container, speed, simulation, data):
     particle = particle_container[0]
     if particle["cell_ID"] == -1:
-        particle["cell_ID"] = get_cell(
-            particle_container, UNIVERSE_ROOT, simulation, data
+        particle["cell_ID"] = _get_cell(
+            particle_container, speed, UNIVERSE_ROOT, simulation, data
         )
     return particle["cell_ID"]
 
@@ -318,14 +331,20 @@ def get_cell(particle_container, universe_ID, simulation, data):
     Find and return particle cell ID in the given universe
     Return -1 if particle is lost
     """
-    particle = particle_container[0]
+    speed = physics.particle_speed(particle_container, simulation, data)
+    return _get_cell(particle_container, speed, universe_ID, simulation, data)
+
+
+@njit
+def _get_cell(particle_container, speed, universe_ID, simulation, data):
+    """Find the particle cell using the supplied speed for coincidence checks."""
     universe = simulation["universes"][universe_ID]
 
     # Check over all cells in the universe
     for i in range(universe["N_cell"]):
         cell_ID = mcdc_get.universe.cell_IDs(i, universe, data)
         cell = simulation["cells"][cell_ID]
-        if check_cell(particle_container, cell, simulation, data):
+        if _check_cell(particle_container, speed, cell, simulation, data):
             return cell_ID
 
     # Particle is not found
@@ -337,8 +356,13 @@ def check_cell(particle_container, cell, simulation, data):
     """
     Check if the particle is inside the cell
     """
-    particle = particle_container[0]
+    speed = physics.particle_speed(particle_container, simulation, data)
+    return _check_cell(particle_container, speed, cell, simulation, data)
+
 
+@njit
+def _check_cell(particle_container, speed, cell, simulation, data):
+    """Check cell membership using the supplied speed for coincidence checks."""
     # Access RPN data
     N_token = cell["region_RPN_tokens_length"]
     if N_token == 0:
@@ -348,9 +372,6 @@ def check_cell(particle_container, cell, simulation, data):
     value = util.local_array(literals.rpn_evaluation_buffer_size(), np.bool_)
     N_value = 0
 
-    # Particle parameters
-    speed = physics.particle_speed(particle_container, simulation, data)
-
     # March forward through RPN tokens
     for idx in range(N_token):
         token = mcdc_get.cell.region_RPN_tokens(idx, cell, data)
diff --git a/test/unit/geometry/test_interface.py b/test/unit/geometry/test_interface.py
new file mode 100644
index 000000000..126adc636
--- /dev/null
+++ b/test/unit/geometry/test_interface.py
@@ -0,0 +1,34 @@
+import numpy as np
+
+import mcdc
+import mcdc.numba_types as type_
+from mcdc.transport.geometry import locate_particle
+
+
+def test_locate_particle_without_material_speed(prepare_simulation):
+    material = mcdc.Material.multigroup(capture=np.array([1.0]))
+    boundary = mcdc.Surface.PlaneX(x=0.0)
+    universe = mcdc.Universe(cells=[mcdc.Cell(region=+boundary, fill=material)])
+    root_cell = mcdc.Cell(fill=universe, translation=[5.0, 0.0, 0.0])
+    simulation_container, data = prepare_simulation(cells=[root_cell])
+    simulation = simulation_container[0]
+
+    particle_container = np.zeros(1, dtype=type_.particle)
+    particle = particle_container[0]
+    particle["x"] = 6.0
+    particle["ux"] = 1.0
+    particle["cell_ID"] = -1
+    particle["material_ID"] = -1
+    original_coordinates = tuple(
+        particle[field] for field in ("x", "y", "z", "t", "ux", "uy", "uz")
+    )
+
+    found = locate_particle(particle_container, simulation, data)
+
+    assert found
+    assert particle["cell_ID"] == root_cell.ID
+    assert particle["material_ID"] == material.ID
+    assert (
+        tuple(particle[field] for field in ("x", "y", "z", "t", "ux", "uy", "uz"))
+        == original_coordinates
+    )

From fca8b8aba069e9081f4a9af2805f80ed44136b8a Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 14:18:12 +0700
Subject: [PATCH 152/202] set the interface design

---
 mcdc/transport/physics/neutron/interface.py  |  8 ++--
 mcdc/transport/physics/neutron/multigroup.py | 45 +++++++++++++++++++-
 2 files changed, 47 insertions(+), 6 deletions(-)

diff --git a/mcdc/transport/physics/neutron/interface.py b/mcdc/transport/physics/neutron/interface.py
index 29f78602f..f9186efae 100644
--- a/mcdc/transport/physics/neutron/interface.py
+++ b/mcdc/transport/physics/neutron/interface.py
@@ -13,7 +13,7 @@
 
 @njit
 def particle_speed(particle_container, simulation, data):
-    if simulation["settings"]["neutron_multigroup_mode"]:
+    if multigroup.applicable(particle_container, simulation, data):
         return multigroup.particle_speed(particle_container, simulation, data)
     else:
         return native.particle_speed(particle_container)
@@ -26,7 +26,7 @@ def particle_speed(particle_container, simulation, data):
 
 @njit
 def macro_xs(reaction_type, particle_container, simulation, data):
-    if simulation["settings"]["neutron_multigroup_mode"]:
+    if multigroup.applicable(particle_container, simulation, data):
         return multigroup.macro_xs(reaction_type, particle_container, simulation, data)
     else:
         return native.macro_xs(reaction_type, particle_container, simulation, data)
@@ -34,7 +34,7 @@ def macro_xs(reaction_type, particle_container, simulation, data):
 
 @njit
 def neutron_production_xs(reaction_type, particle_container, simulation, data):
-    if simulation["settings"]["neutron_multigroup_mode"]:
+    if multigroup.applicable(particle_container, simulation, data):
         return multigroup.neutron_production_xs(
             reaction_type, particle_container, simulation, data
         )
@@ -53,7 +53,7 @@ def neutron_production_xs(reaction_type, particle_container, simulation, data):
 def collision(particle_container, collision_data_container, program, data):
     simulation = util.access_simulation(program)
 
-    if simulation["settings"]["neutron_multigroup_mode"]:
+    if multigroup.applicable(particle_container, simulation, data):
         multigroup.collision(
             particle_container, collision_data_container, program, data
         )
diff --git a/mcdc/transport/physics/neutron/multigroup.py b/mcdc/transport/physics/neutron/multigroup.py
index 1719bede3..dcf3fc5ac 100644
--- a/mcdc/transport/physics/neutron/multigroup.py
+++ b/mcdc/transport/physics/neutron/multigroup.py
@@ -24,6 +24,33 @@
 from mcdc.transport.physics.util import scatter_direction
 from mcdc.transport.distribution import sample_isotropic_direction
 
+# ======================================================================================
+# Applicability
+# ======================================================================================
+
+
+@njit
+def applicable(particle_container, simulation, data):
+    particle = particle_container[0]
+    material = simulation["materials"][particle["material_ID"]]
+
+    if not material["has_neutron_multigroup"]:
+        return False
+
+    if simulation["technique"]["neutron_multigroup"]["hybrid"]:
+        mgxs_ID = material["neutron_multigroup_ID"]
+        mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
+
+        E = particle["E"]
+        E_min = mcdc_get.neutron_multigroup_data.energy_grid(0, mgxs, data)
+        E_max = mcdc_get.neutron_multigroup_data.energy_grid_last(mgxs, data)
+
+        if E < E_min or E > E_max:
+            return False
+
+    return True
+
+
 # ======================================================================================
 # Particle attributes
 # ======================================================================================
@@ -32,8 +59,22 @@
 @njit
 def particle_speed(particle_container, simulation, data):
     particle = particle_container[0]
-    material = simulation["multigroup_materials"][particle["material_ID"]]
-    return mcdc_get.multigroup_material.mgxs_speed(particle["g"], material, data)
+    material = simulation["materials"][particle["material_ID"]]
+
+    mgxs_ID = material["neutron_multigroup_ID"]
+    mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
+
+    if simulation["technique"]["neutron_multigroup"]["hybrid"]:
+        E = particle["E"]
+        offset = mgxs["energy_grid_offset"]
+        length = mgxs["energy_grid_length"]
+        E_grid = data[offset : offset + length]
+        group = util.find_bin(E, E_grid)
+
+    else:
+        group = particle["group"]
+
+    return mcdc_get.neutron_multigroup_data.speed(group, mgxs, data)
 
 
 # ======================================================================================

From 13f2415def2facb524fd8234549a237fc3875b3b Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 15:14:50 +0700
Subject: [PATCH 153/202] implement the redesign

---
 docs/source/_ext/simulation_members.py        |  2 -
 docs/source/reference/python_api/index.rst    |  2 +-
 .../user_guide/materials_and_multigroup.rst   | 19 +++---
 mcdc/numba_types.py                           |  2 +-
 mcdc/object_/material.py                      | 10 ++-
 mcdc/object_/simulation.py                    | 49 +++++++++------
 mcdc/object_/source.py                        |  4 +-
 mcdc/object_/technique.py                     | 31 ++--------
 mcdc/object_/transport_model_data.py          | 34 +++++------
 test/unit/test_object_compilation.py          | 61 ++++++++++++++++---
 test/unit/test_transport_model_data.py        |  9 +--
 11 files changed, 130 insertions(+), 93 deletions(-)

diff --git a/docs/source/_ext/simulation_members.py b/docs/source/_ext/simulation_members.py
index 53ca807f8..86b49ea39 100644
--- a/docs/source/_ext/simulation_members.py
+++ b/docs/source/_ext/simulation_members.py
@@ -15,7 +15,6 @@
 from mcdc.object_.technique import (
     GlobalWeightRoulette,
     ImplicitCapture,
-    NeutronMultigroupTechnique,
     PopulationControl,
     WeightedEmission,
     WeightWindows,
@@ -43,7 +42,6 @@
 )
 
 TECHNIQUES = (
-    ("neutron_multigroup", NeutronMultigroupTechnique),
     ("implicit_capture", ImplicitCapture),
     ("weighted_emission", WeightedEmission),
     ("global_weight_roulette", GlobalWeightRoulette),
diff --git a/docs/source/reference/python_api/index.rst b/docs/source/reference/python_api/index.rst
index ad2f78eb3..d23984b4d 100644
--- a/docs/source/reference/python_api/index.rst
+++ b/docs/source/reference/python_api/index.rst
@@ -124,7 +124,7 @@ Transport techniques
 ^^^^^^^^^^^^^^^^^^^^
 
 Transport techniques are grouped under ``simulation.technique``.
-For example, enable implicit capture with ``simulation.technique.implicit_capture()`` or allow material-local neutron group structures with ``simulation.technique.neutron_multigroup(multigrid=True)``.
+For example, enable implicit capture with ``simulation.technique.implicit_capture()`` or configure weight windows with ``simulation.technique.weight_windows(...)``.
 See :class:`mcdc.Simulation` for the ownership model and examples.
 
 Compiling and running
diff --git a/docs/source/user_guide/materials_and_multigroup.rst b/docs/source/user_guide/materials_and_multigroup.rst
index 265e4067d..96b7ed4d6 100644
--- a/docs/source/user_guide/materials_and_multigroup.rst
+++ b/docs/source/user_guide/materials_and_multigroup.rst
@@ -64,8 +64,8 @@ An explicit ``energy_grid`` contains ``G + 1`` physical energy boundaries in eV.
 Group ``g`` covers ``energy_grid[g] <= E < energy_grid[g + 1]``.
 The grid both maps continuous energy to a group and bounds continuous energy reconstructed from a group.
 
-When no grid is supplied, MC/DC creates the group-coordinate grid ``[-0.5, 0.5, 1.5, 2.5, ...]`` with ``energy_representation="midpoint"``.
-Its reconstructed values are therefore the integer group coordinates ``0, 1, 2, ...``.
+When no grid is supplied, MC/DC stores a zero-valued placeholder with length ``G + 1``.
+The placeholder does not represent physical energy boundaries and is used only for standard multigroup transport, where the particle's group is authoritative and continuous energy does not select a group.
 
 For lower and upper group boundaries :math:`E_g` and :math:`E_{g+1}`, the energy-representation policies are:
 
@@ -74,15 +74,18 @@ For lower and upper group boundaries :math:`E_g` and :math:`E_{g+1}`, the energy
 - ``"uniform"``: sample :math:`E` uniformly between the two boundaries; and
 - ``"log_uniform"``: sample :math:`\log E` uniformly between their logarithms, equivalently :math:`E=E_g(E_{g+1}/E_g)^\xi` for :math:`\xi\sim\mathcal{U}(0,1)`.
 
+The policies apply when an explicit physical energy grid is used.
 The logarithmic policies require strictly positive energy boundaries.
 Midpoint policies reconstruct one deterministic value per group, while uniform policies sample a new value when continuous energy is reconstructed.
 
-Neutron multigroup datasets use one shared energy grid by default.
-Enable the multigrid option when materials use different group structures:
+MC/DC determines the neutron multigroup transport organization when the simulation is compiled.
+Standard neutron multigroup transport means that every material uses neutron multigroup data without native composition and that all materials share one energy grid.
+MC/DC selects this organization only when every material satisfies those conditions.
+This includes materials sharing either the zero-valued placeholder or the same explicit physical grid.
 
-.. code-block:: python
-
-   simulation.technique.neutron_multigroup(multigrid=True)
+Transport is hybrid when native composition data is present or multigroup materials use different grids.
+Every multigroup dataset participating in hybrid transport requires an explicit physical energy grid because continuous energy selects the applicable material-local group.
+If a particle lies outside that grid, MC/DC uses the material's native neutron data when present; without a native composition, the material has zero interaction cross section at that energy.
 
 Combining Native and Multigroup Data
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -120,5 +123,5 @@ A particle carries continuous ``energy`` and an auxiliary integer ``group`` as s
 
 The physics using ``group`` determines its meaning.
 Neutron multigroup transport uses it as the neutron energy-group index.
-If both variables are supplied, the group takes precedence over energy only for shared-grid neutron multigroup transport.
+If both variables are supplied, the group takes precedence over energy only for standard neutron multigroup transport selected during compilation.
 The tally equivalents are the separate ``group`` and ``energy`` filters described in :doc:`tallies`.
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index 9d42bd46d..bc6e72a9f 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -547,7 +547,7 @@
 ])
 
 neutron_multigroup = into_dtype([
-    ('multigrid', bool),
+    ('hybrid', bool),
 ])
 
 implicit_capture = into_dtype([
diff --git a/mcdc/object_/material.py b/mcdc/object_/material.py
index ba89de081..5c7d85a06 100644
--- a/mcdc/object_/material.py
+++ b/mcdc/object_/material.py
@@ -37,7 +37,9 @@ class Material(MCDCObject):
         groups. When supplied with a
         :ref:`native composition <user_native_transport>`, its explicit
         ``energy_grid`` defines the energy range where the multigroup treatment
-        applies.
+        applies. In hybrid transport, native neutron data is used outside that
+        range when present; without native composition, the material has zero
+        interaction cross section.
 
     Notes
     -----
@@ -139,7 +141,7 @@ def __init__(
             (nuclide_composition or element_composition)
             and neutron_multigroup is not None
             and neutron_multigroup.G > 0
-            and neutron_multigroup._uses_default_energy_grid
+            and not np.any(neutron_multigroup.energy_grid)
         ):
             print_error(
                 "Material requires an explicit neutron multigroup energy_grid "
@@ -204,7 +206,9 @@ def multigroup(
         :class:`NeutronMultigroupData` and attaches the data to the material.
         Macroscopic cross sections use ``cm^-1``, group speeds use cm/s,
         precursor decay rates use ``s^-1``, and explicit physical energy
-        boundaries use eV.
+        boundaries use eV. Omitting ``energy_grid`` creates a zero-valued
+        placeholder that is valid only when every material with neutron
+        multigroup data also omits its energy grid.
         """
         # Build the neutron multigroup data while preserving Material as the sole type
         neutron_multigroup = NeutronMultigroupData(
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index be9c51c33..b8158afc2 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -310,24 +310,37 @@ def _finalize_compilation(self) -> None:
 
         settings = self.settings
 
-        # Require one shared grid unless multigrid was explicitly enabled
-        neutron_multigroup_data = [
-            model for model in self.neutron_multigroup_data if model.G > 0
-        ]
-        if (
-            not self.technique.neutron_multigroup.multigrid
-            and len(neutron_multigroup_data) > 1
-        ):
-            shared_grid = neutron_multigroup_data[0].energy_grid
-            if any(
-                not np.array_equal(model.energy_grid, shared_grid)
-                for model in neutron_multigroup_data[1:]
-            ):
-                print_error(
-                    "Neutron multigroup energy grids must be identical unless "
-                    "simulation.technique.neutron_multigroup(multigrid=True) is "
-                    "configured."
-                )
+        # Select standard multigroup or hybrid neutron transport.
+        materials_have_native_composition = any(
+            material.nuclide_composition or material.element_composition
+            for material in self.materials
+        )
+        materials_have_multigroup = bool(self.materials) and all(
+            material.has_neutron_multigroup for material in self.materials
+        )
+        multigroup_grids_are_identical = False
+        if materials_have_multigroup:
+            shared_grid = self.materials[0].neutron_multigroup.energy_grid
+            multigroup_grids_are_identical = all(
+                np.array_equal(material.neutron_multigroup.energy_grid, shared_grid)
+                for material in self.materials[1:]
+            )
+
+        self.technique.neutron_multigroup.hybrid = not (
+            not materials_have_native_composition
+            and materials_have_multigroup
+            and multigroup_grids_are_identical
+        )
+
+        # Require physical energy boundaries wherever energy selects local groups.
+        if self.technique.neutron_multigroup.hybrid:
+            for material in self.materials:
+                model = material.neutron_multigroup
+                if model.G > 0 and not np.any(model.energy_grid):
+                    print_error(
+                        "Hybrid neutron multigroup transport requires an explicit "
+                        "energy_grid for every multigroup material."
+                    )
 
         # Limit transport to the latest requested tally boundary
         settings.time_boundary = min(
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 2bfe444e7..a526d63f3 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -104,8 +104,8 @@ class Source(MCDCObject):
     - otherwise, the default direction behavior is used.
 
     ``energy`` and ``group`` are independent source variables and may both be
-    supplied. When shared-grid neutron multigroup transport is used, ``group``
-    takes precedence over ``energy`` when both are provided.
+    supplied. When compilation selects standard neutron multigroup transport,
+    ``group`` takes precedence over ``energy`` when both are provided.
     Array-like inputs may be supplied as lists, tuples, or NumPy arrays.
 
     Examples
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index ae4b54619..59b7d56e1 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -12,35 +12,16 @@
 # ======================================================================================
 
 
-class NeutronMultigroupTechnique(MCDCBase):
-    """Configure simulation-wide neutron multigroup behavior."""
+class NeutronMultigroup(MCDCBase):
+    """Describe whether neutron multigroup transport is standard or hybrid."""
 
     # MC/DC framework metadata
     label = "neutron_multigroup"
 
-    multigrid: bool
+    hybrid: bool  # Whether neutron multigroup transport is hybrid
 
     def __init__(self):
-        self.multigrid = False
-
-    def __call__(self, multigrid: bool = False):
-        """Configure whether multiple neutron energy grids are allowed.
-
-        Parameters
-        ----------
-        multigrid : bool, optional
-            Allow materials to use different neutron multigroup energy grids.
-            By default, compilation requires one shared grid.
-
-        Examples
-        --------
-        Allow material-local neutron multigroup grids:
-
-        >>> import mcdc
-        >>> simulation = mcdc.Simulation()
-        >>> simulation.technique.neutron_multigroup(multigrid=True)
-        """
-        self.multigrid = multigrid
+        self.hybrid = True
 
 
 # ======================================================================================
@@ -389,7 +370,7 @@ class Technique(MCDCBase):
     # MC/DC framework metadata
     label = "technique"
 
-    neutron_multigroup: NeutronMultigroupTechnique
+    neutron_multigroup: NeutronMultigroup
     implicit_capture: ImplicitCapture
     weighted_emission: WeightedEmission
     global_weight_roulette: GlobalWeightRoulette
@@ -398,7 +379,7 @@ class Technique(MCDCBase):
 
     def __init__(self):
         # Construct every simulation-wide technique configuration
-        self.neutron_multigroup = NeutronMultigroupTechnique()
+        self.neutron_multigroup = NeutronMultigroup()
         self.implicit_capture = ImplicitCapture()
         self.weighted_emission = WeightedEmission()
         self.global_weight_roulette = GlobalWeightRoulette()
diff --git a/mcdc/object_/transport_model_data.py b/mcdc/object_/transport_model_data.py
index f91779cf0..05ceb83fc 100644
--- a/mcdc/object_/transport_model_data.py
+++ b/mcdc/object_/transport_model_data.py
@@ -33,9 +33,9 @@ class NeutronMultigroupData(MCDCObject):
     and describes interactions using groupwise cross sections, production
     spectra, speeds, and delayed-precursor data. For a multigroup-only material,
     :meth:`mcdc.Material.multigroup` provides the convenient entry point.
-    Construct ``NeutronMultigroupData`` directly to attach it alongside a
-    :ref:`native composition <user_native_transport>` over the energy range
-    defined by ``energy_grid``.
+    Construct ``NeutronMultigroupData`` directly when a material needs an
+    explicit physical energy grid, including when attaching it alongside a
+    :ref:`native composition <user_native_transport>`.
 
     Parameters
     ----------
@@ -76,25 +76,28 @@ class NeutronMultigroupData(MCDCObject):
         Decay constant in ``s^-1`` for each delayed precursor group, with
         shape ``(J,)``. Defaults to infinity.
     energy_grid : array_like of float, optional
-        Strictly increasing physical energy-group boundaries in eV with shape
-        ``(G + 1,)``. Group ``g`` spans
-        ``energy_grid[g] <= E < energy_grid[g + 1]``. The default is the
-        group-coordinate grid
-        ``[-0.5, 0.5, 1.5, ...]``.
+        Physical energy-group boundaries in eV with shape ``(G + 1,)``.
+        User-supplied boundaries must be strictly increasing, and group ``g``
+        spans ``energy_grid[g] <= E < energy_grid[g + 1]``. The default is a
+        zero-valued placeholder used only when physical energy mapping is not
+        required.
     energy_representation : str or int, optional
-        Policy used to reconstruct continuous energy from a group.
+        Policy used to reconstruct continuous energy from a group when a
+        physical energy grid participates in transport.
         ``"midpoint"`` uses the arithmetic midpoint, ``"log_midpoint"`` uses
         the geometric midpoint, ``"uniform"`` samples uniformly in energy,
         and ``"log_uniform"`` samples uniformly in log-energy. The default is
-        ``"midpoint"``. Logarithmic policies require positive boundaries.
+        ``"midpoint"``. Only the default ``"midpoint"`` placeholder is
+        accepted when ``energy_grid`` is omitted. Logarithmic policies require
+        positive boundaries.
         The corresponding ``NEUTRON_MULTIGROUP_ENERGY_*`` integer constants
         are also accepted.
 
     Notes
     -----
-    ``G`` is inferred from ``capture``, ``scatter``, or ``fission``. The
-    generated default energy grid uses the default ``"midpoint"``
-    representation.
+    ``G`` is inferred from ``capture``, ``scatter``, or ``fission``. An
+    explicit energy grid is required whenever simulation transport needs to
+    map continuous neutron energy to material-local groups.
 
     Examples
     --------
@@ -143,12 +146,10 @@ class NeutronMultigroupData(MCDCObject):
 
     # MC/DC framework metadata
     label = "neutron_multigroup_data"
-    non_numba = ["_uses_default_energy_grid"]
 
     G: int
     J: int
 
-    _uses_default_energy_grid: bool  # Non-Numba
     energy_grid: Annotated[NDArray[float64], ("G+1",)]
     energy_representation: int
 
@@ -252,14 +253,13 @@ def __init__(
         self.energy_representation = _resolve_energy_representation(
             energy_representation
         )
-        self._uses_default_energy_grid = energy_grid is None
         if energy_grid is None:
             if self.energy_representation != NEUTRON_MULTIGROUP_ENERGY_MIDPOINT:
                 print_error(
                     "NeutronMultigroupData requires an explicit energy_grid when "
                     "energy_representation is not 'midpoint'."
                 )
-            self.energy_grid = np.arange(self.G + 1, dtype=float64) - 0.5
+            self.energy_grid = np.zeros(self.G + 1, dtype=float64)
         else:
             if not np.all(np.isfinite(energy_grid)):
                 print_error("NeutronMultigroupData energy grid entries must be finite.")
diff --git a/test/unit/test_object_compilation.py b/test/unit/test_object_compilation.py
index fe3cea66b..c330d0871 100644
--- a/test/unit/test_object_compilation.py
+++ b/test/unit/test_object_compilation.py
@@ -47,33 +47,74 @@ def test_simulation_reserves_zero_group_mg_as_id_zero():
     assert simulation.neutron_multigroup_data[0].compile_ID == simulation.compile_ID
 
 
-def test_simulation_requires_a_shared_neutron_multigroup_grid(capsys):
+def test_simulation_derives_hybrid_for_local_multigroup_grids():
     material_a = mcdc.Material.multigroup(capture=[0.1], energy_grid=[1.0, 2.0])
     material_b = mcdc.Material.multigroup(capture=[0.2], energy_grid=[2.0, 3.0])
     simulation = mcdc.Simulation()
     simulation.set_model([mcdc.Cell(fill=material_a), mcdc.Cell(fill=material_b)])
 
+    simulation.compile()
+
+    assert simulation.technique.neutron_multigroup.hybrid
+
+
+@pytest.mark.parametrize("explicit_grid", [False, True])
+def test_simulation_derives_standard_multigroup_for_shared_grid(
+    explicit_grid, prepare_simulation
+):
+    kwargs = {"energy_grid": [1.0, 2.0]} if explicit_grid else {}
+    material_a = mcdc.Material.multigroup(capture=[0.1], **kwargs)
+    material_b = mcdc.Material.multigroup(capture=[0.2], **kwargs)
+
+    simulation_container, _ = prepare_simulation(
+        cells=[mcdc.Cell(fill=material_a), mcdc.Cell(fill=material_b)]
+    )
+
+    simulation = simulation_container[0]
+    assert not simulation["technique"]["neutron_multigroup"]["hybrid"]
+
+
+def test_hybrid_multigroup_requires_explicit_energy_grids(capsys):
+    material_default = mcdc.Material.multigroup(capture=[0.1])
+    material_explicit = mcdc.Material.multigroup(capture=[0.2], energy_grid=[2.0, 3.0])
+    simulation = mcdc.Simulation()
+    simulation.set_model(
+        [mcdc.Cell(fill=material_default), mcdc.Cell(fill=material_explicit)]
+    )
+
     with pytest.raises(SystemExit):
         simulation.compile()
 
-    assert "energy grids must be identical" in capsys.readouterr().out
+    assert "requires an explicit energy_grid" in capsys.readouterr().out
 
 
-def test_neutron_multigroup_technique_allows_and_packs_multigrid(
-    prepare_simulation,
-):
+def test_native_only_simulation_remains_hybrid(monkeypatch):
+    # Isolate mode finalization from native data-library loading.
+    def compile_nuclide(nuclide, simulation):
+        nuclide.fissionable = False
+        return MCDCObject._compile_into_simulation(nuclide, simulation)
+
+    monkeypatch.setattr(Nuclide, "_compile_into_simulation", compile_nuclide)
+    monkeypatch.setattr(Nuclide, "set_neutron_data", lambda self, simulation: None)
+    material = mcdc.Material(nuclide_composition={"H1": 0.1})
+    simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell(fill=material)])
+
+    simulation.compile()
+
+    assert simulation.technique.neutron_multigroup.hybrid
+
+
+def test_local_multigroup_grids_pack_hybrid(prepare_simulation):
     material_a = mcdc.Material.multigroup(capture=[0.1], energy_grid=[1.0, 2.0])
     material_b = mcdc.Material.multigroup(capture=[0.2], energy_grid=[2.0, 3.0])
 
     simulation_container, _ = prepare_simulation(
-        cells=[mcdc.Cell(fill=material_a), mcdc.Cell(fill=material_b)],
-        configure=lambda simulation: simulation.technique.neutron_multigroup(
-            multigrid=True
-        ),
+        cells=[mcdc.Cell(fill=material_a), mcdc.Cell(fill=material_b)]
     )
 
     simulation = simulation_container[0]
-    assert simulation["technique"]["neutron_multigroup"]["multigrid"]
+    assert simulation["technique"]["neutron_multigroup"]["hybrid"]
 
 
 def test_mcdc_object_compiles_object_members_and_lists():
diff --git a/test/unit/test_transport_model_data.py b/test/unit/test_transport_model_data.py
index 45ca48122..b96ff1538 100644
--- a/test/unit/test_transport_model_data.py
+++ b/test/unit/test_transport_model_data.py
@@ -31,10 +31,8 @@ def test_zero_group_placeholder():
     assert (
         neutron_multigroup.energy_representation == NEUTRON_MULTIGROUP_ENERGY_MIDPOINT
     )
-    assert neutron_multigroup._uses_default_energy_grid
-    assert "_uses_default_energy_grid" in neutron_multigroup.non_numba
 
-    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [-0.5])
+    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [0.0])
     np.testing.assert_array_equal(neutron_multigroup.speed, [])
     np.testing.assert_array_equal(neutron_multigroup.decay_rate, [])
     np.testing.assert_array_equal(neutron_multigroup.capture, [])
@@ -58,7 +56,7 @@ def test_capture_only_defaults():
     assert neutron_multigroup.J == 0
     assert not neutron_multigroup.fissionable
 
-    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [-0.5, 0.5, 1.5])
+    np.testing.assert_array_equal(neutron_multigroup.energy_grid, [0.0, 0.0, 0.0])
     np.testing.assert_array_equal(neutron_multigroup.speed, [1.0, 1.0])
     np.testing.assert_array_equal(neutron_multigroup.capture, [0.1, 0.2])
     np.testing.assert_array_equal(neutron_multigroup.scatter, [0.0, 0.0])
@@ -182,7 +180,7 @@ def test_standalone_mg_registration_and_packing(prepare_simulation):
     assert packed["G"] == 2
 
     np.testing.assert_array_equal(
-        get_neutron_multigroup_data.energy_grid_all(reserved, data), [-0.5]
+        get_neutron_multigroup_data.energy_grid_all(reserved, data), [0.0]
     )
     np.testing.assert_array_equal(
         get_neutron_multigroup_data.energy_grid_all(packed, data),
@@ -222,7 +220,6 @@ def test_energy_grid_and_representation(policy, expected):
     )
 
     assert neutron_multigroup.energy_representation == expected
-    assert not neutron_multigroup._uses_default_energy_grid
     np.testing.assert_array_equal(neutron_multigroup.energy_grid, [1.0e-5, 1.0, 20.0e6])
 
 

From 3d7567b314ca2dd510105fddadd92949038de48e Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 16:01:01 +0700
Subject: [PATCH 154/202] implement new design in transport

---
 mcdc/transport/physics/neutron/multigroup.py | 154 ++++++++++++-------
 1 file changed, 100 insertions(+), 54 deletions(-)

diff --git a/mcdc/transport/physics/neutron/multigroup.py b/mcdc/transport/physics/neutron/multigroup.py
index dcf3fc5ac..3bb4fe824 100644
--- a/mcdc/transport/physics/neutron/multigroup.py
+++ b/mcdc/transport/physics/neutron/multigroup.py
@@ -64,15 +64,7 @@ def particle_speed(particle_container, simulation, data):
     mgxs_ID = material["neutron_multigroup_ID"]
     mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
 
-    if simulation["technique"]["neutron_multigroup"]["hybrid"]:
-        E = particle["E"]
-        offset = mgxs["energy_grid_offset"]
-        length = mgxs["energy_grid_length"]
-        E_grid = data[offset : offset + length]
-        group = util.find_bin(E, E_grid)
-
-    else:
-        group = particle["group"]
+    group = _get_energy_group(particle["E"], mgxs, simulation, data)
 
     return mcdc_get.neutron_multigroup_data.speed(group, mgxs, data)
 
@@ -85,38 +77,46 @@ def particle_speed(particle_container, simulation, data):
 @njit
 def macro_xs(reaction_type, particle_container, simulation, data):
     particle = particle_container[0]
-    material = simulation["multigroup_materials"][particle["material_ID"]]
-    g = particle["g"]
+    material = simulation["materials"][particle["material_ID"]]
+
+    mgxs_ID = material["neutron_multigroup_ID"]
+    mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
+
+    group = _get_energy_group(particle["E"], mgxs, simulation, data)
 
     if reaction_type == NEUTRON_REACTION_TOTAL:
-        return mcdc_get.multigroup_material.mgxs_total(g, material, data)
+        return mcdc_get.neutron_multigroup_data.total(group, mgxs, data)
     elif reaction_type == NEUTRON_REACTION_CAPTURE:
-        return mcdc_get.multigroup_material.mgxs_capture(g, material, data)
+        return mcdc_get.neutron_multigroup_data.capture(group, mgxs, data)
     elif reaction_type == NEUTRON_REACTION_ELASTIC_SCATTERING:
-        return mcdc_get.multigroup_material.mgxs_scatter(g, material, data)
+        return mcdc_get.neutron_multigroup_data.scatter(group, mgxs, data)
     elif reaction_type == NEUTRON_REACTION_FISSION:
-        return mcdc_get.multigroup_material.mgxs_fission(g, material, data)
+        return mcdc_get.neutron_multigroup_data.fission(group, mgxs, data)
     return 0.0
 
 
 @njit
 def neutron_production_xs(reaction_type, particle_container, simulation, data):
     particle = particle_container[0]
-    material = simulation["multigroup_materials"][particle["material_ID"]]
-    g = particle["g"]
+    material = simulation["materials"][particle["material_ID"]]
+
+    mgxs_ID = material["neutron_multigroup_ID"]
+    mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
+
+    group = _get_energy_group(particle["E"], mgxs, simulation, data)
 
     # Total production
     if reaction_type == NEUTRON_REACTION_TOTAL:
         total = 0.0
 
         # Scattering production
-        nu = mcdc_get.multigroup_material.mgxs_nu_s(g, material, data)
-        xs = mcdc_get.multigroup_material.mgxs_scatter(g, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_s(group, material, data)
+        xs = mcdc_get.neutron_multigroup_data.scatter(group, material, data)
         total += nu * xs
 
         # Fission production
-        nu = mcdc_get.multigroup_material.mgxs_nu_f(g, material, data)
-        xs = mcdc_get.multigroup_material.mgxs_fission(g, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_f(group, material, data)
+        xs = mcdc_get.neutron_multigroup_data.fission(group, material, data)
         total += nu * xs
         return total
 
@@ -126,26 +126,26 @@ def neutron_production_xs(reaction_type, particle_container, simulation, data):
 
     # Scattering production
     elif reaction_type == NEUTRON_REACTION_ELASTIC_SCATTERING:
-        nu = mcdc_get.multigroup_material.mgxs_nu_s(g, material, data)
-        xs = mcdc_get.multigroup_material.mgxs_scatter(g, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_s(group, material, data)
+        xs = mcdc_get.neutron_multigroup_data.scatter(group, material, data)
         return nu * xs
 
     # Fission production
     elif reaction_type == NEUTRON_REACTION_FISSION:
-        nu = mcdc_get.multigroup_material.mgxs_nu_f(g, material, data)
-        xs = mcdc_get.multigroup_material.mgxs_fission(g, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_f(group, material, data)
+        xs = mcdc_get.neutron_multigroup_data.fission(group, material, data)
         return nu * xs
 
     # Prompt fission production
     elif reaction_type == NEUTRON_REACTION_FISSION_PROMPT:
-        nu = mcdc_get.multigroup_material.mgxs_nu_p(g, material, data)
-        xs = mcdc_get.multigroup_material.mgxs_fission(g, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_p(group, material, data)
+        xs = mcdc_get.neutron_multigroup_data.fission(group, material, data)
         return nu * xs
 
     # Delayed neutron production
     elif reaction_type == NEUTRON_REACTION_FISSION_DELAYED:
-        nu = mcdc_get.multigroup_material.mgxs_nu_d_total(g, material, data)
-        xs = mcdc_get.multigroup_material.mgxs_fission(g, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_d_total(group, material, data)
+        xs = mcdc_get.neutron_multigroup_data.fission(group, material, data)
         return nu * xs
 
     # Unsupported default
@@ -196,17 +196,19 @@ def collision(particle_container, collision_data_container, program, data):
 @njit
 def scattering(particle_container, program, data):
     simulation = util.access_simulation(program)
+    particle = particle_container[0]
+    material = simulation["materials"][particle["material_ID"]]
+
+    # Material attributes
+    mgxs_ID = material["neutron_multigroup_ID"]
+    mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
+    G = material["G"]
 
     # Particle attributes
-    particle = particle_container[0]
-    g = particle["g"]
     ux = particle["ux"]
     uy = particle["uy"]
     uz = particle["uz"]
-
-    # Material attributes
-    material = simulation["multigroup_materials"][particle["material_ID"]]
-    G = material["G"]
+    group = _get_energy_group(particle["E"], mgxs, simulation, data)
 
     # Kill the current particle
     particle["alive"] = False
@@ -220,7 +222,7 @@ def scattering(particle_container, program, data):
         weight_product = weight_target
 
     # Get number of secondaries
-    nu_s = mcdc_get.multigroup_material.mgxs_nu_s(g, material, data)
+    nu_s = mcdc_get.neutron_multigroup_data.nu_s(group, material, data)
     N = int(math.floor(weight_production * nu_s + rng.lcg(particle_container)))
 
     # Set up secondary partice container
@@ -247,18 +249,22 @@ def scattering(particle_container, program, data):
 
         # Get outgoing spectrum
         stride = material["G"]
-        start = material["mgxs_chi_s_offset"] + g * stride
+        start = material["mgxs_chi_s_offset"] + group * stride
         chi_s = data[start : start + stride]
-        # Above is equivalent to: chi_s = mcdc_get.multigroup_material.mgxs_chi_s_vector(g, material, data)
+        # Above is equivalent to: chi_s = mcdc_get.neutron_multigroup_data.chi_s_vector(group, material, data)
 
         # Sample outgoing energy
         xi = rng.lcg(particle_container_new)
         total = 0.0
-        for g_out in range(G):
-            total += chi_s[g_out]
+        group_out = 0
+        for group_out in range(G):
+            total += chi_s[group_out]
             if total > xi:
                 break
-        particle_new["g"] = g_out
+        particle_new["group"] = group_out
+        particle_new["E"] = _get_group_energy(
+            particle_container, mgxs, simulation, data
+        )
 
         # Bank, but keep it if it is the last particle
         if n == N - 1:
@@ -266,7 +272,7 @@ def scattering(particle_container, program, data):
             particle["ux"] = particle_new["ux"]
             particle["uy"] = particle_new["uy"]
             particle["uz"] = particle_new["uz"]
-            particle["g"] = particle_new["g"]
+            particle["group"] = particle_new["group"]
             particle["E"] = particle_new["E"]
             particle["w"] = particle_new["w"]
         else:
@@ -280,10 +286,10 @@ def fission(particle_container, program, data):
 
     # Particle properties
     particle = particle_container[0]
-    g = particle["g"]
+    g = particle["group"]
 
     # Material properties
-    material = simulation["multigroup_materials"][particle["material_ID"]]
+    material = simulation["materials"][particle["material_ID"]]
     G = material["G"]
     J = material["J"]
 
@@ -299,13 +305,13 @@ def fission(particle_container, program, data):
         weight_product = weight_target
 
     # Fission yields
-    nu = mcdc_get.multigroup_material.mgxs_nu_f(g, material, data)
-    nu_p = mcdc_get.multigroup_material.mgxs_nu_p(g, material, data)
+    nu = mcdc_get.neutron_multigroup_data.nu_f(group, material, data)
+    nu_p = mcdc_get.neutron_multigroup_data.nu_p(group, material, data)
     if J > 0:
         stride = material["J"]
         start = material["mgxs_nu_d_offset"] + g * stride
         nu_d = data[start : start + stride]
-        # Above is equivalent to: nu_d = mcdc_get.multigroup_material.mgxs_nu_d_vector(g, material, data)
+        # Above is equivalent to: nu_d = mcdc_get.neutron_multigroup_data.nu_d_vector(group, material, data)
 
     # Get number of secondaries
     N = int(
@@ -340,7 +346,7 @@ def fission(particle_container, program, data):
             stride = material["G"]
             start = material["mgxs_chi_p_offset"] + g * stride
             spectrum = data[start : start + stride]
-            # Above is equivalent to: spectrum = mcdc_get.multigroup_material.mgxs_chi_p_vector(g, material, data)
+            # Above is equivalent to: spectrum = mcdc_get.neutron_multigroup_data.chi_p_vector(group, material, data)
         else:
             prompt = False
 
@@ -352,10 +358,10 @@ def fission(particle_container, program, data):
                     start = material["mgxs_chi_d_offset"] + j * stride
                     spectrum = data[start : start + stride]
                     # Above is equivalent to:
-                    # spectrum = mcdc_get.multigroup_material.mgxs_chi_d_vector(
+                    # spectrum = mcdc_get.neutron_multigroup_data.chi_d_vector(
                     #     j, material, data
                     # )
-                    decay = mcdc_get.multigroup_material.mgxs_decay_rate(
+                    decay = mcdc_get.neutron_multigroup_data.decay_rate(
                         j, material, data
                     )
                     break
@@ -363,11 +369,11 @@ def fission(particle_container, program, data):
         # Sample outgoing energy
         xi = rng.lcg(particle_container_new)
         tot = 0.0
-        for g_out in range(G):
-            tot += spectrum[g_out]
+        for group_out in range(G):
+            tot += spectrum[group_out]
             if tot > xi:
                 break
-        particle_new["g"] = g_out
+        particle_new["group"] = group_out
 
         # Sample emission time
         if not prompt:
@@ -407,7 +413,7 @@ def fission(particle_container, program, data):
                 particle["uy"] = particle_new["uy"]
                 particle["uz"] = particle_new["uz"]
                 particle["t"] = particle_new["t"]
-                particle["g"] = particle_new["g"]
+                particle["group"] = particle_new["group"]
                 particle["E"] = particle_new["E"]
                 particle["w"] = particle_new["w"]
             else:
@@ -424,3 +430,43 @@ def fission(particle_container, program, data):
         else:
             # Particle will participate after the current census is completed
             particle_bank_module.bank_census_particle(particle_container_new, program)
+
+
+# ======================================================================================
+# Helpers
+# ======================================================================================
+
+
+@njit
+def _get_energy_group(particle_container, mgxs, simulation, data):
+    particle = particle_container[0]
+
+    if simulation["technique"]["neutron_multigroup"]["hybrid"]:
+        E = particle["E"]
+        offset = mgxs["energy_grid_offset"]
+        length = mgxs["energy_grid_length"]
+        E_grid = data[offset : offset + length]
+        group = util.find_bin(E, E_grid)
+
+    else:
+        group = particle["group"]
+
+    return group
+
+
+@njit
+def _get_group_energy(particle_container, mgxs, simulation, data):
+    particle = particle_container[0]
+
+    if simulation["technique"]["neutron_multigroup"]["hybrid"]:
+        E = particle["E"]
+        E_low = mcdc_get.neutron_multigroup_data.energy_grid(0, mgxs, data)
+        E_high = mcdc_get.neutron_multigroup_data.energy_grid_last(mgxs, data)
+
+        # TODO: Do the policy-based energy representation
+        energy = 0.0
+
+    else:
+        energy = 0.0
+
+    return energy

From 30e8837258fe21f91b0dd2166308aa0cc32255b0 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 16:22:36 +0700
Subject: [PATCH 155/202] implement new design in transport

---
 mcdc/transport/physics/neutron/multigroup.py | 123 +++++++++++--------
 1 file changed, 71 insertions(+), 52 deletions(-)

diff --git a/mcdc/transport/physics/neutron/multigroup.py b/mcdc/transport/physics/neutron/multigroup.py
index 3bb4fe824..47790561c 100644
--- a/mcdc/transport/physics/neutron/multigroup.py
+++ b/mcdc/transport/physics/neutron/multigroup.py
@@ -1,4 +1,3 @@
-import numpy as np
 import math
 
 from numba import njit
@@ -14,6 +13,10 @@
 
 from mcdc.constant import (
     PI,
+    NEUTRON_MULTIGROUP_ENERGY_MIDPOINT,
+    NEUTRON_MULTIGROUP_ENERGY_MIDPOINT_LOG,
+    NEUTRON_MULTIGROUP_ENERGY_UNIFORM,
+    NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG,
     NEUTRON_REACTION_TOTAL,
     NEUTRON_REACTION_CAPTURE,
     NEUTRON_REACTION_ELASTIC_SCATTERING,
@@ -45,7 +48,7 @@ def applicable(particle_container, simulation, data):
         E_min = mcdc_get.neutron_multigroup_data.energy_grid(0, mgxs, data)
         E_max = mcdc_get.neutron_multigroup_data.energy_grid_last(mgxs, data)
 
-        if E < E_min or E > E_max:
+        if E < E_min or E >= E_max:
             return False
 
     return True
@@ -64,7 +67,7 @@ def particle_speed(particle_container, simulation, data):
     mgxs_ID = material["neutron_multigroup_ID"]
     mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
 
-    group = _get_energy_group(particle["E"], mgxs, simulation, data)
+    group = _get_energy_group(particle_container, mgxs, simulation, data)
 
     return mcdc_get.neutron_multigroup_data.speed(group, mgxs, data)
 
@@ -82,7 +85,7 @@ def macro_xs(reaction_type, particle_container, simulation, data):
     mgxs_ID = material["neutron_multigroup_ID"]
     mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
 
-    group = _get_energy_group(particle["E"], mgxs, simulation, data)
+    group = _get_energy_group(particle_container, mgxs, simulation, data)
 
     if reaction_type == NEUTRON_REACTION_TOTAL:
         return mcdc_get.neutron_multigroup_data.total(group, mgxs, data)
@@ -103,20 +106,20 @@ def neutron_production_xs(reaction_type, particle_container, simulation, data):
     mgxs_ID = material["neutron_multigroup_ID"]
     mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
 
-    group = _get_energy_group(particle["E"], mgxs, simulation, data)
+    group = _get_energy_group(particle_container, mgxs, simulation, data)
 
     # Total production
     if reaction_type == NEUTRON_REACTION_TOTAL:
         total = 0.0
 
         # Scattering production
-        nu = mcdc_get.neutron_multigroup_data.nu_s(group, material, data)
-        xs = mcdc_get.neutron_multigroup_data.scatter(group, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_s(group, mgxs, data)
+        xs = mcdc_get.neutron_multigroup_data.scatter(group, mgxs, data)
         total += nu * xs
 
         # Fission production
-        nu = mcdc_get.neutron_multigroup_data.nu_f(group, material, data)
-        xs = mcdc_get.neutron_multigroup_data.fission(group, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_f(group, mgxs, data)
+        xs = mcdc_get.neutron_multigroup_data.fission(group, mgxs, data)
         total += nu * xs
         return total
 
@@ -126,26 +129,26 @@ def neutron_production_xs(reaction_type, particle_container, simulation, data):
 
     # Scattering production
     elif reaction_type == NEUTRON_REACTION_ELASTIC_SCATTERING:
-        nu = mcdc_get.neutron_multigroup_data.nu_s(group, material, data)
-        xs = mcdc_get.neutron_multigroup_data.scatter(group, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_s(group, mgxs, data)
+        xs = mcdc_get.neutron_multigroup_data.scatter(group, mgxs, data)
         return nu * xs
 
     # Fission production
     elif reaction_type == NEUTRON_REACTION_FISSION:
-        nu = mcdc_get.neutron_multigroup_data.nu_f(group, material, data)
-        xs = mcdc_get.neutron_multigroup_data.fission(group, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_f(group, mgxs, data)
+        xs = mcdc_get.neutron_multigroup_data.fission(group, mgxs, data)
         return nu * xs
 
     # Prompt fission production
     elif reaction_type == NEUTRON_REACTION_FISSION_PROMPT:
-        nu = mcdc_get.neutron_multigroup_data.nu_p(group, material, data)
-        xs = mcdc_get.neutron_multigroup_data.fission(group, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_p(group, mgxs, data)
+        xs = mcdc_get.neutron_multigroup_data.fission(group, mgxs, data)
         return nu * xs
 
     # Delayed neutron production
     elif reaction_type == NEUTRON_REACTION_FISSION_DELAYED:
-        nu = mcdc_get.neutron_multigroup_data.nu_d_total(group, material, data)
-        xs = mcdc_get.neutron_multigroup_data.fission(group, material, data)
+        nu = mcdc_get.neutron_multigroup_data.nu_d_total(group, mgxs, data)
+        xs = mcdc_get.neutron_multigroup_data.fission(group, mgxs, data)
         return nu * xs
 
     # Unsupported default
@@ -202,13 +205,13 @@ def scattering(particle_container, program, data):
     # Material attributes
     mgxs_ID = material["neutron_multigroup_ID"]
     mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
-    G = material["G"]
+    G = mgxs["G"]
 
     # Particle attributes
     ux = particle["ux"]
     uy = particle["uy"]
     uz = particle["uz"]
-    group = _get_energy_group(particle["E"], mgxs, simulation, data)
+    group = _get_energy_group(particle_container, mgxs, simulation, data)
 
     # Kill the current particle
     particle["alive"] = False
@@ -222,7 +225,7 @@ def scattering(particle_container, program, data):
         weight_product = weight_target
 
     # Get number of secondaries
-    nu_s = mcdc_get.neutron_multigroup_data.nu_s(group, material, data)
+    nu_s = mcdc_get.neutron_multigroup_data.nu_s(group, mgxs, data)
     N = int(math.floor(weight_production * nu_s + rng.lcg(particle_container)))
 
     # Set up secondary partice container
@@ -248,10 +251,10 @@ def scattering(particle_container, program, data):
         particle_new["uz"] = uz_new
 
         # Get outgoing spectrum
-        stride = material["G"]
-        start = material["mgxs_chi_s_offset"] + group * stride
+        stride = mgxs["G"]
+        start = mgxs["chi_s_offset"] + group * stride
         chi_s = data[start : start + stride]
-        # Above is equivalent to: chi_s = mcdc_get.neutron_multigroup_data.chi_s_vector(group, material, data)
+        # Above is equivalent to: chi_s = mcdc_get.neutron_multigroup_data.chi_s_vector(group, mgxs, data)
 
         # Sample outgoing energy
         xi = rng.lcg(particle_container_new)
@@ -263,7 +266,7 @@ def scattering(particle_container, program, data):
                 break
         particle_new["group"] = group_out
         particle_new["E"] = _get_group_energy(
-            particle_container, mgxs, simulation, data
+            particle_container_new, mgxs, simulation, data
         )
 
         # Bank, but keep it if it is the last particle
@@ -282,16 +285,18 @@ def scattering(particle_container, program, data):
 @njit
 def fission(particle_container, program, data):
     simulation = util.access_simulation(program)
+    particle = particle_container[0]
+    material = simulation["materials"][particle["material_ID"]]
     settings = simulation["settings"]
 
-    # Particle properties
-    particle = particle_container[0]
-    g = particle["group"]
+    # Material attributes
+    mgxs_ID = material["neutron_multigroup_ID"]
+    mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
+    G = mgxs["G"]
+    J = mgxs["J"]
 
-    # Material properties
-    material = simulation["materials"][particle["material_ID"]]
-    G = material["G"]
-    J = material["J"]
+    # Particle attributes
+    group = _get_energy_group(particle_container, mgxs, simulation, data)
 
     # Kill the current particle
     particle["alive"] = False
@@ -305,13 +310,13 @@ def fission(particle_container, program, data):
         weight_product = weight_target
 
     # Fission yields
-    nu = mcdc_get.neutron_multigroup_data.nu_f(group, material, data)
-    nu_p = mcdc_get.neutron_multigroup_data.nu_p(group, material, data)
+    nu = mcdc_get.neutron_multigroup_data.nu_f(group, mgxs, data)
+    nu_p = mcdc_get.neutron_multigroup_data.nu_p(group, mgxs, data)
     if J > 0:
-        stride = material["J"]
-        start = material["mgxs_nu_d_offset"] + g * stride
+        stride = mgxs["J"]
+        start = mgxs["nu_d_offset"] + group * stride
         nu_d = data[start : start + stride]
-        # Above is equivalent to: nu_d = mcdc_get.neutron_multigroup_data.nu_d_vector(group, material, data)
+        # Above is equivalent to: nu_d = mcdc_get.neutron_multigroup_data.nu_d_vector(group, mgxs, data)
 
     # Get number of secondaries
     N = int(
@@ -343,10 +348,10 @@ def fission(particle_container, program, data):
         total = nu_p
         if xi < total:
             prompt = True
-            stride = material["G"]
-            start = material["mgxs_chi_p_offset"] + g * stride
+            stride = mgxs["G"]
+            start = mgxs["chi_p_offset"] + group * stride
             spectrum = data[start : start + stride]
-            # Above is equivalent to: spectrum = mcdc_get.neutron_multigroup_data.chi_p_vector(group, material, data)
+            # Above is equivalent to: spectrum = mcdc_get.neutron_multigroup_data.chi_p_vector(group, mgxs, data)
         else:
             prompt = False
 
@@ -354,16 +359,14 @@ def fission(particle_container, program, data):
             for j in range(J):
                 total += nu_d[j]
                 if xi < total:
-                    stride = material["G"]
-                    start = material["mgxs_chi_d_offset"] + j * stride
+                    stride = mgxs["G"]
+                    start = mgxs["chi_d_offset"] + j * stride
                     spectrum = data[start : start + stride]
                     # Above is equivalent to:
                     # spectrum = mcdc_get.neutron_multigroup_data.chi_d_vector(
-                    #     j, material, data
+                    #     j, mgxs, data
                     # )
-                    decay = mcdc_get.neutron_multigroup_data.decay_rate(
-                        j, material, data
-                    )
+                    decay = mcdc_get.neutron_multigroup_data.decay_rate(j, mgxs, data)
                     break
 
         # Sample outgoing energy
@@ -374,6 +377,9 @@ def fission(particle_container, program, data):
             if tot > xi:
                 break
         particle_new["group"] = group_out
+        particle_new["E"] = _get_group_energy(
+            particle_container_new, mgxs, simulation, data
+        )
 
         # Sample emission time
         if not prompt:
@@ -446,7 +452,7 @@ def _get_energy_group(particle_container, mgxs, simulation, data):
         offset = mgxs["energy_grid_offset"]
         length = mgxs["energy_grid_length"]
         E_grid = data[offset : offset + length]
-        group = util.find_bin(E, E_grid)
+        group = util.find_bin_with_rules(E, E_grid, 0.0, False)
 
     else:
         group = particle["group"]
@@ -459,12 +465,25 @@ def _get_group_energy(particle_container, mgxs, simulation, data):
     particle = particle_container[0]
 
     if simulation["technique"]["neutron_multigroup"]["hybrid"]:
-        E = particle["E"]
-        E_low = mcdc_get.neutron_multigroup_data.energy_grid(0, mgxs, data)
-        E_high = mcdc_get.neutron_multigroup_data.energy_grid_last(mgxs, data)
-
-        # TODO: Do the policy-based energy representation
-        energy = 0.0
+        group = particle["group"]
+        E_low = mcdc_get.neutron_multigroup_data.energy_grid(group, mgxs, data)
+        E_high = mcdc_get.neutron_multigroup_data.energy_grid(group + 1, mgxs, data)
+        representation = mgxs["energy_representation"]
+
+        if representation == NEUTRON_MULTIGROUP_ENERGY_MIDPOINT:
+            energy = 0.5 * (E_low + E_high)
+        elif representation == NEUTRON_MULTIGROUP_ENERGY_MIDPOINT_LOG:
+            energy = math.sqrt(E_low * E_high)
+        elif representation == NEUTRON_MULTIGROUP_ENERGY_UNIFORM:
+            xi = rng.lcg(particle_container)
+            energy = E_low + xi * (E_high - E_low)
+        elif representation == NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG:
+            xi = rng.lcg(particle_container)
+            log_E_low = math.log(E_low)
+            energy = math.exp(log_E_low + xi * (math.log(E_high) - log_E_low))
+        else:
+            # Unreachable
+            energy = -1.0
 
     else:
         energy = 0.0

From a04cf3d1789a43ef21570d488ed4f2335b3312bd Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Fri, 7 Aug 2026 16:23:06 +0700
Subject: [PATCH 156/202] add test

---
 test/unit/transport/test_multigroup.py | 162 +++++++++++++++++++++++++
 1 file changed, 162 insertions(+)
 create mode 100644 test/unit/transport/test_multigroup.py

diff --git a/test/unit/transport/test_multigroup.py b/test/unit/transport/test_multigroup.py
new file mode 100644
index 000000000..82aeb94b5
--- /dev/null
+++ b/test/unit/transport/test_multigroup.py
@@ -0,0 +1,162 @@
+import math
+
+import numpy as np
+import pytest
+
+import mcdc
+import mcdc.numba_types as type_
+import mcdc.transport.physics.neutron.multigroup as multigroup
+
+
+def _prepare_multigroup(prepare_simulation, **kwargs):
+    material = mcdc.Material.multigroup(
+        energy_grid=[1.0, 10.0, 100.0],
+        **kwargs,
+    )
+    simulation_container, data = prepare_simulation(cells=[mcdc.Cell(fill=material)])
+    simulation = simulation_container[0]
+    packed_material = simulation["materials"][0]
+    mgxs = simulation["neutron_multigroup_data"][
+        packed_material["neutron_multigroup_ID"]
+    ]
+    return simulation, mgxs, data
+
+
+@pytest.mark.parametrize(
+    "representation, expected",
+    [
+        ("midpoint", 55.0),
+        ("log_midpoint", math.sqrt(1000.0)),
+        ("uniform", None),
+        ("log_uniform", None),
+    ],
+)
+def test_group_energy_representation(representation, expected, prepare_simulation):
+    simulation, mgxs, data = _prepare_multigroup(
+        prepare_simulation,
+        capture=[1.0, 1.0],
+        energy_representation=representation,
+    )
+    simulation["technique"]["neutron_multigroup"]["hybrid"] = True
+
+    particle_container = np.zeros(1, dtype=type_.particle)
+    particle_container[0]["group"] = 1
+    particle_container[0]["rng_seed"] = np.uint64(1)
+
+    energy = multigroup._get_group_energy(particle_container, mgxs, simulation, data)
+
+    if expected is None:
+        assert 10.0 <= energy < 100.0
+    else:
+        assert energy == pytest.approx(expected)
+
+
+def test_standard_multigroup_does_not_reconstruct_energy(prepare_simulation):
+    simulation, mgxs, data = _prepare_multigroup(
+        prepare_simulation,
+        capture=[1.0, 1.0],
+    )
+
+    particle_container = np.zeros(1, dtype=type_.particle)
+    particle_container[0]["group"] = 1
+
+    energy = multigroup._get_group_energy(particle_container, mgxs, simulation, data)
+
+    assert energy == 0.0
+
+
+def test_hybrid_energy_groups_are_left_closed(prepare_simulation):
+    simulation, mgxs, data = _prepare_multigroup(
+        prepare_simulation,
+        capture=[1.0, 1.0],
+    )
+    simulation["technique"]["neutron_multigroup"]["hybrid"] = True
+
+    particle_container = np.zeros(1, dtype=type_.particle)
+    particle = particle_container[0]
+    particle["material_ID"] = 0
+
+    particle["E"] = 1.0
+    assert multigroup.applicable(particle_container, simulation, data)
+    assert multigroup._get_energy_group(particle_container, mgxs, simulation, data) == 0
+
+    particle["E"] = 10.0
+    assert multigroup._get_energy_group(particle_container, mgxs, simulation, data) == 1
+
+    particle["E"] = 100.0
+    assert not multigroup.applicable(particle_container, simulation, data)
+
+
+def _make_particle():
+    particle_container = np.zeros(1, dtype=type_.particle)
+    particle = particle_container[0]
+    particle["material_ID"] = 0
+    particle["alive"] = True
+    particle["E"] = 5.0
+    particle["w"] = 1.0
+    particle["uz"] = 1.0
+    particle["rng_seed"] = np.uint64(1)
+    return particle_container
+
+
+def _assert_fission_products(particle_container, simulation):
+    particle = particle_container[0]
+    assert particle["alive"]
+    assert particle["group"] == 1
+    assert particle["E"] == pytest.approx(55.0)
+
+    bank = simulation["bank_active"]
+    assert bank["size"][0] == 3
+    banked = bank["particle_data"][:3]
+    np.testing.assert_array_equal(banked["group"], 1)
+    np.testing.assert_allclose(banked["E"], 55.0)
+
+
+def test_scattering_product_uses_multigroup_data(prepare_simulation):
+    simulation, _, data = _prepare_multigroup(
+        prepare_simulation,
+        scatter=[[0.0, 0.0], [1.0, 1.0]],
+    )
+    simulation["technique"]["neutron_multigroup"]["hybrid"] = True
+    particle_container = _make_particle()
+
+    multigroup.scattering(particle_container, simulation, data)
+
+    particle = particle_container[0]
+    assert particle["alive"]
+    assert particle["group"] == 1
+    assert particle["E"] == pytest.approx(55.0)
+
+
+def test_prompt_fission_products(prepare_simulation):
+    simulation, _, data = _prepare_multigroup(
+        prepare_simulation,
+        fission=[1.0, 1.0],
+        nu_p=[4.0, 4.0],
+        chi_p=[0.0, 1.0],
+    )
+    simulation["technique"]["neutron_multigroup"]["hybrid"] = True
+    particle_container = _make_particle()
+
+    multigroup.fission(particle_container, simulation, data)
+
+    _assert_fission_products(particle_container, simulation)
+    assert particle_container[0]["t"] == 0.0
+
+
+def test_delayed_fission_products(prepare_simulation):
+    simulation, _, data = _prepare_multigroup(
+        prepare_simulation,
+        fission=[1.0, 1.0],
+        nu_d=[[4.0, 4.0]],
+        chi_d=[[0.0], [1.0]],
+        decay_rate=[1.0],
+    )
+    simulation["technique"]["neutron_multigroup"]["hybrid"] = True
+    particle_container = _make_particle()
+
+    multigroup.fission(particle_container, simulation, data)
+
+    _assert_fission_products(particle_container, simulation)
+    assert particle_container[0]["t"] > 0.0
+    assert np.all(simulation["bank_active"]["particle_data"][:3]["t"] > 0.0)

From 692b128d0a8cc8299c4c17ed3d2268782feef057 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 8 Aug 2026 05:40:04 +0700
Subject: [PATCH 157/202] start removing particle\'s group attribute

---
 mcdc/numba_types.py        |  7 +--
 mcdc/object_/particle.py   |  7 +--
 mcdc/object_/source.py     | 97 ++++++++++++++++++--------------------
 mcdc/transport/particle.py |  1 -
 mcdc/transport/source.py   | 15 ++----
 test/unit/test_source.py   | 59 +++++++++--------------
 6 files changed, 78 insertions(+), 108 deletions(-)

diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index bc6e72a9f..d1407b6b6 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -18,7 +18,6 @@
     ('ux', float64),
     ('uy', float64),
     ('uz', float64),
-    ('group', int64),
     ('E', float64),
     ('w', float64),
     ('particle_type', int64),
@@ -39,7 +38,6 @@
     ('ux', float64),
     ('uy', float64),
     ('uz', float64),
-    ('group', int64),
     ('E', float64),
     ('w', float64),
     ('particle_type', int64),
@@ -608,12 +606,11 @@
     ('direction', float64, (3,)),
     ('polar_cosine', float64, (2,)),
     ('azimuthal', float64, (2,)),
-    ('mono_group', bool),
-    ('group', int64),
-    ('group_pmf_ID', int64),
     ('mono_energetic', bool),
+    ('discrete_energy', bool),
     ('energy', float64),
     ('energy_pdf_ID', int64),
+    ('energy_pmf_ID', int64),
     ('discrete_time', bool),
     ('time', float64),
     ('time_range', float64, (2,)),
diff --git a/mcdc/object_/particle.py b/mcdc/object_/particle.py
index 4855c9227..c28b925f0 100644
--- a/mcdc/object_/particle.py
+++ b/mcdc/object_/particle.py
@@ -13,11 +13,7 @@
 
 @dataclass
 class ParticleData(MCDCBase):
-    """Serializable phase-space state stored in particle banks.
-
-    ``group`` is an auxiliary integer state available to transport physics.
-    Neutron multigroup transport uses it as the neutron energy-group index.
-    """
+    """Serializable phase-space state stored in particle banks."""
 
     # MC/DC framework metadata
     label = "particle_data"
@@ -29,7 +25,6 @@ class ParticleData(MCDCBase):
     ux: float = 0.0
     uy: float = 0.0
     uz: float = 0.0
-    group: int = -1
     E: float = 0.0
     w: float = 0.0
     particle_type: int = PARTICLE_NEUTRON
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index a526d63f3..7e0e31d93 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -1,6 +1,6 @@
 import numpy as np
 
-from numbers import Integral, Real
+from numbers import Real
 from numpy import float64
 from numpy.typing import ArrayLike, NDArray
 from types import NoneType
@@ -28,9 +28,8 @@
 class Source(MCDCObject):
     """Distributions of particles introduced into the simulation.
 
-    A source specifies the position, direction, energy, time, particle type,
-    auxiliary group state, and relative sampling probability for emitted
-    particles.
+    A source specifies the position, direction, energy, time, particle type, and
+    relative sampling probability for emitted particles.
 
     Parameters
     ----------
@@ -68,14 +67,12 @@ class Source(MCDCObject):
         a tabulated distribution: the first row contains energy values and the
         second row contains their probability density in ``eV^-1``. Defaults
         to a mono-energetic source at **1 MeV**.
-    group : int or array_like, optional
-        Auxiliary integer state assigned to an emitted particle. A Python or
-        NumPy integer defines a mono-group source. An array-like value with
-        shape ``(2, N)`` defines a discrete probability mass function: the
-        first row contains integer group values and the second row contains
-        their probabilities. The physics using the group determines its
-        meaning; neutron multigroup transport interprets it as an energy-group
-        index. The default is **group 0**.
+    discrete_energy : array_like of float, optional
+        Discrete source-energy distribution with shape ``(2, N)``. The first
+        row contains sampled energy values and the second row contains their
+        probabilities. Values are physical energies in eV for continuous-energy
+        transport and group-coordinate energies for standard multigroup
+        transport. Cannot be supplied with ``energy``.
     time : real or array_like of float, optional
         Emission time in seconds. A real scalar, including a NumPy scalar,
         defines a discrete emission time. An array-like value with shape
@@ -103,11 +100,6 @@ class Source(MCDCObject):
       source;
     - otherwise, the default direction behavior is used.
 
-    ``energy`` and ``group`` are independent source variables and may both be
-    supplied. When compilation selects standard neutron multigroup transport,
-    ``group`` takes precedence over ``energy`` when both are provided.
-    Array-like inputs may be supplied as lists, tuples, or NumPy arrays.
-
     Examples
     --------
     Point source at the origin emitting mono-energetic neutrons isotropically:
@@ -150,10 +142,14 @@ class Source(MCDCObject):
     ...     azimuthal=[0.0, np.pi / 2],
     ... )
 
-    Source with a discrete group:
+    Sample discrete emission lines in a continuous-energy calculation:
 
-    >>> src = mcdc.Source(
-    ...     group=3,
+    >>> decay_electrons = mcdc.Source(
+    ...     particle_type="electron",
+    ...     discrete_energy=(
+    ...         [1.0e5, 2.0e5],
+    ...         [0.8, 0.2],
+    ...     ),
     ... )
 
     Sample a continuous-energy source from a tabulated probability density:
@@ -167,11 +163,11 @@ class Source(MCDCObject):
     ...     direction=[0.0, 0.0, 1.0],
     ... )
 
-    Sample between two groups:
+    Sample between groups 0 and 1 in standard multigroup transport:
 
     >>> multigroup_source = mcdc.Source(
-    ...     group=(
-    ...         [0, 1],
+    ...     discrete_energy=(
+    ...         [0.0, 1.0],
     ...         [0.25, 0.75],
     ...     ),
     ... )
@@ -203,15 +199,12 @@ class Source(MCDCObject):
     polar_cosine: Annotated[NDArray[float64], (2,)]
     azimuthal: Annotated[NDArray[float64], (2,)]
 
-    # Group
-    mono_group: bool
-    group: int
-    group_pmf: DistributionPMF
-
     # Energy
     mono_energetic: bool
+    discrete_energy: bool
     energy: float
     energy_pdf: DistributionTabulated
+    energy_pmf: DistributionPMF
 
     # Time
     discrete_time: bool
@@ -246,7 +239,7 @@ def __init__(
         azimuthal: Sequence[float] | NoneType = None,
         #
         energy: ArrayLike | NoneType = None,
-        group: ArrayLike | NoneType = None,
+        discrete_energy: ArrayLike | NoneType = None,
         #
         time: ArrayLike = 0.0,
         #
@@ -260,9 +253,11 @@ def __init__(
 
         # ==============================================================================
         # Default attributes
-        #   Point source at origin, isotropic, mono-group at 0,
+        #   Point source at origin,
+        #   isotropic,
         #   mono-energetic at 1 MeV,
-        #   time = 0, neutron
+        #   time = 0,
+        #   neutron
         # ==============================================================================
 
         # Position
@@ -280,18 +275,15 @@ def __init__(
         self.polar_cosine = np.array([-1.0, 1.0])
         self.azimuthal = np.array([0.0, 2.0 * PI])
 
-        # Group
-        self.mono_group = True
-        self.group = 0
-        self.group_pmf = DistributionPMF(np.array([0.0]), np.array([1.0]))
-
         # Energy
         self.mono_energetic = True
+        self.discrete_energy = False
         self.energy = 1.0e6
         self.energy_pdf = DistributionTabulated(
             np.array([1.0e6 - 1.0, 1.0e6 + 1.0]),
             np.array([1.0, 1.0]),
         )
+        self.energy_pmf = DistributionPMF(np.array([1.0e6]), np.array([1.0]))
 
         # Time
         self.discrete_time = True
@@ -341,18 +333,18 @@ def __init__(
         # Normalize direction
         self.direction /= np.linalg.norm(self.direction)
 
-        # Group
-        if group is not None:
-            if isinstance(group, Integral) and not isinstance(group, (bool, np.bool_)):
-                self.group = int(group)
-            else:
-                values, probabilities = _distribution_pair(group, "Group")
-                if not np.all(np.isfinite(values)) or not np.all(
-                    values == np.floor(values)
-                ):
-                    print_error("Group distribution values must be integers")
-                self.mono_group = False
-                self.group_pmf = DistributionPMF(values, probabilities)
+        # Require one unambiguous source-energy representation
+        if discrete_energy is not None and energy is not None:
+            print_error("Cannot specify both energy and discrete_energy.")
+
+        # Discrete energy
+        if discrete_energy is not None:
+            values, probabilities = _distribution_pair(
+                discrete_energy, "Discrete energy"
+            )
+            self.mono_energetic = False
+            self.discrete_energy = True
+            self.energy_pmf = DistributionPMF(values, probabilities)
 
         # Energy
         if energy is not None:
@@ -408,8 +400,13 @@ def __repr__(self):
             text += f"  - Direction [ux, uy, yz]: {self.direction}\n"
         elif self.white_direction:
             text += f"  - Isotropic halfspace: {self.direction}\n"
-        text += f"  - Group: {self.group if self.mono_group else 'PMF'}\n"
-        text += f"  - Energy: {f'{self.energy} eV' if self.mono_energetic else 'PDF'}\n"
+        if self.mono_energetic:
+            energy_text = f"{self.energy} eV"
+        elif self.discrete_energy:
+            energy_text = "PMF"
+        else:
+            energy_text = "PDF"
+        text += f"  - Energy: {energy_text}\n"
         if self.discrete_time:
             text += f"  - Time: {self.time} s\n"
         else:
diff --git a/mcdc/transport/particle.py b/mcdc/transport/particle.py
index 4297fa920..21c8f4b51 100644
--- a/mcdc/transport/particle.py
+++ b/mcdc/transport/particle.py
@@ -29,7 +29,6 @@ def copy(target_particle_container, source_particle_container):
     target_particle["ux"] = source_particle["ux"]
     target_particle["uy"] = source_particle["uy"]
     target_particle["uz"] = source_particle["uz"]
-    target_particle["group"] = source_particle["group"]
     target_particle["E"] = source_particle["E"]
     target_particle["w"] = source_particle["w"]
     target_particle["particle_type"] = source_particle["particle_type"]
diff --git a/mcdc/transport/source.py b/mcdc/transport/source.py
index 68fb89eab..51a4672cd 100644
--- a/mcdc/transport/source.py
+++ b/mcdc/transport/source.py
@@ -62,18 +62,14 @@ def source_particle(particle_container, seed, simulation, data):
             particle_container,
         )
 
-    # Group
-    if source["mono_group"]:
-        group = source["group"]
-    else:
-        ID = source["group_pmf_ID"]
-        sub_ID = simulation["distributions"][ID]["sub_ID"]
-        pmf = simulation["pmf_distributions"][sub_ID]
-        group = sample_pmf(pmf, particle_container, data)
-
     # Energy
     if source["mono_energetic"]:
         E = source["energy"]
+    elif source["discrete_energy"]:
+        ID = source["energy_pmf_ID"]
+        sub_ID = simulation["distributions"][ID]["sub_ID"]
+        pmf = simulation["pmf_distributions"][sub_ID]
+        E = sample_pmf(pmf, particle_container, data)
     else:
         ID = source["energy_pdf_ID"]
         sub_ID = simulation["distributions"][ID]["sub_ID"]
@@ -133,7 +129,6 @@ def source_particle(particle_container, seed, simulation, data):
     particle["ux"] = ux
     particle["uy"] = uy
     particle["uz"] = uz
-    particle["group"] = group
     particle["E"] = E
     particle["w"] = 1.0
     particle["particle_type"] = source["particle_type"]
diff --git a/test/unit/test_source.py b/test/unit/test_source.py
index 7c6b5c0a7..5eac04565 100644
--- a/test/unit/test_source.py
+++ b/test/unit/test_source.py
@@ -34,52 +34,42 @@ def test_energy_distribution(energy):
     source = mcdc.Source(energy=energy)
 
     assert not source.mono_energetic
+    assert not source.discrete_energy
     np.testing.assert_array_equal(source.energy_pdf.pdf.x, [9_999.0, 10_001.0])
 
 
-@pytest.mark.parametrize("group", [3, np.int64(3)])
-def test_scalar_group(group):
-    source = mcdc.Source(group=group)
-
-    assert source.mono_group
-    assert source.group == 3
-
-
 @pytest.mark.parametrize(
-    "group",
+    "discrete_energy",
     [
-        [[1, 3], [0.25, 0.75]],
-        ([1, 3], [0.25, 0.75]),
-        np.array([[1, 3], [0.25, 0.75]]),
+        [[9_999.0, 10_001.0], [0.25, 0.75]],
+        ([9_999.0, 10_001.0], [0.25, 0.75]),
+        np.array([[9_999.0, 10_001.0], [0.25, 0.75]]),
     ],
 )
-def test_group_distribution(group):
-    source = mcdc.Source(group=group)
+def test_discrete_energy_distribution(discrete_energy):
+    source = mcdc.Source(discrete_energy=discrete_energy)
 
-    assert not source.mono_group
-    np.testing.assert_array_equal(source.group_pmf.value, [1, 3])
+    assert not source.mono_energetic
+    assert source.discrete_energy
+    np.testing.assert_array_equal(source.energy_pmf.value, [9_999.0, 10_001.0])
+    assert "Energy: PMF" in repr(source)
 
 
-def test_group_distribution_rejects_noninteger_values(capsys):
+def test_energy_and_discrete_energy_are_mutually_exclusive(capsys):
     with pytest.raises(SystemExit):
-        mcdc.Source(group=[[1.5, 3.0], [0.25, 0.75]])
+        mcdc.Source(
+            energy=10_000.0,
+            discrete_energy=[[9_999.0, 10_001.0], [0.25, 0.75]],
+        )
 
-    assert "Group distribution values must be integers" in capsys.readouterr().out
-
-
-def test_energy_and_group_are_stored_independently():
-    source = mcdc.Source(energy=10_000.0, group=3)
-
-    assert source.energy == 10_000.0
-    assert source.group == 3
+    assert "Cannot specify both energy and discrete_energy" in capsys.readouterr().out
 
 
-def test_transport_source_sets_energy_and_group_independently(prepare_simulation):
+def test_transport_source_sets_mono_energy(prepare_simulation):
     source = mcdc.Source(
         position=[0.0, 0.0, 0.0],
         direction=[0.0, 0.0, 1.0],
         energy=10_000.0,
-        group=3,
     )
     simulation_container, data = prepare_simulation(sources=[source])
     particle_container = np.zeros(1, dtype=type_.particle)
@@ -92,15 +82,13 @@ def test_transport_source_sets_energy_and_group_independently(prepare_simulation
     )
 
     assert particle_container[0]["E"] == 10_000.0
-    assert particle_container[0]["group"] == 3
 
 
-def test_transport_source_samples_energy_and_group_independently(prepare_simulation):
+def test_transport_source_samples_discrete_energy(prepare_simulation):
     source = mcdc.Source(
         position=[0.0, 0.0, 0.0],
         direction=[0.0, 0.0, 1.0],
-        energy=([9_999.0, 10_001.0], [0.5, 0.5]),
-        group=([3], [1.0]),
+        discrete_energy=([10_001.0], [1.0]),
     )
     simulation_container, data = prepare_simulation(sources=[source])
     particle_container = np.zeros(1, dtype=type_.particle)
@@ -112,8 +100,7 @@ def test_transport_source_samples_energy_and_group_independently(prepare_simulat
         data,
     )
 
-    assert 9_999.0 <= particle_container[0]["E"] <= 10_001.0
-    assert particle_container[0]["group"] == 3
+    assert particle_container[0]["E"] == 10_001.0
 
 
 @pytest.mark.parametrize("time", [2, 2.0, np.int64(2), np.float64(2.0)])
@@ -144,8 +131,8 @@ def test_time_interval(time):
     [
         ({"energy": [1.0, 2.0, 3.0]}, "Energy distribution must have shape (2, N)"),
         (
-            {"group": [1, 2, 3]},
-            "Group distribution must have shape (2, N)",
+            {"discrete_energy": [1.0, 2.0, 3.0]},
+            "Discrete energy distribution must have shape (2, N)",
         ),
         ({"time": [1.0, 2.0, 3.0]}, "Source time interval must have shape (2,)"),
     ],

From 5376484e7295352474aa7cedc9014afd9cff40bd Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 8 Aug 2026 05:50:00 +0700
Subject: [PATCH 158/202] better checkers for source position and direction

---
 mcdc/object_/source.py   | 56 ++++++++++++++++++++++++++++-----------
 test/unit/test_source.py | 57 ++++++++++++++++++++++++++++++++++++++++
 2 files changed, 97 insertions(+), 16 deletions(-)

diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 7e0e31d93..2eb7efb10 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -37,30 +37,34 @@ class Source(MCDCObject):
         User label. If omitted, a default name is generated from the source ID.
     position : array_like of float, optional
         Point-source position ``[x, y, z]`` in cm. If provided, the source is
-        treated as a point source.
+        treated as a point source. Cannot be supplied with ``x``, ``y``, or
+        ``z``.
     x, y, z : array_like of float, optional
         Spatial bounds of a box source in cm, given as ``[min, max]`` for each
-        coordinate. These are used when ``position`` is not provided.
+        coordinate. Cannot be supplied with ``position``.
     direction : array_like of float, optional
         Source direction vector ``[ux, uy, uz]``. The vector is normalized
         internally. If provided without angular bounds, the source is
-        mono-directional.
+        mono-directional. Cannot be supplied with ``isotropic=True`` or
+        ``white_direction``.
 
         When ``polar_cosine`` and/or ``azimuthal`` are specified, this vector
         defines the reference (polar) axis about which directions are sampled.
     white_direction : array_like of float, optional
         Outward normal direction for a white boundary source. The vector is
-        normalized internally.
+        normalized internally. Cannot be supplied with ``isotropic=True`` or
+        ``direction``.
     isotropic : bool, optional
-        If True, emit particles isotropically.
+        If True, emit particles isotropically. Cannot be supplied with
+        ``direction`` or ``white_direction``.
     polar_cosine : array_like of float, optional
         Bounds for the sampled polar cosine,
         ``[mu_min, mu_max]``, measured with respect to ``direction``.
-        Defaults to ``[-1.0, 1.0]``.
+        Requires ``direction``. Defaults to ``[-1.0, 1.0]``.
     azimuthal : array_like of float, optional
         Bounds for the sampled azimuthal angle,
         ``[azi_min, azi_max]`` in radians, measured about ``direction``.
-        Defaults to ``[0.0, 2π]``.
+        Requires ``direction``. Defaults to ``[0.0, 2π]``.
     energy : real or array_like of float, optional
         Source energy in eV. A real scalar, including a NumPy scalar, defines a
         mono-energetic source. An array-like value with shape ``(2, N)`` defines
@@ -85,20 +89,19 @@ class Source(MCDCObject):
 
     Notes
     -----
-    If ``position`` is provided, ``x``, ``y``, and ``z`` are ignored.
+    ``position`` and the box bounds ``x``, ``y``, and ``z`` are alternative
+    spatial specifications and cannot be combined.
 
     When ``position`` is not provided, the source is treated as a box source.
     Any unspecified coordinate range defaults to ``[0.0, 0.0]`` cm. For
     example, if only ``z=[-1.0, 1.0]`` is specified, then the source occupies
     ``x=[0.0, 0.0]``, ``y=[0.0, 0.0]``, and ``z=[-1.0, 1.0]``.
 
-    Direction options are interpreted in the following order:
-
-    - if ``isotropic=True``, the source is isotropic;
-    - else if ``direction`` is provided, the source uses that direction;
-    - else if ``white_direction`` is provided, the source is a white boundary
-      source;
-    - otherwise, the default direction behavior is used.
+    ``isotropic=True``, ``direction``, and ``white_direction`` are alternative
+    angular specifications and cannot be combined. ``polar_cosine`` and
+    ``azimuthal`` describe an angular spread about ``direction`` and therefore
+    require it. If no angular specification is provided, the source is
+    isotropic.
 
     Examples
     --------
@@ -300,6 +303,10 @@ def __init__(
         # Assignment
         # ==============================================================================
 
+        # Require one unambiguous source-position representation
+        if position is not None and any(value is not None for value in (x, y, z)):
+            print_error("Cannot specify position together with x, y, or z.")
+
         # Position
         if position is not None:
             self.point = np.array(position)
@@ -312,8 +319,25 @@ def __init__(
             if z is not None:
                 self.z = np.array(z)
 
+        # Require one unambiguous source-direction representation
+        isotropic_enabled = isotropic is not None and bool(isotropic)
+        direction_modes = sum(
+            (
+                isotropic_enabled,
+                direction is not None,
+                white_direction is not None,
+            )
+        )
+        if direction_modes > 1:
+            print_error(
+                "Cannot specify more than one of isotropic=True, direction, and "
+                "white_direction."
+            )
+        if direction is None and (polar_cosine is not None or azimuthal is not None):
+            print_error("polar_cosine and azimuthal require direction.")
+
         # Direction
-        if isotropic is not None and isotropic:
+        if isotropic_enabled:
             pass
         elif direction is not None:
             self.isotropic_direction = False
diff --git a/test/unit/test_source.py b/test/unit/test_source.py
index 5eac04565..5df197239 100644
--- a/test/unit/test_source.py
+++ b/test/unit/test_source.py
@@ -6,6 +6,63 @@
 from mcdc.transport.source import source_particle
 
 
+@pytest.mark.parametrize("coordinate", ["x", "y", "z"])
+def test_position_and_box_bounds_are_mutually_exclusive(coordinate, capsys):
+    with pytest.raises(SystemExit):
+        mcdc.Source(position=[0.0, 0.0, 0.0], **{coordinate: [-1.0, 1.0]})
+
+    assert "Cannot specify position together with x, y, or z" in capsys.readouterr().out
+
+
+@pytest.mark.parametrize(
+    "kwargs",
+    [
+        {"isotropic": True, "direction": [0.0, 0.0, 1.0]},
+        {"isotropic": True, "white_direction": [0.0, 0.0, 1.0]},
+        {
+            "direction": [0.0, 0.0, 1.0],
+            "white_direction": [0.0, 0.0, 1.0],
+        },
+    ],
+)
+def test_direction_representations_are_mutually_exclusive(kwargs, capsys):
+    with pytest.raises(SystemExit):
+        mcdc.Source(**kwargs)
+
+    assert "Cannot specify more than one" in capsys.readouterr().out
+
+
+@pytest.mark.parametrize(
+    "kwargs",
+    [
+        {"polar_cosine": [0.8, 1.0]},
+        {"azimuthal": [0.0, np.pi]},
+        {
+            "white_direction": [0.0, 0.0, 1.0],
+            "polar_cosine": [0.8, 1.0],
+        },
+    ],
+)
+def test_angular_bounds_require_direction(kwargs, capsys):
+    with pytest.raises(SystemExit):
+        mcdc.Source(**kwargs)
+
+    assert "polar_cosine and azimuthal require direction" in capsys.readouterr().out
+
+
+def test_direction_accepts_angular_bounds():
+    source = mcdc.Source(
+        direction=[0.0, 0.0, 1.0],
+        polar_cosine=[0.8, 1.0],
+        azimuthal=[0.0, np.pi],
+    )
+
+    assert not source.isotropic_direction
+    assert not source.mono_direction
+    np.testing.assert_array_equal(source.polar_cosine, [0.8, 1.0])
+    np.testing.assert_array_equal(source.azimuthal, [0.0, np.pi])
+
+
 @pytest.mark.parametrize(
     "energy",
     [

From 0476cd0801bd0ab61f9c39ac8aefdeba49cc5bc6 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 8 Aug 2026 06:16:47 +0700
Subject: [PATCH 159/202] remove group from tally

---
 examples/c5g7/k-eigenvalue/input.py           |   2 +-
 mcdc/mcdc_get/tally.py                        |  29 ----
 mcdc/mcdc_set/tally.py                        |  29 ----
 mcdc/numba_types.py                           |   4 -
 mcdc/object_/simulation.py                    |   2 +-
 mcdc/object_/tally.py                         | 141 ++++++------------
 test/regression/inf_shem361/input.py          |   2 +-
 .../inf_shem361_k_eigenvalue/input.py         |   2 +-
 test/regression/inf_shem361_td/input.py       |   2 +-
 .../regression/inf_shem361_td_census/input.py |   2 +-
 test/unit/tally/conftest.py                   |   4 +-
 test/unit/tally/test_tally_factory.py         |  43 +++++-
 12 files changed, 92 insertions(+), 170 deletions(-)

diff --git a/examples/c5g7/k-eigenvalue/input.py b/examples/c5g7/k-eigenvalue/input.py
index edd163960..ebe85d659 100644
--- a/examples/c5g7/k-eigenvalue/input.py
+++ b/examples/c5g7/k-eigenvalue/input.py
@@ -295,7 +295,7 @@ def set_mat(mat):
 )
 g_grid = np.array([-0.5, 3.5, 6.5])  # Collapsing to fast (1-4) and slow (5-7)
 mesh = mcdc.MeshStructured(x=x_grid, y=y_grid, z=z_grid)
-tally = mcdc.Tally(mesh=mesh, scores=["flux"], group=g_grid)
+tally = mcdc.Tally(mesh=mesh, scores=["flux"], energy=g_grid)
 simulation.set_tallies([tally])
 
 # Settings
diff --git a/mcdc/mcdc_get/tally.py b/mcdc/mcdc_get/tally.py
index 3e1c7be67..5556883c1 100644
--- a/mcdc/mcdc_get/tally.py
+++ b/mcdc/mcdc_get/tally.py
@@ -91,35 +91,6 @@ def azi_chunk(start, length, tally, data):
     return data[start:end]
 
 
-@njit
-def group(index, tally, data):
-    offset = tally["group_offset"]
-    return data[offset + index]
-
-
-@njit
-def group_all(tally, data):
-    start = tally["group_offset"]
-    size = tally["group_length"]
-    end = start + size
-    return data[start:end]
-
-
-@njit
-def group_last(tally, data):
-    start = tally["group_offset"]
-    size = tally["group_length"]
-    end = start + size
-    return data[end - 1]
-
-
-@njit
-def group_chunk(start, length, tally, data):
-    start += tally["group_offset"]
-    end = start + length
-    return data[start:end]
-
-
 @njit
 def energy(index, tally, data):
     offset = tally["energy_offset"]
diff --git a/mcdc/mcdc_set/tally.py b/mcdc/mcdc_set/tally.py
index fb3cd93cd..d8daaf548 100644
--- a/mcdc/mcdc_set/tally.py
+++ b/mcdc/mcdc_set/tally.py
@@ -90,35 +90,6 @@ def azi_chunk(start, length, tally, data, value):
     data[start:end] = value
 
 
-@njit
-def group(index, tally, data, value):
-    offset = tally["group_offset"]
-    data[offset + index] = value
-
-
-@njit
-def group_all(tally, data, value):
-    start = tally["group_offset"]
-    size = tally["group_length"]
-    end = start + size
-    data[start:end] = value
-
-
-@njit
-def group_last(tally, data, value):
-    start = tally["group_offset"]
-    size = tally["group_length"]
-    end = start + size
-    data[end - 1] = value
-
-
-@njit
-def group_chunk(start, length, tally, data, value):
-    start += tally["group_offset"]
-    end = start + length
-    data[start:end] = value
-
-
 @njit
 def energy(index, tally, data, value):
     offset = tally["energy_offset"]
diff --git a/mcdc/numba_types.py b/mcdc/numba_types.py
index d1407b6b6..33d5a3b42 100644
--- a/mcdc/numba_types.py
+++ b/mcdc/numba_types.py
@@ -683,7 +683,6 @@
     ('scores_length', int64),
     ('particle_type', int64),
     ('filter_direction', bool),
-    ('filter_group', bool),
     ('filter_energy', bool),
     ('filter_time', bool),
     ('mu_offset', int64),
@@ -691,8 +690,6 @@
     ('azi_offset', int64),
     ('azi_length', int64),
     ('polar_reference', float64, (3,)),
-    ('group_offset', int64),
-    ('group_length', int64),
     ('energy_offset', int64),
     ('energy_length', int64),
     ('time_offset', int64),
@@ -707,7 +704,6 @@
     ('bin_shape_length', int64),
     ('stride_mu', int64),
     ('stride_azi', int64),
-    ('stride_group', int64),
     ('stride_energy', int64),
     ('stride_time', int64),
     ('ID', int64),
diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index b8158afc2..4d40f7b08 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -375,7 +375,7 @@ def _finalize_compilation(self) -> None:
 
         # Resolve tally filters and shapes that require the complete model
         for tally in self.tallies:
-            tally._resolve_group_filter(self)
+            tally._resolve_energy_filter(self)
 
         if settings.use_census_based_tally:
             for tally in self.tallies:
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 9a4fef065..9fe27bb87 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -78,13 +78,11 @@ class Tally(MCDCPolymorphic):
     particle_type : {"neutron", "electron", "proton"}, optional
         Particle type selected by the tally. If omitted, the tally accepts any
         transported particle type.
-    group : sequence of float or "all", optional
-        Bin boundaries for the auxiliary integer group state. The physics using
-        the group determines its meaning. For neutron multigroup transport,
-        these bins may collapse several energy groups into one tally bin, and
-        ``"all"`` creates one bin per neutron energy group during compilation.
-    energy : sequence of float, optional
-        Continuous-energy bin boundaries in eV.
+    energy : sequence of float or "all", optional
+        Physical energy-bin boundaries in eV. In standard neutron multigroup
+        transport, boundaries instead use the group-coordinate energy, and
+        ``"all"`` creates one tally bin per energy group during simulation
+        compilation.
     time : sequence of float, optional
         Time-bin boundaries in seconds.
 
@@ -163,18 +161,19 @@ class Tally(MCDCPolymorphic):
     ...     scores=["energy_deposition"],
     ... )
 
-    Use one bin per neutron energy group:
+    Use one energy bin per group in standard neutron multigroup transport:
 
-    >>> group_flux = mcdc.Tally(
+    >>> multigroup_flux = mcdc.Tally(
     ...     cell=cell,
     ...     scores=["flux"],
-    ...     group="all",
+    ...     energy="all",
     ... )
     """
 
     # MC/DC framework metadata
     label = "tally"
     sub_type = -1  # Polymorphic base
+    non_numba = ["_energy_all"]
 
     # Basic properties
     name: str
@@ -183,15 +182,14 @@ class Tally(MCDCPolymorphic):
     # Non-spatial filters
     particle_type: int
     filter_direction: bool
-    filter_group: bool
     filter_energy: bool
     filter_time: bool
     mu: NDArray[float64]
     azi: NDArray[float64]
     polar_reference: Annotated[NDArray[float64], (3,)]
-    group: NDArray[float64]
     energy: NDArray[float64]
     time: NDArray[float64]
+    _energy_all: bool  # Non-numba
 
     # Score bins
     bin: NDArray[float64]
@@ -202,7 +200,6 @@ class Tally(MCDCPolymorphic):
     # Filter strides
     stride_mu: int
     stride_azi: int
-    stride_group: int
     stride_energy: int
     stride_time: int
 
@@ -217,8 +214,7 @@ def __new__(
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
         particle_type: str | NoneType = None,
-        group: Sequence[float] | str | NoneType = None,
-        energy: Sequence[float] | NoneType = None,
+        energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NDArray[float64] | NoneType = None,
         spatial_shape: tuple[int, ...] | NoneType = None,
     ) -> TallySurfaceCrossing | TallyTracklength | TallyCollision:
@@ -278,8 +274,7 @@ def __init__(
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
         particle_type: str | NoneType = None,
-        group: Sequence[float] | str | NoneType = None,
-        energy: Sequence[float] | NoneType = None,
+        energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
         spatial_shape: tuple[int, ...] | NoneType = None,
     ):
@@ -328,14 +323,12 @@ def __init__(
         self.mu = np.array([-1.0, 1.0])
         self.azi = np.array([-PI, PI])
         self.polar_reference = np.array([0.0, 0.0, 1.0])
-        self.group = np.array([-INF, INF])
         self.energy = np.array([-1.0, INF])
         self.time = np.array([0.0, INF])
         self.filter_direction = False
-        self.filter_group = False
         self.filter_energy = False
         self.filter_time = False
-        self.all_groups = False
+        self._energy_all = False
         if mu is not None:
             self.mu = np.array(mu)
             self.filter_direction = True
@@ -347,17 +340,14 @@ def __init__(
             self.polar_reference = polar_reference_arr / np.linalg.norm(
                 polar_reference_arr
             )
-        if group is not None:
-            if isinstance(group, str):
-                if group != "all":
-                    print_error(f"Unsupported tally group filter: {group}")
-                self.all_groups = True
-                self.group = np.array([0])  # Compilation placeholder
-            else:
-                self.group = np.array(group)
-            self.filter_group = True
         if energy is not None:
-            self.energy = np.array(energy)
+            if isinstance(energy, str):
+                if energy != "all":
+                    print_error(f"Unsupported tally energy filter: {energy}")
+                self._energy_all = True
+                self.energy = np.array([0.0])  # Compilation placeholder
+            else:
+                self.energy = np.array(energy)
             self.filter_energy = True
         if time is not None:
             self.time = np.array(time)
@@ -366,17 +356,14 @@ def __init__(
         # Determine bin shape
         N_mu = len(self.mu) - 1
         N_azi = len(self.azi) - 1
-        N_group = len(self.group) - 1
         N_energy = len(self.energy) - 1
         N_time = len(self.time) - 1
         N_score = len(self.scores)
         #
         if spatial_shape is None:
-            shape = (N_mu, N_azi, N_group, N_energy, N_time, N_score)
+            shape = (N_mu, N_azi, N_energy, N_time, N_score)
         else:
-            shape = (
-                (N_mu, N_azi, N_group, N_energy, N_time) + spatial_shape + (N_score,)
-            )
+            shape = (N_mu, N_azi, N_energy, N_time) + spatial_shape + (N_score,)
 
         # Set bins and strides
         self._set_bin_shape_and_strides(shape)
@@ -386,9 +373,8 @@ def _set_bin_shape_and_strides(self, shape: tuple):
         self.bin_shape = list(shape)
 
         # Set strides
-        self.stride_time = reduce(operator.mul, shape[5:])
-        self.stride_energy = reduce(operator.mul, shape[4:])
-        self.stride_group = reduce(operator.mul, shape[3:])
+        self.stride_time = reduce(operator.mul, shape[4:])
+        self.stride_energy = reduce(operator.mul, shape[3:])
         self.stride_azi = reduce(operator.mul, shape[2:])
         self.stride_mu = reduce(operator.mul, shape[1:])
 
@@ -398,20 +384,17 @@ def _use_census_based_tally(self, frequency: int, simulation):
 
         N_mu = len(self.mu) - 1
         N_azi = len(self.azi) - 1
-        N_group = len(self.group) - 1
         N_energy = len(self.energy) - 1
         N_score = len(self.scores)
 
         spatial_shape = None
-        if len(self.bin_shape) > 6:
-            spatial_shape = tuple(self.bin_shape[5:-1])
+        if len(self.bin_shape) > 5:
+            spatial_shape = tuple(self.bin_shape[4:-1])
 
         if spatial_shape is None:
-            shape = (N_mu, N_azi, N_group, N_energy, frequency, N_score)
+            shape = (N_mu, N_azi, N_energy, frequency, N_score)
         else:
-            shape = (
-                (N_mu, N_azi, N_group, N_energy, frequency) + spatial_shape + (N_score,)
-            )
+            shape = (N_mu, N_azi, N_energy, frequency) + spatial_shape + (N_score,)
 
         self._set_bin_shape_and_strides(shape)
 
@@ -425,22 +408,15 @@ def _phasespace_filter_text(self):
             PARTICLE_PROTON: "Proton",
         }.get(self.particle_type, "Unspecified")
         text += f"  - Particle: {particle_name}\n"
-        if (
-            self.filter_time
-            or self.filter_energy
-            or self.filter_group
-            or self.filter_direction
-        ):
+        if self.filter_time or self.filter_energy or self.filter_direction:
             text += f"  - Phase-space filters\n"
         if self.filter_time:
             text += f"    - Time {print_1d_array(self.time)} s\n"
-        if self.filter_group:
-            if self.all_groups:
-                text += f"    - Group: All groups\n"
-            else:
-                text += f"    - Group {print_1d_array(self.group)}\n"
         if self.filter_energy:
-            text += f"    - Energy {print_1d_array(self.energy)} eV\n"
+            if self._energy_all:
+                text += f"    - Energy: All multigroup energy groups\n"
+            else:
+                text += f"    - Energy {print_1d_array(self.energy)} eV\n"
         if self.filter_direction:
             text += f"    - Direction\n"
             text += f"    -   Polar reference: {self.polar_reference}\n"
@@ -455,29 +431,16 @@ def _compile_into_simulation(self, simulation) -> bool:
 
         return True
 
-    def _resolve_group_filter(self, simulation) -> None:
-        """Resolve group filters that require the complete material model."""
-        if self.all_groups:
-            if self.particle_type not in (PARTICLE_ANY, PARTICLE_NEUTRON):
-                print_error('The group="all" filter currently supports only neutrons.')
-            if not simulation.materials or any(
-                not material.has_neutron_multigroup for material in simulation.materials
-            ):
+    def _resolve_energy_filter(self, simulation) -> None:
+        """Resolve energy filters that require the complete material model."""
+        if self._energy_all:
+            if simulation.technique.neutron_multigroup.hybrid:
                 print_error(
-                    'The neutron group="all" filter requires multigroup data for '
-                    "every material."
-                )
-            shared_grid = simulation.materials[0].neutron_multigroup.energy_grid
-            if any(
-                not np.array_equal(material.neutron_multigroup.energy_grid, shared_grid)
-                for material in simulation.materials[1:]
-            ):
-                print_error(
-                    'The neutron group="all" filter requires one shared multigroup '
-                    "energy grid."
+                    'The energy="all" filter requires standard neutron multigroup '
+                    "transport."
                 )
             G = simulation.materials[0].neutron_multigroup.G
-            self.group = np.linspace(0, G, G + 1) - 0.5
+            self.energy = np.linspace(0, G, G + 1) - 0.5
             shape = list(self.bin_shape)
             shape[2] = G
             self._set_bin_shape_and_strides(tuple(shape))
@@ -550,8 +513,7 @@ def __init__(
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
         particle_type: str | NoneType = None,
-        group: Sequence[float] | str | NoneType = None,
-        energy: Sequence[float] | NoneType = None,
+        energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
         super().__init__(
@@ -561,7 +523,6 @@ def __init__(
             azi=azi,
             polar_reference=polar_reference,
             particle_type=particle_type,
-            group=group,
             energy=energy,
             time=time,
         )
@@ -622,9 +583,7 @@ def __repr__(self):
         if isinstance(self.cell, Cell):
             text += f"  - Cell filter: {self.cell.name}\n"
         text += super()._phasespace_filter_text()
-        text += (
-            f"  - Bin shape [mu, azi, group, energy, time, score]: {self.bin_shape} \n"
-        )
+        text += f"  - Bin shape [mu, azi, energy, time, score]: {self.bin_shape} \n"
         return text
 
 
@@ -669,8 +628,7 @@ def __init__(
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
         particle_type: str | NoneType = None,
-        group: Sequence[float] | str | NoneType = None,
-        energy: Sequence[float] | NoneType = None,
+        energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
         spatial_shape = None
@@ -684,7 +642,6 @@ def __init__(
             azi=azi,
             polar_reference=polar_reference,
             particle_type=particle_type,
-            group=group,
             energy=energy,
             time=time,
             spatial_shape=spatial_shape,
@@ -756,9 +713,7 @@ def __repr__(self):
         if self.mesh:
             text += f"  - Mesh: {self.mesh.name}\n"
         text += super()._phasespace_filter_text()
-        text += (
-            f"  - Bin shape [mu, azi, group, energy, time, score]: {self.bin_shape} \n"
-        )
+        text += f"  - Bin shape [mu, azi, energy, time, score]: {self.bin_shape} \n"
         return text
 
 
@@ -803,8 +758,7 @@ def __init__(
         azi: Sequence[float] | NoneType = None,
         polar_reference: Sequence[float] | NoneType = None,
         particle_type: str | NoneType = None,
-        group: Sequence[float] | str | NoneType = None,
-        energy: Sequence[float] | NoneType = None,
+        energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
     ):
         spatial_shape = None
@@ -818,7 +772,6 @@ def __init__(
             azi=azi,
             polar_reference=polar_reference,
             particle_type=particle_type,
-            group=group,
             energy=energy,
             time=time,
             spatial_shape=spatial_shape,
@@ -891,7 +844,5 @@ def __repr__(self):
         if self.mesh:
             text += f"  - Mesh: {self.mesh.name}\n"
         text += super()._phasespace_filter_text()
-        text += (
-            f"  - Bin shape [mu, azi, group, energy, time, score]: {self.bin_shape} \n"
-        )
+        text += f"  - Bin shape [mu, azi, energy, time, score]: {self.bin_shape} \n"
         return text
diff --git a/test/regression/inf_shem361/input.py b/test/regression/inf_shem361/input.py
index ab17cc273..b49ecedfd 100644
--- a/test/regression/inf_shem361/input.py
+++ b/test/regression/inf_shem361/input.py
@@ -55,7 +55,7 @@
 # ======================================================================================
 
 # Tallies
-tally = mcdc.Tally(scores=["flux"], group="all")
+tally = mcdc.Tally(scores=["flux"], energy="all")
 simulation.set_tallies([tally])
 
 # Settings
diff --git a/test/regression/inf_shem361_k_eigenvalue/input.py b/test/regression/inf_shem361_k_eigenvalue/input.py
index 98025240e..263cdfc17 100644
--- a/test/regression/inf_shem361_k_eigenvalue/input.py
+++ b/test/regression/inf_shem361_k_eigenvalue/input.py
@@ -54,7 +54,7 @@
 # =============================================================================
 
 # Tallies
-tally = mcdc.Tally(scores=["flux"], group="all")
+tally = mcdc.Tally(scores=["flux"], energy="all")
 simulation.set_tallies([tally])
 
 # Settings
diff --git a/test/regression/inf_shem361_td/input.py b/test/regression/inf_shem361_td/input.py
index dedb1b214..84f76e09a 100644
--- a/test/regression/inf_shem361_td/input.py
+++ b/test/regression/inf_shem361_td/input.py
@@ -60,7 +60,7 @@
 tally = mcdc.Tally(
     scores=["flux"],
     time=np.insert(np.logspace(-8, 1, 100), 0, 0.0),
-    group="all",
+    energy="all",
 )
 simulation.set_tallies([tally])
 
diff --git a/test/regression/inf_shem361_td_census/input.py b/test/regression/inf_shem361_td_census/input.py
index 5a1d49b32..da58989c3 100644
--- a/test/regression/inf_shem361_td_census/input.py
+++ b/test/regression/inf_shem361_td_census/input.py
@@ -60,7 +60,7 @@
 tally = mcdc.Tally(
     scores=["flux"],
     time=np.insert(np.logspace(-8, 1, 100), 0, 0.0),
-    group="all",
+    energy="all",
 )
 simulation.set_tallies([tally])
 
diff --git a/test/unit/tally/conftest.py b/test/unit/tally/conftest.py
index 8bc2cf117..e330a3b92 100644
--- a/test/unit/tally/conftest.py
+++ b/test/unit/tally/conftest.py
@@ -22,7 +22,7 @@ def _particle(surface_ID, x, ux, cell_ID=-1, w=2.0):
         particle["surface_ID"] = surface_ID
         particle["cell_ID"] = cell_ID
         particle["material_ID"] = 0
-        particle["group"] = 0
+        particle["E"] = 0.0
         particle["x"] = x
         particle["y"] = 0.0
         particle["z"] = 0.0
@@ -80,7 +80,7 @@ def surface_crossing_tally_context(slab_plane_x, prepare_simulation):
     particle = particle_container[0]
     particle["particle_type"] = PARTICLE_NEUTRON
     particle["material_ID"] = 0
-    particle["group"] = 0
+    particle["E"] = 0.0
     particle["x"] = 0.0
     particle["y"] = 0.0
     particle["z"] = 0.0
diff --git a/test/unit/tally/test_tally_factory.py b/test/unit/tally/test_tally_factory.py
index eb77f31ac..93e325762 100644
--- a/test/unit/tally/test_tally_factory.py
+++ b/test/unit/tally/test_tally_factory.py
@@ -97,19 +97,21 @@ def test_tally_factory_allows_combined_supported_filters(slab_plane_x):
     assert cell_mesh_tally.mesh_filter_ID == mesh.ID
 
 
-def test_all_group_filter_resizes_compiled_tally_bins(prepare_simulation):
+def test_all_energy_filter_resizes_standard_multigroup_tally_bins(
+    prepare_simulation,
+):
     material = mcdc.Material.multigroup(capture=np.ones(3))
     cell = mcdc.Cell(fill=material)
-    tally = mcdc.Tally(scores=["flux"], group="all")
+    tally = mcdc.Tally(scores=["flux"], energy="all")
 
     simulation_container, data = prepare_simulation(cells=[cell], tallies=[tally])
     simulation = simulation_container[0]
     tally_record = simulation["tallies"][tally.ID]
 
     assert tally.particle_type == PARTICLE_ANY
-    np.testing.assert_array_equal(tally.group, [-0.5, 0.5, 1.5, 2.5])
-    assert tally.bin_shape == [1, 1, 3, 1, 1, 1]
-    assert tally.stride_group == 1
+    assert "_energy_all" not in tally_record.dtype.names
+    np.testing.assert_array_equal(tally.energy, [-0.5, 0.5, 1.5, 2.5])
+    assert tally.bin_shape == [1, 1, 3, 1, 1]
     assert tally.stride_energy == 1
     assert tally.stride_azi == 3
     assert tally.stride_mu == 3
@@ -120,6 +122,37 @@ def test_all_group_filter_resizes_compiled_tally_bins(prepare_simulation):
     assert len(data[bin_start:bin_stop]) == 3
 
 
+def test_all_energy_filter_rejects_hybrid_multigroup_transport(
+    prepare_simulation,
+    capsys,
+):
+    material_a = mcdc.Material.multigroup(
+        capture=np.ones(2),
+        energy_grid=[0.0, 1.0, 2.0],
+    )
+    material_b = mcdc.Material.multigroup(
+        capture=np.ones(2),
+        energy_grid=[0.0, 2.0, 3.0],
+    )
+    cells = [mcdc.Cell(fill=material_a), mcdc.Cell(fill=material_b)]
+    tally = mcdc.Tally(scores=["flux"], energy="all")
+
+    with pytest.raises(SystemExit):
+        prepare_simulation(cells=cells, tallies=[tally])
+
+    assert (
+        'The energy="all" filter requires standard neutron multigroup transport'
+        in capsys.readouterr().out
+    )
+
+
+def test_tally_factory_rejects_unsupported_energy_filter(capsys):
+    with pytest.raises(SystemExit):
+        mcdc.Tally(scores=["flux"], energy="groups")
+
+    assert "Unsupported tally energy filter: groups" in capsys.readouterr().out
+
+
 def test_tally_factory_rejects_mixed_estimator_scores(capsys):
     with pytest.raises(SystemExit):
         mcdc.Tally(scores=["flux", "energy_deposition"])

From 939f2ad2efdadcb26491541d7b1221b2ab7d901e Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 8 Aug 2026 06:41:09 +0700
Subject: [PATCH 160/202] update examples and tests

---
 examples/c5g7/k-eigenvalue/input.py               | 2 +-
 examples/c5g7/transient/input.py                  | 2 +-
 examples/fuel_array_packaged/input.py             | 2 +-
 examples/iterative_source_reweighting/input.py    | 4 ++--
 examples/kobayashi-TD/input.py                    | 2 +-
 examples/kobayashi/input.py                       | 2 +-
 examples/moving_pellet/input.py                   | 2 +-
 examples/moving_source/input.py                   | 2 +-
 examples/slab_shielding/input.py                  | 2 +-
 examples/sphere_in_cube/input.py                  | 2 +-
 mcdc/object_/source.py                            | 8 +++++---
 test/regression/azurv1/input.py                   | 2 +-
 test/regression/azurv1_census/input.py            | 2 +-
 test/regression/azurv1_census_tally/input.py      | 2 +-
 test/regression/c5g7_2d_k_eigenvalue/input.py     | 2 +-
 test/regression/cooper2/input.py                  | 2 +-
 test/regression/fuel_array_packaged/input.py      | 2 +-
 test/regression/inf_shem361/input.py              | 2 +-
 test/regression/inf_shem361_k_eigenvalue/input.py | 2 +-
 test/regression/inf_shem361_td/input.py           | 2 +-
 test/regression/inf_shem361_td_census/input.py    | 2 +-
 test/regression/kobayashi3-TD/input.py            | 2 +-
 test/regression/kornreich/input.py                | 2 +-
 test/regression/moving_pellet/input.py            | 2 +-
 test/regression/moving_source/input.py            | 2 +-
 test/regression/slab_absorbium/input.py           | 2 +-
 test/regression/slab_isobeam_td/input.py          | 2 +-
 test/regression/slab_isobeam_td_census/input.py   | 2 +-
 test/regression/slab_reed/input.py                | 4 ++--
 test/regression/sphere_in_cube/input.py           | 2 +-
 test/unit/test_source.py                          | 1 +
 31 files changed, 37 insertions(+), 34 deletions(-)

diff --git a/examples/c5g7/k-eigenvalue/input.py b/examples/c5g7/k-eigenvalue/input.py
index ebe85d659..990afc624 100644
--- a/examples/c5g7/k-eigenvalue/input.py
+++ b/examples/c5g7/k-eigenvalue/input.py
@@ -279,7 +279,7 @@ def set_mat(mat):
     y=[-pitch * 17 * 2, 0.0],
     z=[-core_height / 2, core_height / 2],
     isotropic=True,
-    group=0,  # Highest energy
+    energy=0,  # Highest energy
 )
 simulation.set_sources([source])
 
diff --git a/examples/c5g7/transient/input.py b/examples/c5g7/transient/input.py
index f7d5da4c0..2ccd8661f 100644
--- a/examples/c5g7/transient/input.py
+++ b/examples/c5g7/transient/input.py
@@ -340,7 +340,7 @@ def set_mat(mat):
     y=np.array([-pitch * 17 * 3 / 2] * 2) + np.array([-pitch / 2, +pitch / 2]),
     z=[-core_height / 2, core_height / 2],
     isotropic=True,
-    group=0,  # Highest energy
+    energy=0,  # Highest energy
     time=[0.0, 15.0],
 )
 simulation.set_sources([source])
diff --git a/examples/fuel_array_packaged/input.py b/examples/fuel_array_packaged/input.py
index 294d0d991..6810fba3e 100644
--- a/examples/fuel_array_packaged/input.py
+++ b/examples/fuel_array_packaged/input.py
@@ -77,7 +77,7 @@
 # Set source
 # ======================================================================================
 
-source = mcdc.Source(x=[-0.1, 0.1], isotropic=True, group=0)
+source = mcdc.Source(x=[-0.1, 0.1], isotropic=True, energy=0)
 simulation.set_sources([source])
 
 # ======================================================================================
diff --git a/examples/iterative_source_reweighting/input.py b/examples/iterative_source_reweighting/input.py
index 15c57b69a..a458640a0 100644
--- a/examples/iterative_source_reweighting/input.py
+++ b/examples/iterative_source_reweighting/input.py
@@ -22,13 +22,13 @@
     name="Left source",
     z=[1.0, 2.0],
     isotropic=True,
-    group=0,
+    energy=0,
 )
 source_right = mcdc.Source(
     name="Right source",
     z=[8.0, 9.0],
     isotropic=True,
-    group=0,
+    energy=0,
 )
 simulation.set_sources([source_left, source_right])
 
diff --git a/examples/kobayashi-TD/input.py b/examples/kobayashi-TD/input.py
index 6fb8c5e30..26b6bdb68 100644
--- a/examples/kobayashi-TD/input.py
+++ b/examples/kobayashi-TD/input.py
@@ -55,7 +55,7 @@
     y=[0.0, 10.0],
     z=[0.0, 10.0],
     isotropic=True,
-    group=0,
+    energy=0,
     time=[0.0, 50.0],
 )
 simulation.set_sources([source])
diff --git a/examples/kobayashi/input.py b/examples/kobayashi/input.py
index 524aef46e..cfec37d95 100644
--- a/examples/kobayashi/input.py
+++ b/examples/kobayashi/input.py
@@ -53,7 +53,7 @@
     y=[0.0, 10.0],
     z=[0.0, 10.0],
     isotropic=True,
-    group=0,
+    energy=0,
 )
 simulation.set_sources([source])
 
diff --git a/examples/moving_pellet/input.py b/examples/moving_pellet/input.py
index aa1fce45b..ddd5c165e 100644
--- a/examples/moving_pellet/input.py
+++ b/examples/moving_pellet/input.py
@@ -57,7 +57,7 @@
     y=[-0.5, 0.5],
     z=[-0.5, 0.5],
     isotropic=True,
-    group=0,
+    energy=0,
     time=[0.0, 9.0],
 )
 simulation.set_sources([source])
diff --git a/examples/moving_source/input.py b/examples/moving_source/input.py
index 196395068..60cc23d06 100644
--- a/examples/moving_source/input.py
+++ b/examples/moving_source/input.py
@@ -37,7 +37,7 @@
     z=[-0.5, 0.5],
     direction=[1.0, 1.0, 0.0],
     polar_cosine=[-1.0, -0.9],
-    group=0,
+    energy=0,
     time=[0.0, 10.0],
 )
 src.move(
diff --git a/examples/slab_shielding/input.py b/examples/slab_shielding/input.py
index af98b89fa..503fd40d5 100644
--- a/examples/slab_shielding/input.py
+++ b/examples/slab_shielding/input.py
@@ -33,7 +33,7 @@
 source = mcdc.Source(
     z=[0.0, 2.0],
     isotropic=True,
-    group=0,
+    energy=0,
 )
 simulation.set_sources([source])
 
diff --git a/examples/sphere_in_cube/input.py b/examples/sphere_in_cube/input.py
index 9729aea9d..ca51baade 100644
--- a/examples/sphere_in_cube/input.py
+++ b/examples/sphere_in_cube/input.py
@@ -37,7 +37,7 @@
     y=[0.0, 4.0],
     z=[0.0, 4.0],
     isotropic=True,
-    group=0,
+    energy=0,
     time=[0.0, 50.0],
 )
 simulation.set_sources([source])
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 2eb7efb10..04529ce2c 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -65,12 +65,14 @@ class Source(MCDCObject):
         Bounds for the sampled azimuthal angle,
         ``[azi_min, azi_max]`` in radians, measured about ``direction``.
         Requires ``direction``. Defaults to ``[0.0, 2π]``.
-    energy : real or array_like of float, optional
+    energy : float, array_like of float, or int, optional
         Source energy in eV. A real scalar, including a NumPy scalar, defines a
         mono-energetic source. An array-like value with shape ``(2, N)`` defines
         a tabulated distribution: the first row contains energy values and the
         second row contains their probability density in ``eV^-1``. Defaults
-        to a mono-energetic source at **1 MeV**.
+        to a mono-energetic source at **1 MeV**. In standard neutron multigroup
+        transport, an integer conventionally specifies a group-coordinate energy and is
+        stored internally as a float.
     discrete_energy : array_like of float, optional
         Discrete source-energy distribution with shape ``(2, N)``. The first
         row contains sampled energy values and the second row contains their
@@ -241,7 +243,7 @@ def __init__(
         polar_cosine: Sequence[float] | NoneType = None,
         azimuthal: Sequence[float] | NoneType = None,
         #
-        energy: ArrayLike | NoneType = None,
+        energy: float | ArrayLike | int | NoneType = None,
         discrete_energy: ArrayLike | NoneType = None,
         #
         time: ArrayLike = 0.0,
diff --git a/test/regression/azurv1/input.py b/test/regression/azurv1/input.py
index 09efc5ea1..4ff4453a6 100644
--- a/test/regression/azurv1/input.py
+++ b/test/regression/azurv1/input.py
@@ -37,7 +37,7 @@
 source = mcdc.Source(
     position=[0.0, 0.0, 0.0],
     isotropic=True,
-    group=0,
+    energy=0,
     time=0.0,
 )
 simulation.set_sources([source])
diff --git a/test/regression/azurv1_census/input.py b/test/regression/azurv1_census/input.py
index f55ad04aa..84ffbb07c 100644
--- a/test/regression/azurv1_census/input.py
+++ b/test/regression/azurv1_census/input.py
@@ -35,7 +35,7 @@
 source = mcdc.Source(
     position=[0.0, 0.0, 0.0],
     isotropic=True,
-    group=0,
+    energy=0,
     time=0.0,
 )
 simulation.set_sources([source])
diff --git a/test/regression/azurv1_census_tally/input.py b/test/regression/azurv1_census_tally/input.py
index e3c19587b..71957d0a1 100644
--- a/test/regression/azurv1_census_tally/input.py
+++ b/test/regression/azurv1_census_tally/input.py
@@ -35,7 +35,7 @@
 source = mcdc.Source(
     position=[0.0, 0.0, 0.0],
     isotropic=True,
-    group=0,
+    energy=0,
     time=0.0,
 )
 simulation.set_sources([source])
diff --git a/test/regression/c5g7_2d_k_eigenvalue/input.py b/test/regression/c5g7_2d_k_eigenvalue/input.py
index 885b649c5..ec4ffe8a5 100644
--- a/test/regression/c5g7_2d_k_eigenvalue/input.py
+++ b/test/regression/c5g7_2d_k_eigenvalue/input.py
@@ -180,7 +180,7 @@ def set_mat(mat):
     x=[0.0, pitch * 17 * 2],
     y=[-pitch * 17 * 2, 0.0],
     isotropic=True,
-    group=6,
+    energy=6,
 )
 simulation.set_sources([source])
 
diff --git a/test/regression/cooper2/input.py b/test/regression/cooper2/input.py
index 6d8c0afed..066c2f4e6 100644
--- a/test/regression/cooper2/input.py
+++ b/test/regression/cooper2/input.py
@@ -45,7 +45,7 @@
     x=[0.0, 1.0],
     y=[0.0, 1.0],
     isotropic=True,
-    group=0,
+    energy=0,
     time=0.0,
 )
 simulation.set_sources([source])
diff --git a/test/regression/fuel_array_packaged/input.py b/test/regression/fuel_array_packaged/input.py
index c1065abf1..d8d59d76a 100644
--- a/test/regression/fuel_array_packaged/input.py
+++ b/test/regression/fuel_array_packaged/input.py
@@ -78,7 +78,7 @@
 # Set source
 # ======================================================================================
 
-source = mcdc.Source(x=[-0.1, 0.1], isotropic=True, group=0)
+source = mcdc.Source(x=[-0.1, 0.1], isotropic=True, energy=0)
 simulation.set_sources([source])
 
 # ======================================================================================
diff --git a/test/regression/inf_shem361/input.py b/test/regression/inf_shem361/input.py
index b49ecedfd..b762b197c 100644
--- a/test/regression/inf_shem361/input.py
+++ b/test/regression/inf_shem361/input.py
@@ -46,7 +46,7 @@
 # ======================================================================================
 
 source = mcdc.Source(
-    position=(0.0, 0.0, 0.0), isotropic=True, group=np.array([[360], [1.0]])
+    position=(0.0, 0.0, 0.0), isotropic=True, discrete_energy=np.array([[360], [1.0]])
 )
 simulation.set_sources([source])
 
diff --git a/test/regression/inf_shem361_k_eigenvalue/input.py b/test/regression/inf_shem361_k_eigenvalue/input.py
index 263cdfc17..28380ed5f 100644
--- a/test/regression/inf_shem361_k_eigenvalue/input.py
+++ b/test/regression/inf_shem361_k_eigenvalue/input.py
@@ -45,7 +45,7 @@
 # =============================================================================
 
 source = mcdc.Source(
-    position=(0.0, 0.0, 0.0), isotropic=True, group=np.array([[360], [1.0]])
+    position=(0.0, 0.0, 0.0), isotropic=True, discrete_energy=np.array([[360], [1.0]])
 )
 simulation.set_sources([source])
 
diff --git a/test/regression/inf_shem361_td/input.py b/test/regression/inf_shem361_td/input.py
index 84f76e09a..975fd993d 100644
--- a/test/regression/inf_shem361_td/input.py
+++ b/test/regression/inf_shem361_td/input.py
@@ -48,7 +48,7 @@
 # ======================================================================================
 
 source = mcdc.Source(
-    position=(0.0, 0.0, 0.0), isotropic=True, group=np.array([[360], [1.0]])
+    position=(0.0, 0.0, 0.0), isotropic=True, discrete_energy=np.array([[360], [1.0]])
 )
 simulation.set_sources([source])
 
diff --git a/test/regression/inf_shem361_td_census/input.py b/test/regression/inf_shem361_td_census/input.py
index da58989c3..c571df021 100644
--- a/test/regression/inf_shem361_td_census/input.py
+++ b/test/regression/inf_shem361_td_census/input.py
@@ -48,7 +48,7 @@
 # ======================================================================================
 
 source = mcdc.Source(
-    position=(0.0, 0.0, 0.0), isotropic=True, group=np.array([[360], [1.0]])
+    position=(0.0, 0.0, 0.0), isotropic=True, discrete_energy=np.array([[360], [1.0]])
 )
 simulation.set_sources([source])
 
diff --git a/test/regression/kobayashi3-TD/input.py b/test/regression/kobayashi3-TD/input.py
index 607d66a43..717affda9 100644
--- a/test/regression/kobayashi3-TD/input.py
+++ b/test/regression/kobayashi3-TD/input.py
@@ -56,7 +56,7 @@
     y=[0.0, 10.0],
     z=[0.0, 10.0],
     isotropic=True,
-    group=0,
+    energy=0,
     time=[0.0, 50.0],
 )
 simulation.set_sources([source])
diff --git a/test/regression/kornreich/input.py b/test/regression/kornreich/input.py
index 2d0841fc0..4ae57c201 100644
--- a/test/regression/kornreich/input.py
+++ b/test/regression/kornreich/input.py
@@ -38,7 +38,7 @@
 # Set source
 # ======================================================================================
 
-source = mcdc.Source(x=[0.0, 2.5], isotropic=True, group=0)
+source = mcdc.Source(x=[0.0, 2.5], isotropic=True, energy=0)
 simulation.set_sources([source])
 
 # ======================================================================================
diff --git a/test/regression/moving_pellet/input.py b/test/regression/moving_pellet/input.py
index 7628e4253..10f8774d4 100644
--- a/test/regression/moving_pellet/input.py
+++ b/test/regression/moving_pellet/input.py
@@ -58,7 +58,7 @@
     y=[-0.5, 0.5],
     z=[-0.5, 0.5],
     isotropic=True,
-    group=0,
+    energy=0,
     time=[0.0, 9.0],
 )
 simulation.set_sources([source])
diff --git a/test/regression/moving_source/input.py b/test/regression/moving_source/input.py
index 20099cd48..2291e4863 100644
--- a/test/regression/moving_source/input.py
+++ b/test/regression/moving_source/input.py
@@ -38,7 +38,7 @@
     z=[-0.5, 0.5],
     direction=[1.0, 1.0, 0.0],
     polar_cosine=[-1.0, -0.9],
-    group=0,
+    energy=0,
     time=[0.0, 10.0],
 )
 src.move([[1.0, 0.0, 0.0], [-0.5, 2.0, 0.0], [0.0, -3.0, 0.0]], [7.0, 2.0, 1.0])
diff --git a/test/regression/slab_absorbium/input.py b/test/regression/slab_absorbium/input.py
index 39e12a0de..b715ff539 100644
--- a/test/regression/slab_absorbium/input.py
+++ b/test/regression/slab_absorbium/input.py
@@ -31,7 +31,7 @@
 # ======================================================================================
 # Uniform isotropic source throughout the domain
 
-source = mcdc.Source(z=[0.0, 6.0], isotropic=True, group=0)
+source = mcdc.Source(z=[0.0, 6.0], isotropic=True, energy=0)
 simulation.set_sources([source])
 
 # ======================================================================================
diff --git a/test/regression/slab_isobeam_td/input.py b/test/regression/slab_isobeam_td/input.py
index 7eec22bd8..a66da41f9 100644
--- a/test/regression/slab_isobeam_td/input.py
+++ b/test/regression/slab_isobeam_td/input.py
@@ -29,7 +29,7 @@
 source = mcdc.Source(
     position=(0.0, 0.0, 0.0),
     white_direction=(1.0, 0.0, 0.0),
-    group=0,
+    energy=0,
     time=[0.0, 5.0],
 )
 simulation.set_sources([source])
diff --git a/test/regression/slab_isobeam_td_census/input.py b/test/regression/slab_isobeam_td_census/input.py
index 27915511a..b2a4ccfb1 100644
--- a/test/regression/slab_isobeam_td_census/input.py
+++ b/test/regression/slab_isobeam_td_census/input.py
@@ -29,7 +29,7 @@
 source = mcdc.Source(
     position=(1e-10, 0.0, 0.0),
     white_direction=(1.0, 0.0, 0.0),
-    group=0,
+    energy=0,
     time=[0.0, 5.0],
 )
 simulation.set_sources([source])
diff --git a/test/regression/slab_reed/input.py b/test/regression/slab_reed/input.py
index 9d8362d49..69cf5cb82 100644
--- a/test/regression/slab_reed/input.py
+++ b/test/regression/slab_reed/input.py
@@ -35,11 +35,11 @@
 # ======================================================================================
 
 # Isotropic source in the absorbing medium
-source_1 = mcdc.Source(z=[0.0, 2.0], isotropic=True, group=0, probability=50.0)
+source_1 = mcdc.Source(z=[0.0, 2.0], isotropic=True, energy=0, probability=50.0)
 
 # Isotropic source in the first half of the outermost medium,
 # with 1/100 strength
-source_2 = mcdc.Source(z=[5.0, 6.0], isotropic=True, group=0, probability=0.5)
+source_2 = mcdc.Source(z=[5.0, 6.0], isotropic=True, energy=0, probability=0.5)
 simulation.set_sources([source_1, source_2])
 
 # ======================================================================================
diff --git a/test/regression/sphere_in_cube/input.py b/test/regression/sphere_in_cube/input.py
index 1bf38e1bb..e16b46b41 100644
--- a/test/regression/sphere_in_cube/input.py
+++ b/test/regression/sphere_in_cube/input.py
@@ -41,7 +41,7 @@
     y=[0.0, 4.0],
     z=[0.0, 4.0],
     isotropic=True,
-    group=0,
+    energy=0,
     time=[0.0, 50.0],
 )
 simulation.set_sources([source])
diff --git a/test/unit/test_source.py b/test/unit/test_source.py
index 5df197239..c8f174ef4 100644
--- a/test/unit/test_source.py
+++ b/test/unit/test_source.py
@@ -76,6 +76,7 @@ def test_scalar_energy(energy):
     source = mcdc.Source(energy=energy)
 
     assert source.mono_energetic
+    assert isinstance(source.energy, float)
     assert source.energy == 10_000.0
 
 

From b6ac38c3d7308c8740305dd2b7db7cd0b9c19492 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 8 Aug 2026 07:13:39 +0700
Subject: [PATCH 161/202] working implementation

---
 mcdc/transport/physics/neutron/multigroup.py | 36 +++++++-------------
 mcdc/transport/tally/filter.py               | 11 +++---
 mcdc/transport/tally/score.py                | 15 ++------
 3 files changed, 20 insertions(+), 42 deletions(-)

diff --git a/mcdc/transport/physics/neutron/multigroup.py b/mcdc/transport/physics/neutron/multigroup.py
index 47790561c..e1d48d495 100644
--- a/mcdc/transport/physics/neutron/multigroup.py
+++ b/mcdc/transport/physics/neutron/multigroup.py
@@ -67,7 +67,7 @@ def particle_speed(particle_container, simulation, data):
     mgxs_ID = material["neutron_multigroup_ID"]
     mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
 
-    group = _get_energy_group(particle_container, mgxs, simulation, data)
+    group = _get_energy_group(particle["E"], mgxs, simulation, data)
 
     return mcdc_get.neutron_multigroup_data.speed(group, mgxs, data)
 
@@ -85,7 +85,7 @@ def macro_xs(reaction_type, particle_container, simulation, data):
     mgxs_ID = material["neutron_multigroup_ID"]
     mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
 
-    group = _get_energy_group(particle_container, mgxs, simulation, data)
+    group = _get_energy_group(particle["E"], mgxs, simulation, data)
 
     if reaction_type == NEUTRON_REACTION_TOTAL:
         return mcdc_get.neutron_multigroup_data.total(group, mgxs, data)
@@ -106,7 +106,7 @@ def neutron_production_xs(reaction_type, particle_container, simulation, data):
     mgxs_ID = material["neutron_multigroup_ID"]
     mgxs = simulation["neutron_multigroup_data"][mgxs_ID]
 
-    group = _get_energy_group(particle_container, mgxs, simulation, data)
+    group = _get_energy_group(particle["E"], mgxs, simulation, data)
 
     # Total production
     if reaction_type == NEUTRON_REACTION_TOTAL:
@@ -211,7 +211,7 @@ def scattering(particle_container, program, data):
     ux = particle["ux"]
     uy = particle["uy"]
     uz = particle["uz"]
-    group = _get_energy_group(particle_container, mgxs, simulation, data)
+    group = _get_energy_group(particle["E"], mgxs, simulation, data)
 
     # Kill the current particle
     particle["alive"] = False
@@ -264,9 +264,8 @@ def scattering(particle_container, program, data):
             total += chi_s[group_out]
             if total > xi:
                 break
-        particle_new["group"] = group_out
         particle_new["E"] = _get_group_energy(
-            particle_container_new, mgxs, simulation, data
+            group_out, particle_container_new, mgxs, simulation, data
         )
 
         # Bank, but keep it if it is the last particle
@@ -275,7 +274,6 @@ def scattering(particle_container, program, data):
             particle["ux"] = particle_new["ux"]
             particle["uy"] = particle_new["uy"]
             particle["uz"] = particle_new["uz"]
-            particle["group"] = particle_new["group"]
             particle["E"] = particle_new["E"]
             particle["w"] = particle_new["w"]
         else:
@@ -296,7 +294,7 @@ def fission(particle_container, program, data):
     J = mgxs["J"]
 
     # Particle attributes
-    group = _get_energy_group(particle_container, mgxs, simulation, data)
+    group = _get_energy_group(particle["E"], mgxs, simulation, data)
 
     # Kill the current particle
     particle["alive"] = False
@@ -376,9 +374,8 @@ def fission(particle_container, program, data):
             tot += spectrum[group_out]
             if tot > xi:
                 break
-        particle_new["group"] = group_out
         particle_new["E"] = _get_group_energy(
-            particle_container_new, mgxs, simulation, data
+            group_out, particle_container_new, mgxs, simulation, data
         )
 
         # Sample emission time
@@ -419,7 +416,6 @@ def fission(particle_container, program, data):
                 particle["uy"] = particle_new["uy"]
                 particle["uz"] = particle_new["uz"]
                 particle["t"] = particle_new["t"]
-                particle["group"] = particle_new["group"]
                 particle["E"] = particle_new["E"]
                 particle["w"] = particle_new["w"]
             else:
@@ -444,28 +440,22 @@ def fission(particle_container, program, data):
 
 
 @njit
-def _get_energy_group(particle_container, mgxs, simulation, data):
-    particle = particle_container[0]
-
+def _get_energy_group(E, mgxs, simulation, data):
     if simulation["technique"]["neutron_multigroup"]["hybrid"]:
-        E = particle["E"]
         offset = mgxs["energy_grid_offset"]
         length = mgxs["energy_grid_length"]
         E_grid = data[offset : offset + length]
         group = util.find_bin_with_rules(E, E_grid, 0.0, False)
 
     else:
-        group = particle["group"]
+        group = int(E)
 
     return group
 
 
 @njit
-def _get_group_energy(particle_container, mgxs, simulation, data):
-    particle = particle_container[0]
-
+def _get_group_energy(group, rng_state, mgxs, simulation, data):
     if simulation["technique"]["neutron_multigroup"]["hybrid"]:
-        group = particle["group"]
         E_low = mcdc_get.neutron_multigroup_data.energy_grid(group, mgxs, data)
         E_high = mcdc_get.neutron_multigroup_data.energy_grid(group + 1, mgxs, data)
         representation = mgxs["energy_representation"]
@@ -475,10 +465,10 @@ def _get_group_energy(particle_container, mgxs, simulation, data):
         elif representation == NEUTRON_MULTIGROUP_ENERGY_MIDPOINT_LOG:
             energy = math.sqrt(E_low * E_high)
         elif representation == NEUTRON_MULTIGROUP_ENERGY_UNIFORM:
-            xi = rng.lcg(particle_container)
+            xi = rng.lcg(rng_state)
             energy = E_low + xi * (E_high - E_low)
         elif representation == NEUTRON_MULTIGROUP_ENERGY_UNIFORM_LOG:
-            xi = rng.lcg(particle_container)
+            xi = rng.lcg(rng_state)
             log_E_low = math.log(E_low)
             energy = math.exp(log_E_low + xi * (math.log(E_high) - log_E_low))
         else:
@@ -486,6 +476,6 @@ def _get_group_energy(particle_container, mgxs, simulation, data):
             energy = -1.0
 
     else:
-        energy = 0.0
+        energy = float(group)
 
     return energy
diff --git a/mcdc/transport/tally/filter.py b/mcdc/transport/tally/filter.py
index a743f785f..d976b1bee 100644
--- a/mcdc/transport/tally/filter.py
+++ b/mcdc/transport/tally/filter.py
@@ -16,14 +16,14 @@
 
 
 @njit
-def get_filter_indices(particle_container, tally, data, MG_mode):
+def get_filter_indices(particle_container, tally, data):
     i_mu, i_azi, i_energy, i_time = 0, 0, 0, 0
 
     if tally["filter_direction"]:
         i_mu, i_azi = get_direction_index(particle_container, tally, data)
 
     if tally["filter_energy"]:
-        i_energy = get_energy_index(particle_container, tally, data, MG_mode)
+        i_energy = get_energy_index(particle_container, tally, data)
 
     if tally["filter_time"]:
         i_time = get_time_index(particle_container, tally, data)
@@ -67,13 +67,10 @@ def get_direction_index(particle_container, tally, data):
 
 
 @njit
-def get_energy_index(particle_container, tally, data, neutron_multigroup_mode):
+def get_energy_index(particle_container, tally, data):
     particle = particle_container[0]
 
-    if neutron_multigroup_mode:
-        E = particle["g"]
-    else:
-        E = particle["E"]
+    E = particle["E"]
 
     tolerance = COINCIDENCE_TOLERANCE_ENERGY
     grid_energy = data[
diff --git a/mcdc/transport/tally/score.py b/mcdc/transport/tally/score.py
index 09f9a4889..9b7a228fa 100644
--- a/mcdc/transport/tally/score.py
+++ b/mcdc/transport/tally/score.py
@@ -50,10 +50,7 @@ def surface_crossing(
     surface_crossing_tally = simulation["surface_crossing_tallies"][sub_ID]
 
     # Get filter indices
-    MG_mode = simulation["settings"]["neutron_multigroup_mode"]
-    i_mu, i_azi, i_energy, i_time = get_filter_indices(
-        particle_container, tally, data, MG_mode
-    )
+    i_mu, i_azi, i_energy, i_time = get_filter_indices(particle_container, tally, data)
 
     # No score if outside non-changing phase-space bins
     if i_mu == -1 or i_azi == -1 or i_energy == -1 or i_time == -1:
@@ -131,10 +128,7 @@ def collision(particle_container, collision_data_container, tally, simulation, d
     collision_tally = simulation["collision_tallies"][sub_ID]
 
     # Get filter indices
-    MG_mode = simulation["settings"]["neutron_multigroup_mode"]
-    i_mu, i_azi, i_energy, i_time = get_filter_indices(
-        particle_container, tally, data, MG_mode
-    )
+    i_mu, i_azi, i_energy, i_time = get_filter_indices(particle_container, tally, data)
 
     # No score if outside non-changing phase-space bins
     if i_mu == -1 or i_azi == -1 or i_energy == -1 or i_time == -1:
@@ -188,10 +182,7 @@ def tracklength(particle_container, distance, tally, simulation, data):
     tracklength_tally = simulation["tracklength_tallies"][sub_ID]
 
     # Get filter indices
-    MG_mode = simulation["settings"]["neutron_multigroup_mode"]
-    i_mu, i_azi, i_energy, i_time = get_filter_indices(
-        particle_container, tally, data, MG_mode
-    )
+    i_mu, i_azi, i_energy, i_time = get_filter_indices(particle_container, tally, data)
 
     # No score if outside non-changing phase-space bins
     if i_mu == -1 or i_azi == -1 or i_energy == -1:

From 6bc00fbe78cfa3027dbee3c2071d1841c1b2d3b5 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 8 Aug 2026 07:24:31 +0700
Subject: [PATCH 162/202] debug and add checks for non-integer standard MG mode
 source

---
 mcdc/object_/simulation.py               | 32 ++++++++++
 mcdc/object_/source.py                   |  9 ++-
 mcdc/transport/physics/neutron/native.py |  1 -
 mcdc/transport/technique.py              |  5 +-
 test/unit/test_object_compilation.py     | 79 ++++++++++++++++++++++++
 5 files changed, 118 insertions(+), 8 deletions(-)

diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index 4d40f7b08..dd7b35933 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -25,6 +25,7 @@
 
 ####
 
+from mcdc.constant import PARTICLE_NEUTRON
 from mcdc.object_.base import MCDCBase
 from mcdc.object_.data import DataBase
 from mcdc.object_.distribution import DistributionBase
@@ -342,6 +343,37 @@ def _finalize_compilation(self) -> None:
                         "energy_grid for every multigroup material."
                     )
 
+        # Validate neutron source coordinates for standard multigroup transport
+        else:
+            G = self.materials[0].neutron_multigroup.G
+            for source in self.sources:
+                if source.particle_type != PARTICLE_NEUTRON:
+                    continue
+
+                if source.mono_energetic:
+                    source_energies = np.array([source.energy])
+                elif source.discrete_energy:
+                    source_energies = source.energy_pmf.value
+                else:
+                    print_error(
+                        "Standard neutron multigroup transport requires neutron "
+                        "sources to use a scalar energy or discrete_energy "
+                        "group-coordinate distribution."
+                    )
+
+                if not np.all(np.isfinite(source_energies)) or not np.all(
+                    source_energies == np.floor(source_energies)
+                ):
+                    print_error(
+                        "Standard neutron multigroup source energies must be finite, "
+                        "integer-valued group coordinates."
+                    )
+                if np.any(source_energies < 0) or np.any(source_energies >= G):
+                    print_error(
+                        "Standard neutron multigroup source energies must satisfy "
+                        f"0 <= energy < G (G={G})."
+                    )
+
         # Limit transport to the latest requested tally boundary
         settings.time_boundary = min(
             [settings.time_boundary] + [tally.time[-1] for tally in self.tallies]
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 04529ce2c..fdd24b100 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -71,14 +71,17 @@ class Source(MCDCObject):
         a tabulated distribution: the first row contains energy values and the
         second row contains their probability density in ``eV^-1``. Defaults
         to a mono-energetic source at **1 MeV**. In standard neutron multigroup
-        transport, an integer conventionally specifies a group-coordinate energy and is
-        stored internally as a float.
+        transport, an integer conventionally specifies a group-coordinate
+        energy and is stored internally as a float. The coordinate must identify
+        an available group. Continuous energy distributions are not supported
+        in standard multigroup transport.
     discrete_energy : array_like of float, optional
         Discrete source-energy distribution with shape ``(2, N)``. The first
         row contains sampled energy values and the second row contains their
         probabilities. Values are physical energies in eV for continuous-energy
         transport and group-coordinate energies for standard multigroup
-        transport. Cannot be supplied with ``energy``.
+        transport. Standard-multigroup coordinates must be integer-valued and
+        identify available groups. Cannot be supplied with ``energy``.
     time : real or array_like of float, optional
         Emission time in seconds. A real scalar, including a NumPy scalar,
         defines a discrete emission time. An array-like value with shape
diff --git a/mcdc/transport/physics/neutron/native.py b/mcdc/transport/physics/neutron/native.py
index fa369bf28..25e935e81 100644
--- a/mcdc/transport/physics/neutron/native.py
+++ b/mcdc/transport/physics/neutron/native.py
@@ -930,7 +930,6 @@ def sample_fission(
                 particle["uy"] = particle_new["uy"]
                 particle["uz"] = particle_new["uz"]
                 particle["t"] = particle_new["t"]
-                particle["g"] = particle_new["g"]
                 particle["E"] = particle_new["E"]
                 particle["w"] = particle_new["w"]
             else:
diff --git a/mcdc/transport/technique.py b/mcdc/transport/technique.py
index 30d18414d..602912eae 100644
--- a/mcdc/transport/technique.py
+++ b/mcdc/transport/technique.py
@@ -150,10 +150,7 @@ def get_ww_indices(particle_container, ww_obj, simulation, data):
 
     # get energy index
     energy_bounds = ww_get.energy_bounds_all(ww_obj, data)
-    if simulation["settings"]["neutron_multigroup_mode"]:
-        energy = particle["g"]
-    else:
-        energy = particle["E"]
+    energy = particle["E"]
     ie = util.find_bin(energy, energy_bounds)
 
     # get spatial index
diff --git a/test/unit/test_object_compilation.py b/test/unit/test_object_compilation.py
index c330d0871..a0e9772be 100644
--- a/test/unit/test_object_compilation.py
+++ b/test/unit/test_object_compilation.py
@@ -88,6 +88,85 @@ def test_hybrid_multigroup_requires_explicit_energy_grids(capsys):
     assert "requires an explicit energy_grid" in capsys.readouterr().out
 
 
+@pytest.mark.parametrize(
+    "source",
+    [
+        mcdc.Source(energy=1),
+        mcdc.Source(energy=1.0),
+        mcdc.Source(discrete_energy=([0, 1], [0.25, 0.75])),
+    ],
+)
+def test_standard_multigroup_accepts_integer_group_coordinates(source):
+    material = mcdc.Material.multigroup(capture=[0.1, 0.2])
+    simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell(fill=material)])
+    simulation.set_sources([source])
+
+    simulation.compile()
+
+    assert not simulation.technique.neutron_multigroup.hybrid
+
+
+@pytest.mark.parametrize(
+    "source, expected_message",
+    [
+        (
+            mcdc.Source(energy=0.5),
+            "must be finite, integer-valued group coordinates",
+        ),
+        (
+            mcdc.Source(discrete_energy=([0, 1.5], [0.25, 0.75])),
+            "must be finite, integer-valued group coordinates",
+        ),
+        (
+            mcdc.Source(energy=np.nan),
+            "must be finite, integer-valued group coordinates",
+        ),
+        (
+            mcdc.Source(energy=-1),
+            "must satisfy 0 <= energy < G",
+        ),
+        (
+            mcdc.Source(energy=2),
+            "must satisfy 0 <= energy < G",
+        ),
+        (
+            mcdc.Source(energy=([0.0, 1.0], [1.0, 1.0])),
+            "requires neutron sources to use a scalar energy or discrete_energy",
+        ),
+    ],
+)
+def test_standard_multigroup_rejects_invalid_source_energy(
+    source,
+    expected_message,
+    capsys,
+):
+    material = mcdc.Material.multigroup(capture=[0.1, 0.2])
+    simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell(fill=material)])
+    simulation.set_sources([source])
+
+    with pytest.raises(SystemExit):
+        simulation.compile()
+
+    assert expected_message in capsys.readouterr().out
+
+
+def test_standard_neutron_multigroup_does_not_validate_electron_source_energy():
+    material = mcdc.Material.multigroup(capture=[0.1, 0.2])
+    source = mcdc.Source(
+        particle_type="electron",
+        energy=([1.0e3, 2.0e3], [1.0, 1.0]),
+    )
+    simulation = mcdc.Simulation()
+    simulation.set_model([mcdc.Cell(fill=material)])
+    simulation.set_sources([source])
+
+    simulation.compile()
+
+    assert not simulation.technique.neutron_multigroup.hybrid
+
+
 def test_native_only_simulation_remains_hybrid(monkeypatch):
     # Isolate mode finalization from native data-library loading.
     def compile_nuclide(nuclide, simulation):

From d67a54e37d1361cf52634304a71c189d28bd34e4 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 8 Aug 2026 07:37:08 +0700
Subject: [PATCH 163/202] debug

---
 mcdc/transport/physics/electron/native.py | 12 ++++----
 mcdc/transport/physics/neutron/native.py  | 34 ++++++++++-------------
 2 files changed, 21 insertions(+), 25 deletions(-)

diff --git a/mcdc/transport/physics/electron/native.py b/mcdc/transport/physics/electron/native.py
index 0865fc57c..1f3bb8aef 100644
--- a/mcdc/transport/physics/electron/native.py
+++ b/mcdc/transport/physics/electron/native.py
@@ -53,15 +53,15 @@ def particle_speed(particle_container):
 @njit
 def macro_xs(reaction_type, particle_container, simulation, data):
     particle = particle_container[0]
-    material = simulation["native_materials"][particle["material_ID"]]
+    material = simulation["materials"][particle["material_ID"]]
     E = particle["E"]
 
     total = 0.0
     for i in range(material["N_element"]):
-        element_ID = mcdc_get.native_material.element_IDs(i, material, data)
+        element_ID = mcdc_get.material.element_IDs(i, material, data)
         element = simulation["elements"][element_ID]
 
-        element_density = mcdc_get.native_material.element_densities(i, material, data)
+        element_density = mcdc_get.material.element_densities(i, material, data)
         xs = total_micro_xs(reaction_type, E, element, data)
         total += element_density * xs
 
@@ -115,7 +115,7 @@ def collision(particle_container, collision_data_container, program, data):
     simulation = util.access_simulation(program)
     particle = particle_container[0]
     collision_data = collision_data_container[0]
-    material = simulation["native_materials"][particle["material_ID"]]
+    material = simulation["materials"][particle["material_ID"]]
 
     # Particle properties
     E = particle["E"]
@@ -136,10 +136,10 @@ def collision(particle_container, collision_data_container, program, data):
     xi = rng.lcg(particle_container) * SigmaT
     total = 0.0
     for i in range(material["N_element"]):
-        element_ID = mcdc_get.native_material.element_IDs(i, material, data)
+        element_ID = mcdc_get.material.element_IDs(i, material, data)
         element = simulation["elements"][element_ID]
 
-        element_density = mcdc_get.native_material.element_densities(i, material, data)
+        element_density = mcdc_get.material.element_densities(i, material, data)
         sigmaT = total_micro_xs(ELECTRON_REACTION_TOTAL, E, element, data)
 
         total += element_density * sigmaT
diff --git a/mcdc/transport/physics/neutron/native.py b/mcdc/transport/physics/neutron/native.py
index 25e935e81..bb69d7e5e 100644
--- a/mcdc/transport/physics/neutron/native.py
+++ b/mcdc/transport/physics/neutron/native.py
@@ -72,16 +72,16 @@ def particle_energy_from_speed(speed):
 @njit
 def macro_xs(reaction_type, particle_container, simulation, data):
     particle = particle_container[0]
-    material = simulation["native_materials"][particle["material_ID"]]
+    material = simulation["materials"][particle["material_ID"]]
     E = particle["E"]
 
     total = 0.0
 
     for i in range(material["N_nuclide"]):
-        nuclide_ID = mcdc_get.native_material.nuclide_IDs(i, material, data)
+        nuclide_ID = mcdc_get.material.nuclide_IDs(i, material, data)
         nuclide = simulation["nuclides"][nuclide_ID]
 
-        nuclide_density = mcdc_get.native_material.nuclide_densities(i, material, data)
+        nuclide_density = mcdc_get.material.nuclide_densities(i, material, data)
         xs = total_micro_xs(reaction_type, E, nuclide, data)
 
         total += nuclide_density * xs
@@ -171,16 +171,15 @@ def neutron_production_xs(reaction_type, particle_container, simulation, data):
 @njit
 def _neutron_inelastic_scattering_production_xs(particle_container, simulation, data):
     particle = particle_container[0]
-    material_base = simulation["materials"][particle["material_ID"]]
-    material = simulation["native_materials"][material_base["sub_ID"]]
+    material = simulation["materials"][particle["material_ID"]]
 
     total = 0.0
     for i in range(material["N_nuclide"]):
-        nuclide_ID = mcdc_get.native_material.nuclide_IDs(i, material, data)
+        nuclide_ID = mcdc_get.material.nuclide_IDs(i, material, data)
         nuclide = simulation["nuclides"][nuclide_ID]
 
         E = particle["E"]
-        nuclide_density = mcdc_get.native_material.nuclide_densities(i, material, data)
+        nuclide_density = mcdc_get.material.nuclide_densities(i, material, data)
 
         for j in range(nuclide["N_neutron_inelastic_scattering_reaction"]):
             reaction_ID = mcdc_get.nuclide.neutron_inelastic_scattering_reaction_IDs(
@@ -201,21 +200,20 @@ def _neutron_inelastic_scattering_production_xs(particle_container, simulation,
 @njit
 def _neutron_fission_production_xs(particle_container, simulation, data):
     particle = particle_container[0]
-    material_base = simulation["materials"][particle["material_ID"]]
-    material = simulation["native_materials"][material_base["sub_ID"]]
+    material = simulation["materials"][particle["material_ID"]]
 
-    if not material_base["fissionable"]:
+    if not material["fissionable"]:
         return 0.0
 
     total = 0.0
     for i in range(material["N_nuclide"]):
-        nuclide_ID = mcdc_get.native_material.nuclide_IDs(i, material, data)
+        nuclide_ID = mcdc_get.material.nuclide_IDs(i, material, data)
         nuclide = simulation["nuclides"][nuclide_ID]
         if not nuclide["fissionable"]:
             continue
 
         E = particle["E"]
-        nuclide_density = mcdc_get.native_material.nuclide_densities(i, material, data)
+        nuclide_density = mcdc_get.material.nuclide_densities(i, material, data)
 
         for j in range(nuclide["N_neutron_fission_reaction"]):
             reaction_ID = mcdc_get.nuclide.neutron_fission_reaction_IDs(
@@ -242,7 +240,7 @@ def collision(particle_container, collision_data_container, program, data):
     simulation = util.access_simulation(program)
     particle = particle_container[0]
     collision_data = collision_data_container[0]
-    material = simulation["native_materials"][particle["material_ID"]]
+    material = simulation["materials"][particle["material_ID"]]
 
     # Particle properties
     E = particle["E"]
@@ -266,11 +264,9 @@ def collision(particle_container, collision_data_container, program, data):
 
         # Q-value: xs-weighted average over all nuclides and capture reactions
         for i in range(material["N_nuclide"]):
-            nuclide_ID = mcdc_get.native_material.nuclide_IDs(i, material, data)
+            nuclide_ID = mcdc_get.material.nuclide_IDs(i, material, data)
             nuclide = simulation["nuclides"][nuclide_ID]
-            nuclide_density = mcdc_get.native_material.nuclide_densities(
-                i, material, data
-            )
+            nuclide_density = mcdc_get.material.nuclide_densities(i, material, data)
             for j in range(nuclide["N_neutron_capture_reaction"]):
                 reaction_ID = mcdc_get.nuclide.neutron_capture_reaction_IDs(
                     j, nuclide, data
@@ -291,10 +287,10 @@ def collision(particle_container, collision_data_container, program, data):
     xi = rng.lcg(particle_container) * SigmaT
     total = 0.0
     for i in range(material["N_nuclide"]):
-        nuclide_ID = mcdc_get.native_material.nuclide_IDs(i, material, data)
+        nuclide_ID = mcdc_get.material.nuclide_IDs(i, material, data)
         nuclide = simulation["nuclides"][nuclide_ID]
 
-        nuclide_density = mcdc_get.native_material.nuclide_densities(i, material, data)
+        nuclide_density = mcdc_get.material.nuclide_densities(i, material, data)
         sigmaT = total_micro_xs(NEUTRON_REACTION_TOTAL, E, nuclide, data)
 
         if simulation["technique"]["implicit_capture"]["active"]:

From 8655a0f41439550a5d2a18b6c7dbeea0c2c04f7a Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 8 Aug 2026 11:10:39 +0700
Subject: [PATCH 164/202] debug

---
 mcdc/visualize.py                      |  3 +--
 test/unit/test_particle.py             |  1 -
 test/unit/transport/test_multigroup.py | 23 +++++++++--------------
 3 files changed, 10 insertions(+), 17 deletions(-)

diff --git a/mcdc/visualize.py b/mcdc/visualize.py
index bf986f349..58db720bc 100644
--- a/mcdc/visualize.py
+++ b/mcdc/visualize.py
@@ -96,9 +96,8 @@ def _compute_material_row(
 
         particle = particle_arr[0]
 
-        # Set time and energy
+        # Set time, energy, and direction
         particle["t"] = time_val
-        particle["group"] = 0
         particle["E"] = 1e6
         particle["ux"] = 0.0
         particle["uy"] = 0.0
diff --git a/test/unit/test_particle.py b/test/unit/test_particle.py
index df04e987d..438075c9f 100644
--- a/test/unit/test_particle.py
+++ b/test/unit/test_particle.py
@@ -16,7 +16,6 @@ def test_copy_particle_data_to_active_particle():
         "ux": 0.1,
         "uy": 0.2,
         "uz": 0.3,
-        "group": 7,
         "E": 8.0,
         "w": 9.0,
         "particle_type": 10,
diff --git a/test/unit/transport/test_multigroup.py b/test/unit/transport/test_multigroup.py
index 82aeb94b5..d4568b2b6 100644
--- a/test/unit/transport/test_multigroup.py
+++ b/test/unit/transport/test_multigroup.py
@@ -39,11 +39,10 @@ def test_group_energy_representation(representation, expected, prepare_simulatio
     )
     simulation["technique"]["neutron_multigroup"]["hybrid"] = True
 
-    particle_container = np.zeros(1, dtype=type_.particle)
-    particle_container[0]["group"] = 1
-    particle_container[0]["rng_seed"] = np.uint64(1)
+    rng_state = np.zeros(1, dtype=type_.particle)
+    rng_state[0]["rng_seed"] = np.uint64(1)
 
-    energy = multigroup._get_group_energy(particle_container, mgxs, simulation, data)
+    energy = multigroup._get_group_energy(1, rng_state, mgxs, simulation, data)
 
     if expected is None:
         assert 10.0 <= energy < 100.0
@@ -51,18 +50,17 @@ def test_group_energy_representation(representation, expected, prepare_simulatio
         assert energy == pytest.approx(expected)
 
 
-def test_standard_multigroup_does_not_reconstruct_energy(prepare_simulation):
+def test_standard_multigroup_uses_group_coordinate_energy(prepare_simulation):
     simulation, mgxs, data = _prepare_multigroup(
         prepare_simulation,
         capture=[1.0, 1.0],
     )
 
-    particle_container = np.zeros(1, dtype=type_.particle)
-    particle_container[0]["group"] = 1
+    rng_state = np.zeros(1, dtype=type_.particle)
 
-    energy = multigroup._get_group_energy(particle_container, mgxs, simulation, data)
+    energy = multigroup._get_group_energy(1, rng_state, mgxs, simulation, data)
 
-    assert energy == 0.0
+    assert energy == 1.0
 
 
 def test_hybrid_energy_groups_are_left_closed(prepare_simulation):
@@ -78,10 +76,10 @@ def test_hybrid_energy_groups_are_left_closed(prepare_simulation):
 
     particle["E"] = 1.0
     assert multigroup.applicable(particle_container, simulation, data)
-    assert multigroup._get_energy_group(particle_container, mgxs, simulation, data) == 0
+    assert multigroup._get_energy_group(particle["E"], mgxs, simulation, data) == 0
 
     particle["E"] = 10.0
-    assert multigroup._get_energy_group(particle_container, mgxs, simulation, data) == 1
+    assert multigroup._get_energy_group(particle["E"], mgxs, simulation, data) == 1
 
     particle["E"] = 100.0
     assert not multigroup.applicable(particle_container, simulation, data)
@@ -102,13 +100,11 @@ def _make_particle():
 def _assert_fission_products(particle_container, simulation):
     particle = particle_container[0]
     assert particle["alive"]
-    assert particle["group"] == 1
     assert particle["E"] == pytest.approx(55.0)
 
     bank = simulation["bank_active"]
     assert bank["size"][0] == 3
     banked = bank["particle_data"][:3]
-    np.testing.assert_array_equal(banked["group"], 1)
     np.testing.assert_allclose(banked["E"], 55.0)
 
 
@@ -124,7 +120,6 @@ def test_scattering_product_uses_multigroup_data(prepare_simulation):
 
     particle = particle_container[0]
     assert particle["alive"]
-    assert particle["group"] == 1
     assert particle["E"] == pytest.approx(55.0)
 
 

From 749fc32c3a60bc755f4cf358aa17a1dc01b17628 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 8 Aug 2026 17:30:04 +0700
Subject: [PATCH 165/202] update docs

---
 .../architecture/runtime_data_layout.rst      | 41 +++----------
 .../architecture/simulation_compilation.rst   |  9 +++
 .../extending/extending_the_object_model.rst  |  6 +-
 ...riting_numba_compatible_transport_code.rst |  4 +-
 docs/source/examples/kobayashi_dog_leg.rst    |  2 +-
 docs/source/theory/continuous_energy.rst      |  2 +-
 .../getting_started/first_simulation.rst      |  4 +-
 .../getting_started/what_is_mcdc.rst          |  2 +-
 docs/source/user_guide/index.rst              |  1 +
 .../user_guide/materials_and_multigroup.rst   | 35 +++--------
 docs/source/user_guide/sources.rst            | 61 +++++++++++++++++++
 docs/source/user_guide/tallies.rst            | 28 ++++-----
 12 files changed, 114 insertions(+), 81 deletions(-)
 create mode 100644 docs/source/user_guide/sources.rst

diff --git a/docs/source/developer_guide/architecture/runtime_data_layout.rst b/docs/source/developer_guide/architecture/runtime_data_layout.rst
index 72fa92c8e..01f5b331c 100644
--- a/docs/source/developer_guide/architecture/runtime_data_layout.rst
+++ b/docs/source/developer_guide/architecture/runtime_data_layout.rst
@@ -14,8 +14,7 @@ The representation has two complementary parts:
    A contiguous one-dimensional NumPy array containing variable-length numerical payloads and lists of object IDs.
 
 The same logical representation is supplied to Python, Numba-CPU, and Numba-GPU execution.
-During Python-only prototyping, transport code may also access arbitrary Python state alongside this representation.
-A method intended for portable, maintained execution must express the state required by transport through the prepared representation.
+Portable transport code expresses its state through this prepared representation.
 See :doc:`python_first_numba_accelerated_design` for this development model.
 
 Why Two Structures?
@@ -23,8 +22,13 @@ Why Two Structures?
 
 Python model objects may contain arrays whose sizes depend on the problem: energy grids, cross sections, mesh boundaries, motion tables, tally filters, and many others.
 Nested Python object references and variable-sized arrays cannot be embedded directly in the stable NumPy structured dtype required by the Numba execution modes.
+Separating fixed-layout metadata from variable-length values keeps the structured dtype stable while accommodating model-dependent payloads.
 
-MC/DC separates fixed-layout metadata from variable-length values:
+Runtime Object Model
+--------------------
+
+Fixed fields become structured-record fields, Python object references become simulation-local IDs, and variable-length fields become offsets into ``data``.
+Generated ``mcdc_get`` and ``mcdc_set`` accessors perform the corresponding lookups and offset calculations.
 
 .. image:: ../../images/developer_guide/architecture/runtime_data_layout.png
    :width: 100%
@@ -33,36 +37,10 @@ MC/DC separates fixed-layout metadata from variable-length values:
 The figure follows one connected example from Python model objects into the two runtime layers.
 The cell record locates its three surface IDs in ``data``, the selected surface record locates an attached tally ID, and the base tally record identifies its concrete surface-crossing record.
 Tally scores, bins, and other variable-length payloads share the same flat arena.
-Generated ``mcdc_get`` and ``mcdc_set`` accessors translate logical field access into the required offset calculation.
 The IDs and offsets shown in the figure are illustrative; their values depend on the compiled model and its packed layout.
 
-An Explicit Runtime Object Model
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Together, the structured records, flat data arena, and generated accessors form an explicit runtime object model.
-A conventional object runtime stores fixed fields with the object while references point to separately allocated objects and variable-length values.
-Accessing an attribute follows those references without requiring application code to know where the referenced memory resides.
-
-MC/DC makes comparable operations explicit.
-Fixed fields become structured-record fields, Python object references become simulation-local IDs, variable-length fields become offsets into ``data``, and generated accessors perform the corresponding lookup or offset calculation.
-The combination of ``simulation`` and ``data`` can therefore be understood as a purpose-built runtime object model backed by explicit records and a flat data arena.
-
-Seen narrowly, this design reinvents facilities already supplied by Python and other language runtimes.
-MC/DC derives schemas, assigns object identities, packs values, represents relationships, dispatches among concrete representations, and generates field accessors.
-Maintaining this machinery adds implementation complexity and requires MC/DC to define rules that an ordinary class system would otherwise manage automatically.
-
-The duplication is necessary because the Python object model does not satisfy Numba execution requirements.
-Python objects may contain interpreter-managed references, dynamic types, arbitrary inheritance behavior, and separately allocated containers that Numba cannot generally compile or transfer to an accelerator.
-Host pointers also cannot serve as portable references to state allocated in a GPU address space.
-MC/DC instead needs a complete representation with predictable types, explicit ownership, stable relationships, and equivalent access patterns across Python, Numba-CPU, and Numba-GPU execution.
-
-The current single ``float64`` data arena is a simplifying choice within this design rather than an inherent requirement of an explicit runtime object model.
-It gives MC/DC one variable-length allocation, one offset space, and consistent function signatures across execution modes.
-Integer values stored in the arena, including lists of object IDs, are exactly representable for practical MC/DC model sizes, and generated scalar getters cast them back to integers when accessed.
-Separate typed arenas could preserve integer types and avoid those conversions, but would introduce additional allocations, offsets, generated accessors, function arguments, and GPU memory management.
-
-MC/DC's implementation should therefore be viewed neither as an ordinary Python class layout nor as a general-purpose replacement for one.
-It is a specialized, arena-backed object model that exchanges language-level generality for the predictable representation required by portable particle-transport execution.
+The ``data`` arena uses ``float64`` values, one allocation, and one offset space across execution modes.
+Integer values stored in the arena, including object IDs, are restored to their declared types by generated scalar accessors.
 
 Object Collections
 ^^^^^^^^^^^^^^^^^^
@@ -261,7 +239,6 @@ They use:
 
 The layout is fixed for the duration of a prepared run.
 Transport may update allocated values, tally bins, particle banks, and runtime counters, but it cannot resize a field or introduce a new model object.
-A Python-only prototype may temporarily read or modify external Python state, but that state is not part of the portable runtime layout.
 Changing the prepared MC/DC model requires a new model compilation and runtime preparation pass.
 
 Execution Backends
diff --git a/docs/source/developer_guide/architecture/simulation_compilation.rst b/docs/source/developer_guide/architecture/simulation_compilation.rst
index 151512036..f7886a818 100644
--- a/docs/source/developer_guide/architecture/simulation_compilation.rst
+++ b/docs/source/developer_guide/architecture/simulation_compilation.rst
@@ -202,6 +202,15 @@ The compiler traverses embedded simulation configuration before model-wide final
 This boundary keeps scientific model rules in ``mcdc/object_/``.
 The orchestration in ``python_objects_compiler.py`` changes only when the compilation framework gains a new phase or registered category, while ``mcdc.main.prepare`` remains responsible for framework-level runtime setup after the model is complete.
 
+Neutron Multigroup Finalization
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+For neutron multigroup transport, model-wide finalization selects standard transport only when every material has multigroup data without native composition and all multigroup energy grids are identical.
+An omitted grid is represented internally by a zero-valued ``G + 1`` placeholder, allowing materials that all omit the grid to share one standard multigroup structure.
+All other material combinations select hybrid transport, for which each multigroup dataset requires an explicit physical energy grid.
+Standard transport interprets the particle's ``E`` field as a dimensionless group coordinate, while hybrid transport interprets it as physical energy in eV and maps it through ``energy_grid`` and ``energy_representation``.
+Finalization also validates standard-multigroup source energies and resolves ``energy="all"`` tally filters.
+
 Deduplication and Cycles
 ------------------------
 
diff --git a/docs/source/developer_guide/extending/extending_the_object_model.rst b/docs/source/developer_guide/extending/extending_the_object_model.rst
index 7bc882f6f..68a7cc667 100644
--- a/docs/source/developer_guide/extending/extending_the_object_model.rst
+++ b/docs/source/developer_guide/extending/extending_the_object_model.rst
@@ -168,9 +168,9 @@ The layer generator interprets annotations according to the field's role:
    * - ``move_velocities: Annotated[NDArray[float64], ("N_move", 3)]``
      - Offset, length, and shape metadata plus flattened values
      - ``mcdc_get.surface.move_velocities(move, axis, surface, data)``
-   * - ``group_pmf: DistributionPMF``
+   * - ``energy_pmf: DistributionPMF``
      - Simulation-local object ID
-     - ``simulation["distributions"][source["group_pmf_ID"]]``
+     - ``simulation["distributions"][source["energy_pmf_ID"]]``
    * - ``collision_tallies: list[TallyCollision]``
      - Count and offset to IDs stored in ``data``
      - ``mcdc_get.cell.collision_tally_IDs(index, cell, data)``
@@ -203,7 +203,7 @@ Transport then reads one value through the generated accessor:
 
 .. code-block:: python
 
-   bias = mcdc_get.source.energy_bias(group, source, data)
+   bias = mcdc_get.source.energy_bias(index, source, data)
 
 Avoid adding parallel state in several classes.
 If a value belongs to the simulation as a whole, place it in ``Simulation`` or one of its embedded configuration objects and pass or access that representation consistently.
diff --git a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
index 32f2827a4..4a84436dd 100644
--- a/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
+++ b/docs/source/developer_guide/extending/writing_numba_compatible_transport_code.rst
@@ -101,10 +101,10 @@ For example, recover a prepared distribution by simulation-local ID instead of p
 .. code-block:: python
 
    # Python model construction
-   source_object.group_pmf = distribution_object
+   source_object.energy_pmf = distribution_object
 
    # Portable transport representation
-   distribution = simulation["distributions"][source["group_pmf_ID"]]
+   distribution = simulation["distributions"][source["energy_pmf_ID"]]
 
 Keep Types Stable
 ^^^^^^^^^^^^^^^^^
diff --git a/docs/source/examples/kobayashi_dog_leg.rst b/docs/source/examples/kobayashi_dog_leg.rst
index 861107790..bb0d6699f 100644
--- a/docs/source/examples/kobayashi_dog_leg.rst
+++ b/docs/source/examples/kobayashi_dog_leg.rst
@@ -102,7 +102,7 @@ This section walks through the input file block by block.
    :linenos:
    :lineno-match:
 
-Two mono-energetic multi-group materials are created:
+Two mono-energetic multigroup materials are created:
 ``m`` for the shield (:math:`\Sigma_c = \Sigma_s = 0.05`) and
 ``m_void`` for the dog-leg channel (:math:`10^{-4}` total).
 
diff --git a/docs/source/theory/continuous_energy.rst b/docs/source/theory/continuous_energy.rst
index 8004100ca..5691a4d1f 100644
--- a/docs/source/theory/continuous_energy.rst
+++ b/docs/source/theory/continuous_energy.rst
@@ -5,7 +5,7 @@ Continuous Energy
 =================
 
 MC/DC supports continuous energy (CE) neutron transport using pointwise nuclear data libraries.
-In CE mode, cross sections are represented as energy-dependent tabulated data rather than multi-group averages, enabling higher-fidelity simulations.
+In CE mode, cross sections are represented as energy-dependent tabulated data rather than multigroup averages, enabling higher-fidelity simulations.
 
 Data Libraries
 --------------
diff --git a/docs/source/user_guide/getting_started/first_simulation.rst b/docs/source/user_guide/getting_started/first_simulation.rst
index 66e9e67d0..d68511c10 100644
--- a/docs/source/user_guide/getting_started/first_simulation.rst
+++ b/docs/source/user_guide/getting_started/first_simulation.rst
@@ -133,14 +133,14 @@ MC/DC reaches their materials and surfaces when it compiles the simulation, so t
 Source
 ~~~~~~
 
-The source emits group-0 particles isotropically and uniformly throughout the first cell:
+In standard multigroup transport, ``energy=0`` emits particles at group 0 isotropically and uniformly throughout the first cell:
 
 .. code-block:: python3
 
    source = mcdc.Source(
        z=[0.0, 2.0],
        isotropic=True,
-       group=0,
+       energy=0,
    )
    simulation.set_sources([source])
 
diff --git a/docs/source/user_guide/getting_started/what_is_mcdc.rst b/docs/source/user_guide/getting_started/what_is_mcdc.rst
index beb3ea7d3..8620d4d65 100644
--- a/docs/source/user_guide/getting_started/what_is_mcdc.rst
+++ b/docs/source/user_guide/getting_started/what_is_mcdc.rst
@@ -16,7 +16,7 @@ uncertainty quantification methods, and high-performance computing algorithms.
 It also provides an accessible platform for students learning Monte Carlo
 radiation transport methods and modern code development.
 
-**Capabilities** — MC/DC supports continuous-energy and multi-group neutron
+**Capabilities** — MC/DC supports continuous-energy and multigroup neutron
 transport calculations, including fixed-source and eigenvalue simulations on
 constructive solid geometry (CSG) models. For continuous-energy transport,
 MC/DC converts `ACE <https://nucleardata.lanl.gov/ace/>`_-format nuclear data
diff --git a/docs/source/user_guide/index.rst b/docs/source/user_guide/index.rst
index a4479e4c1..99d864677 100644
--- a/docs/source/user_guide/index.rst
+++ b/docs/source/user_guide/index.rst
@@ -34,6 +34,7 @@ changing selected inputs.
 
    simulation_lifecycle
    materials_and_multigroup
+   sources
    iterative_simulations
    tallies
 
diff --git a/docs/source/user_guide/materials_and_multigroup.rst b/docs/source/user_guide/materials_and_multigroup.rst
index 96b7ed4d6..e7ad37fe3 100644
--- a/docs/source/user_guide/materials_and_multigroup.rst
+++ b/docs/source/user_guide/materials_and_multigroup.rst
@@ -58,14 +58,13 @@ Macroscopic cross sections use cm\ :sup:`-1`, group speeds use cm/s, and precurs
    )
 
 Multigroup Energy Grids and Representation
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 An explicit ``energy_grid`` contains ``G + 1`` physical energy boundaries in eV.
 Group ``g`` covers ``energy_grid[g] <= E < energy_grid[g + 1]``.
 The grid both maps continuous energy to a group and bounds continuous energy reconstructed from a group.
 
-When no grid is supplied, MC/DC stores a zero-valued placeholder with length ``G + 1``.
-The placeholder does not represent physical energy boundaries and is used only for standard multigroup transport, where the particle's group is authoritative and continuous energy does not select a group.
+The grid may be omitted for standard multigroup transport when every material omits ``energy_grid``.
 
 For lower and upper group boundaries :math:`E_g` and :math:`E_{g+1}`, the energy-representation policies are:
 
@@ -74,21 +73,23 @@ For lower and upper group boundaries :math:`E_g` and :math:`E_{g+1}`, the energy
 - ``"uniform"``: sample :math:`E` uniformly between the two boundaries; and
 - ``"log_uniform"``: sample :math:`\log E` uniformly between their logarithms, equivalently :math:`E=E_g(E_{g+1}/E_g)^\xi` for :math:`\xi\sim\mathcal{U}(0,1)`.
 
-The policies apply when an explicit physical energy grid is used.
+The policies apply when transport reconstructs physical energy from a group, including after a hybrid multigroup interaction.
 The logarithmic policies require strictly positive energy boundaries.
 Midpoint policies reconstruct one deterministic value per group, while uniform policies sample a new value when continuous energy is reconstructed.
+Standard multigroup transport retains the group coordinate instead and does not apply a physical-energy reconstruction policy during particle transport.
 
 MC/DC determines the neutron multigroup transport organization when the simulation is compiled.
-Standard neutron multigroup transport means that every material uses neutron multigroup data without native composition and that all materials share one energy grid.
-MC/DC selects this organization only when every material satisfies those conditions.
-This includes materials sharing either the zero-valued placeholder or the same explicit physical grid.
+Standard neutron multigroup transport applies when every material uses neutron multigroup data without native composition and all materials either omit ``energy_grid`` or share the same explicit grid.
+In standard multigroup transport, particle energy uses a dimensionless group coordinate: energy ``0.0`` represents group 0, energy ``1.0`` represents group 1, and so forth.
 
 Transport is hybrid when native composition data is present or multigroup materials use different grids.
 Every multigroup dataset participating in hybrid transport requires an explicit physical energy grid because continuous energy selects the applicable material-local group.
+In hybrid transport, particle energy remains physical energy in eV, and ``energy_grid`` maps it to a material-local group.
+The material's ``energy_representation`` policy maps an outgoing group back to physical energy.
 If a particle lies outside that grid, MC/DC uses the material's native neutron data when present; without a native composition, the material has zero interaction cross section at that energy.
 
 Combining Native and Multigroup Data
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 Construct :class:`mcdc.NeutronMultigroupData` directly when attaching it to a material with a :ref:`native composition <user_native_transport>`:
 
@@ -108,20 +109,4 @@ Construct :class:`mcdc.NeutronMultigroupData` directly when attaching it to a ma
 The explicit energy grid is required whenever a native composition and neutron multigroup data are combined.
 Its bounds identify the energy interval where the multigroup transport model is available.
 
-Particle Energy and Group State
--------------------------------
-
-A particle carries continuous ``energy`` and an auxiliary integer ``group`` as separate state.
-:class:`mcdc.Source` accepts an independent continuous energy distribution in eV and discrete group distribution:
-
-.. code-block:: python
-
-   source = mcdc.Source(
-       energy=1.0e6,
-       group=([0, 1], [0.25, 0.75]),
-   )
-
-The physics using ``group`` determines its meaning.
-Neutron multigroup transport uses it as the neutron energy-group index.
-If both variables are supplied, the group takes precedence over energy only for standard neutron multigroup transport selected during compilation.
-The tally equivalents are the separate ``group`` and ``energy`` filters described in :doc:`tallies`.
+See :ref:`user_standard_multigroup_sources` for the corresponding source-energy convention.
diff --git a/docs/source/user_guide/sources.rst b/docs/source/user_guide/sources.rst
new file mode 100644
index 000000000..8a98890be
--- /dev/null
+++ b/docs/source/user_guide/sources.rst
@@ -0,0 +1,61 @@
+.. _user_sources:
+
+================
+Particle Sources
+================
+
+A :class:`mcdc.Source` describes the position, direction, energy, time, particle type, and relative probability of particles introduced into a simulation.
+Position and spatial bounds use cm, physical energy uses eV, time uses seconds, and direction vectors are dimensionless.
+Only sources passed to :meth:`mcdc.Simulation.set_sources` participate in transport.
+
+Energy Distributions
+--------------------
+
+A scalar ``energy`` defines a mono-energetic source:
+
+.. code-block:: python
+
+   physical_source = mcdc.Source(energy=1.0e6)
+
+An ``energy`` array with shape ``(2, N)`` defines a continuous probability density with energy values in the first row in eV and density in the second row in eV\ :sup:`-1`.
+Use ``discrete_energy`` for a probability mass function over physical emission lines:
+
+.. code-block:: python
+
+   emission_lines = mcdc.Source(
+       particle_type="electron",
+       discrete_energy=(
+           [1.0e5, 2.0e5],
+           [0.8, 0.2],
+       ),
+   )
+
+The values in the second row are dimensionless relative probabilities.
+The ``energy`` and ``discrete_energy`` inputs are alternative source-energy specifications and cannot be combined.
+
+.. _user_standard_multigroup_sources:
+
+Standard Neutron Multigroup Sources
+-----------------------------------
+
+Standard neutron multigroup transport uses a dimensionless group coordinate in place of physical source energy.
+A scalar integer selects one group:
+
+.. code-block:: python
+
+   group_zero_source = mcdc.Source(energy=0)
+
+Use ``discrete_energy`` to sample among groups:
+
+.. code-block:: python
+
+   group_mixture = mcdc.Source(
+       discrete_energy=(
+           [0, 1],
+           [0.25, 0.75],
+       ),
+   )
+
+Group coordinates must be finite, integer-valued, and satisfy ``0 <= energy < G``.
+Continuous ``energy`` distributions are not valid in standard neutron multigroup transport.
+Native and hybrid transport use physical source energy in eV, as described in :doc:`materials_and_multigroup`.
diff --git a/docs/source/user_guide/tallies.rst b/docs/source/user_guide/tallies.rst
index 5a6dcd92a..9059b4ea0 100644
--- a/docs/source/user_guide/tallies.rst
+++ b/docs/source/user_guide/tallies.rst
@@ -11,15 +11,15 @@ The code snippets assume NumPy has been imported as ``np``.
 Each tally combines:
 
 - one or more scores, such as flux, collision rate, or current;
-- optional particle, spatial, angular, group, energy, time, surface, or cell filters; and
+- optional particle, spatial, angular, energy, time, surface, or cell filters; and
 - a name used to identify the tally in the output file.
 
 Only tallies passed to ``simulation.set_tallies(...)`` are scored.
 
-Particle, Group, and Energy Filters
------------------------------------
+Particle and Energy Filters
+---------------------------
 
-The ``particle_type``, ``group``, and ``energy`` filters are independent.
+The ``particle_type`` and ``energy`` filters are independent.
 If ``particle_type`` is omitted, a tally accepts any transported particle type.
 Set it explicitly when one tally should score only neutrons, electrons, or protons:
 
@@ -32,10 +32,9 @@ Set it explicitly when one tally should score only neutrons, electrons, or proto
        energy=[0.0, 1.0e6, 20.0e6],
    )
 
-``energy`` contains continuous-energy bin boundaries in eV.
-``group`` contains boundaries for the independent auxiliary integer group state.
-The physics using the group determines its meaning.
-For neutron multigroup transport, it is the neutron energy-group index, and tally boundaries can coarsen several energy groups into one bin:
+For native and hybrid transport, ``energy`` contains physical energy-bin boundaries in eV.
+For standard neutron multigroup transport, ``energy`` instead contains boundaries on the dimensionless group coordinate.
+Half-integer boundaries can retain individual groups or collapse several adjacent groups into one tally bin:
 
 .. code-block:: python3
 
@@ -43,21 +42,22 @@ For neutron multigroup transport, it is the neutron energy-group index, and tall
        name="collapsed_group_flux",
        scores=["flux"],
        particle_type="neutron",
-       group=[-0.5, 1.5, 3.5],
+       energy=[-0.5, 1.5, 3.5],
    )
 
-Use ``group="all"`` to create one tally bin per neutron energy group during simulation compilation:
+Use ``energy="all"`` to create one tally bin per neutron energy group during simulation compilation:
 
 .. code-block:: python3
 
    group_flux = mcdc.Tally(
        name="group_flux",
        scores=["flux"],
-       group="all",
+       energy="all",
    )
 
-The ``"all"`` shortcut supports neutron groups when every material contains neutron multigroup data on one shared energy grid.
-``particle_type`` may be omitted or set to ``"neutron"``.
+The ``"all"`` shortcut is valid only when compilation selects standard neutron multigroup transport.
+For this shortcut, omit ``particle_type`` or set it to ``"neutron"``.
+Compilation replaces it with ``[-0.5, 0.5, ..., G - 0.5]`` for the shared ``G``-group structure.
 
 Mesh Tallies
 ------------
@@ -196,7 +196,7 @@ Load and normalize the mesh flux with h5py:
    flux_sdev /= dz
 
 The score arrays contain values integrated over their bins.
-Spatial grids in the output retain cm, angular grids use radians or dimensionless polar cosine, energy grids use eV, and time grids use seconds.
+Spatial grids in the output retain cm, angular grids use radians or dimensionless polar cosine, physical energy grids use eV, standard-multigroup group-coordinate grids are dimensionless, and time grids use seconds.
 Divide by the applicable bin widths when a differential result is required.
 
 Reducing an Angular Tally

From 7a7316744fb3f62d2b47b7942d2b95ae24650787 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sat, 8 Aug 2026 18:08:59 +0700
Subject: [PATCH 166/202] update CHANGELOG

---
 CHANGELOG.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 9f24e3b2b..044192510 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -8,8 +8,12 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/2.0.0/),
 
 ### Added
 
+- Add `NeutronMultigroupData` and hybrid neutron multigroup transport with material-local physical energy grids and energy-representation policies, together with the `Material.multigroup()` convenience interface, from [@ilhamv]
+
 ### Changed
 
+- **Breaking:** Unify native and neutron multigroup materials under one non-polymorphic `Material` and runtime layout, replacing `MaterialMG` and the separate native and multigroup material structures, from [@ilhamv]
+- Group transport techniques under `simulation.technique`, from [@ilhamv]
 - Modernize and reorganize the documentation around distinct user, API reference, theory, project, and developer paths; adopt the PyData Sphinx Theme; and expand the architecture and extension guidance from [@ilhamv]
 - Move model-specific finalization into simulation compilation and reserve runtime preparation for framework-level packing and execution setup from [@ilhamv]
 - **Breaking:** Encapsulate MC/DC model building and execution within an explicit `mcdc.Simulation` instance, replacing the global simulation state and interface from [@ilhamv]

From a55630ade6ee2fc6eee64e4eafec8955ff951e92 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Sun, 9 Aug 2026 22:58:15 +0700
Subject: [PATCH 167/202] add hybrid nultigroup example

---
 docs/source/examples/hybrid_multigroup.rst    |  37 ++++++++++++
 docs/source/examples/index.rst                |   1 +
 .../hybrid_multigroup/hybrid_multigroup.h5    | Bin 0 -> 33320 bytes
 examples/hybrid_multigroup/input.py           |  57 ++++++++++++++++++
 examples/hybrid_multigroup/process-output.py  |  29 +++++++++
 test/regression/hybrid_multigroup/answer.h5   | Bin 0 -> 33320 bytes
 test/regression/hybrid_multigroup/input.py    |  53 ++++++++++++++++
 7 files changed, 177 insertions(+)
 create mode 100644 docs/source/examples/hybrid_multigroup.rst
 create mode 100644 examples/hybrid_multigroup/hybrid_multigroup.h5
 create mode 100644 examples/hybrid_multigroup/input.py
 create mode 100644 examples/hybrid_multigroup/process-output.py
 create mode 100644 test/regression/hybrid_multigroup/answer.h5
 create mode 100644 test/regression/hybrid_multigroup/input.py

diff --git a/docs/source/examples/hybrid_multigroup.rst b/docs/source/examples/hybrid_multigroup.rst
new file mode 100644
index 000000000..f8ba3074e
--- /dev/null
+++ b/docs/source/examples/hybrid_multigroup.rst
@@ -0,0 +1,37 @@
+.. _example_hybrid_multigroup:
+
+===========================
+Hybrid Multigroup Transport
+===========================
+
+This fixed-source problem combines native H-1 composition with one-group neutron multigroup data on the same material.
+The 1 eV source lies inside the multigroup interval from 0.1 to 10 eV, while the 1 MeV source uses native H-1 physics outside that interval.
+Multigroup scattering represents the outgoing group at its 5.05 eV midpoint.
+The tally uses physical energy boundaries because particle energy remains in eV during hybrid transport.
+The example requires ``MCDC_LIB`` to identify a native-data library containing ``H1-293.6K.h5``.
+
+Full Input
+----------
+
+.. literalinclude:: ../../../examples/hybrid_multigroup/input.py
+   :language: python
+   :linenos:
+
+Post-processing
+---------------
+
+.. literalinclude:: ../../../examples/hybrid_multigroup/process-output.py
+   :language: python
+   :linenos:
+
+How to Run
+----------
+
+From inside ``examples/hybrid_multigroup``:
+
+.. code-block:: sh
+
+   python input.py
+   python process-output.py
+
+The transport calculation writes ``hybrid_multigroup.h5`` and the post-processing script writes ``hybrid_multigroup_flux.png``.
diff --git a/docs/source/examples/index.rst b/docs/source/examples/index.rst
index 0a0154c65..99719be5d 100644
--- a/docs/source/examples/index.rst
+++ b/docs/source/examples/index.rst
@@ -31,6 +31,7 @@ Basic Examples
    :maxdepth: 1
 
    slab_shielding
+   hybrid_multigroup
    iterative_source_reweighting
    kobayashi_dog_leg
    kobayashi_td
diff --git a/examples/hybrid_multigroup/hybrid_multigroup.h5 b/examples/hybrid_multigroup/hybrid_multigroup.h5
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diff --git a/examples/hybrid_multigroup/input.py b/examples/hybrid_multigroup/input.py
new file mode 100644
index 000000000..58dc2db47
--- /dev/null
+++ b/examples/hybrid_multigroup/input.py
@@ -0,0 +1,57 @@
+import numpy as np
+
+import mcdc
+
+simulation = mcdc.Simulation("Hybrid multigroup sphere")
+
+# Material with native H-1 data and a low-energy multigroup treatment
+# MCDC_LIB must contain H1-293.6K.h5.
+material = mcdc.Material(
+    nuclide_composition={"H1": 5.0e-2},
+    neutron_multigroup=mcdc.NeutronMultigroupData(
+        capture=np.array([0.2]),
+        scatter=np.array([[0.8]]),
+        speed=np.array([1.383e6]),
+        energy_grid=np.array([0.1, 10.0]),
+        energy_representation="midpoint",
+    ),
+)
+
+# Spherical domain
+boundary = mcdc.Surface.Sphere(radius=5.0, boundary_condition="vacuum")
+cell = mcdc.Cell(region=-boundary, fill=material)
+simulation.set_model([cell])
+
+# The low-energy source uses multigroup physics
+multigroup_source = mcdc.Source(
+    position=[0.0, 0.0, 1.0],
+    isotropic=True,
+    energy=1.0,
+    probability=0.5,
+)
+
+# The high-energy source lies outside the multigroup grid and uses native physics
+native_source = mcdc.Source(
+    position=[0.0, 0.0, -1.0],
+    isotropic=True,
+    energy=1.0e6,
+    probability=0.5,
+)
+simulation.set_sources([multigroup_source, native_source])
+
+# Hybrid tallies use physical energy boundaries in eV
+mesh = mcdc.MeshStructured(z=np.array([-5.0, 0.0, 5.0]))
+tally = mcdc.Tally(
+    name="hybrid_flux",
+    mesh=mesh,
+    particle_type="neutron",
+    energy=np.array([0.0, 0.1, 10.0, 1.0e5, 20.0e6]),
+    scores=["flux", "collision"],
+)
+simulation.set_tallies([tally])
+
+simulation.settings.N_particle = 1_000
+simulation.settings.N_batch = 5
+simulation.settings.output_name = "hybrid_multigroup"
+
+simulation.run()
diff --git a/examples/hybrid_multigroup/process-output.py b/examples/hybrid_multigroup/process-output.py
new file mode 100644
index 000000000..0b5316645
--- /dev/null
+++ b/examples/hybrid_multigroup/process-output.py
@@ -0,0 +1,29 @@
+import h5py
+import matplotlib.pyplot as plt
+import numpy as np
+
+with h5py.File("hybrid_multigroup.h5", "r") as output:
+    tally = output["tallies/hybrid_flux"]
+    z = tally["grid/z"][:]
+    energy = tally["grid/energy"][:]
+    flux = tally["flux/mean"][:]
+
+dz = z[1:] - z[:-1]
+z_midpoint = 0.5 * (z[:-1] + z[1:])
+flux = np.reshape(flux, (len(energy) - 1, len(z) - 1)) / dz
+
+figure, axis = plt.subplots()
+for index in range(len(energy) - 1):
+    axis.plot(
+        z_midpoint,
+        flux[index],
+        marker="o",
+        label=f"{energy[index]:.1e}–{energy[index + 1]:.1e} eV",
+    )
+
+axis.set_xlabel("z [cm]")
+axis.set_ylabel("Flux")
+axis.grid()
+axis.legend()
+figure.tight_layout()
+figure.savefig("hybrid_multigroup_flux.png", dpi=150)
diff --git a/test/regression/hybrid_multigroup/answer.h5 b/test/regression/hybrid_multigroup/answer.h5
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diff --git a/test/regression/hybrid_multigroup/input.py b/test/regression/hybrid_multigroup/input.py
new file mode 100644
index 000000000..d3a8e1198
--- /dev/null
+++ b/test/regression/hybrid_multigroup/input.py
@@ -0,0 +1,53 @@
+import numpy as np
+import os
+
+import mcdc
+
+os.environ["MCDC_LIB"] = "../mcdc-regression_test_data/"
+
+simulation = mcdc.Simulation("Hybrid multigroup regression")
+
+# Native composition combined with multigroup data selects hybrid transport
+material = mcdc.Material(
+    nuclide_composition={"H1": 5.0e-2},
+    neutron_multigroup=mcdc.NeutronMultigroupData(
+        capture=np.array([0.2]),
+        scatter=np.array([[0.8]]),
+        speed=np.array([1.383e6]),
+        energy_grid=np.array([0.1, 10.0]),
+        energy_representation="midpoint",
+    ),
+)
+
+boundary = mcdc.Surface.Sphere(radius=5.0, boundary_condition="vacuum")
+cell = mcdc.Cell(region=-boundary, fill=material)
+simulation.set_model([cell])
+
+multigroup_source = mcdc.Source(
+    position=[0.0, 0.0, 1.0],
+    isotropic=True,
+    energy=1.0,
+    probability=0.5,
+)
+native_source = mcdc.Source(
+    position=[0.0, 0.0, -1.0],
+    isotropic=True,
+    energy=1.0e6,
+    probability=0.5,
+)
+simulation.set_sources([multigroup_source, native_source])
+
+mesh = mcdc.MeshStructured(z=np.array([-5.0, 0.0, 5.0]))
+tally = mcdc.Tally(
+    name="hybrid_flux",
+    mesh=mesh,
+    particle_type="neutron",
+    energy=np.array([0.0, 0.1, 10.0, 1.0e5, 20.0e6]),
+    scores=["flux", "collision"],
+)
+simulation.set_tallies([tally])
+
+simulation.settings.N_particle = 40
+simulation.settings.N_batch = 2
+
+simulation.run()

From 0df0ce448bc1d618d4b7433446f8919cef307b97 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 10 Aug 2026 13:30:34 +0700
Subject: [PATCH 168/202] exclude examples that need library in unit tests

---
 test/unit/test_example_inputs.py | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/test/unit/test_example_inputs.py b/test/unit/test_example_inputs.py
index 5eb7475e3..d6c75ee13 100644
--- a/test/unit/test_example_inputs.py
+++ b/test/unit/test_example_inputs.py
@@ -6,7 +6,14 @@
 import mcdc
 
 EXAMPLES_ROOT = Path(__file__).parents[2] / "examples"
-EXAMPLE_INPUTS = tuple(sorted(EXAMPLES_ROOT.glob("**/input.py")))
+EXCLUDED_EXAMPLES = ["hybrid_multigroup"]
+
+# Leave data-library-dependent examples to regression testing
+EXAMPLE_INPUTS = tuple(
+    input_path
+    for input_path in sorted(EXAMPLES_ROOT.glob("**/input.py"))
+    if input_path.parent.name not in EXCLUDED_EXAMPLES
+)
 assert EXAMPLE_INPUTS, "No example inputs found"
 
 

From 1923a09c90eecbb1bb45cc9f4e2f93d11d3f0fcf Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 10 Aug 2026 13:32:29 +0700
Subject: [PATCH 169/202] debug bank printer

---
 mcdc/print_.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/mcdc/print_.py b/mcdc/print_.py
index 42c70594d..17d319bf9 100644
--- a/mcdc/print_.py
+++ b/mcdc/print_.py
@@ -63,7 +63,7 @@ def print_bank(bank, show_content=False):
     """Print summary information for a particle bank."""
     size_field = bank["size"]
     size = int(size_field[0]) if getattr(size_field, "ndim", 0) else int(size_field)
-    particles = bank["particles"]
+    particles = bank["particle_data"]
 
     print("\n=============")
     print("Particle bank")

From d650dff2d49be5eb1d1269a78ec71314634f7260 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 10 Aug 2026 14:55:43 +0700
Subject: [PATCH 170/202] update release policy

---
 docs/source/project/release_policy.rst | 23 +++++++++--------------
 1 file changed, 9 insertions(+), 14 deletions(-)

diff --git a/docs/source/project/release_policy.rst b/docs/source/project/release_policy.rst
index fbca4dc08..4241bbb34 100644
--- a/docs/source/project/release_policy.rst
+++ b/docs/source/project/release_policy.rst
@@ -4,27 +4,22 @@
 Release Policy
 ==============
 
-MC/DC follows `Semantic Versioning <https://semver.org/>`_ and maintains a
-human-readable release history in
-`CHANGELOG.md <https://github.com/mcdc-project/mcdc/blob/dev/CHANGELOG.md>`_.
+MC/DC follows `Semantic Versioning <https://semver.org/>`_ and maintains a human-readable release history in `CHANGELOG.md <https://github.com/mcdc-project/mcdc/blob/dev/CHANGELOG.md>`_.
 
 Minor Releases
 --------------
 
-MC/DC plans a minor release each month. These releases collect compatible
-features, improvements, and fixes that have passed the project's required
-review and validation.
+MC/DC plans one minor release each calendar quarter.
+These releases collect compatible features, improvements, and fixes that have passed the project's required review and validation.
+For planning convenience, the four release cycles may be referred to informally as winter (Dec-Feb), spring (Mar-May), summer (Jun-Aug), and autumn (Sep-Nov) releases.
 
-The monthly schedule is a target rather than a reason to release unverified
-work. A release may be delayed when additional testing, documentation, or
-integration work is needed.
+The quarterly schedule is a target rather than a reason to release unverified work.
+A minor release may be delayed when additional testing, documentation, or integration work is needed; it may also be brought forward when the accumulated changes are substantial and users would benefit from earlier availability.
 
 Patch Releases
 --------------
 
-Bug fixes are not held until the next monthly minor release. Once a fix has
-passed review and the relevant validation and release checks, MC/DC publishes
-a patch release as soon as practical.
+Bug fixes are not held until the next quarterly minor release.
+Once a fix has passed review and the relevant validation and release checks, MC/DC publishes a patch release as soon as practical.
 
-Published versions and release notes are available from the
-`MC/DC releases page <https://github.com/mcdc-project/mcdc/releases>`_.
+Published versions and release notes are available from the `MC/DC releases page <https://github.com/mcdc-project/mcdc/releases>`_.

From 132d0c9aad260c08674935601f136f7ca1788b72 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Mon, 10 Aug 2026 15:03:38 +0700
Subject: [PATCH 171/202] remove legacy items

---
 install.sh | 45 ---------------------------------------------
 1 file changed, 45 deletions(-)
 delete mode 100755 install.sh

diff --git a/install.sh b/install.sh
deleted file mode 100755
index 23ae2f8ed..000000000
--- a/install.sh
+++ /dev/null
@@ -1,45 +0,0 @@
-#!/bin/bash
-
-# Check python version
-if ! { python3 -c 'import sys; assert sys.version_info < (3,12)' > /dev/null 2>&1 && python3 -c 'import sys; assert sys.version_info >= (3,9)' > /dev/null 2>&1; }; then
-  v=$(python3 --version)
-  p=$(which python)
-  echo "ERROR: Python version must be < 3.12 and >= 3.9."
-  echo "    Found $v at $p."
-  echo "ERROR: Installation failed."
-  exit 1
-fi
-
-# Install or build mpi4py
-if [ $# -eq 0 ]; then
-  conda install mpi4py <<< "y"
-fi
-while [ $# -gt 0 ]; do
-  case $1 in
-    --hpc)
-      # Rename legacy compiler option in conda
-      s=$(which python)
-      s=${s//bin\/python/compiler_compat}
-
-      if [ ! -f $s/ld.bak ] && [ -f $s/ld ]; then
-        mv $s/ld $s/ld.bak
-      fi
-
-      mkdir installs; cd installs
-      wget https://github.com/mpi4py/mpi4py/releases/download/3.1.4/mpi4py-3.1.4.tar.gz -q
-      tar -zxf mpi4py-3.1.4.tar.gz
-      cd mpi4py-3.1.4
-      python setup.py install
-      cd ../../
-      rm -rf installs/
-      ;;
-
-  esac
-  shift
-done
-
-# Install MC/DC module (and the dependencies)
-pip install -e .
-
-# Install pre-commit hook
-pre-commit install

From e8de880443a1054f9b47d61a7ba7c4e19aec855b Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 09:56:38 +0700
Subject: [PATCH 172/202] update front matters

---
 CITATION.cff |  2 +-
 README.md    | 56 +++++++++++++++++-----------------------------------
 2 files changed, 19 insertions(+), 39 deletions(-)

diff --git a/CITATION.cff b/CITATION.cff
index d5c8846cf..a86cffad3 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -17,7 +17,7 @@ identifiers:
     value: 10.21105/joss.06415
     description: MC/DC JOSS Article
 repository-code: 'https://github.com/mcdc-project/mcdc'
-url: 'https://mcdc.readthedocs.io/en/latest/'
+url: 'https://mcdc.readthedocs.io/en/stable/'
 abstract: >-
   MC/DC is an open-source, Python-based Monte Carlo
   radiation transport code that
diff --git a/README.md b/README.md
index 045efa334..adeb2847d 100644
--- a/README.md
+++ b/README.md
@@ -2,30 +2,25 @@
 
 ![MC/DC logo](https://raw.githubusercontent.com/mcdc-project/mcdc/main/assets/mcdc-logo.svg)
 
-[![Build](https://github.com/mcdc-project/mcdc/actions/workflows/regression_test.yml/badge.svg)](https://github.com/mcdc-project/mcdc/actions/workflows/regression_test.yml)
+[![Unit Tests](https://github.com/mcdc-project/mcdc/actions/workflows/unit_test.yml/badge.svg)](https://github.com/mcdc-project/mcdc/actions/workflows/unit_test.yml)
+[![Regression Tests](https://github.com/mcdc-project/mcdc/actions/workflows/regression_test.yml/badge.svg)](https://github.com/mcdc-project/mcdc/actions/workflows/regression_test.yml)
 [![Docker Build, Test, and Publish](https://github.com/mcdc-project/mcdc/actions/workflows/docker.yml/badge.svg)](https://github.com/mcdc-project/mcdc/actions/workflows/docker.yml)
-[![Read the Docs](https://github.com/mcdc-project/mcdc/actions/workflows/docs_test.yml/badge.svg)](https://mcdc.readthedocs.io/)
+[![Documentation Build](https://github.com/mcdc-project/mcdc/actions/workflows/docs_test.yml/badge.svg)](https://mcdc.readthedocs.io/)
 [![PyPI](https://img.shields.io/pypi/v/mcdc.svg)](https://pypi.org/project/mcdc/)
 [![DOI](https://joss.theoj.org/papers/10.21105/joss.06415/status.svg)](https://doi.org/10.21105/joss.06415)
 [![License](https://img.shields.io/badge/License-BSD_3--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
 
-MC/DC is an open-source, Python-based Monte Carlo radiation transport code that
-combines rapid methods development with scalable, high-performance execution on
-modern computing systems. Originally initiated by the Center for Exascale
-Monte Carlo Neutron Transport ([CEMeNT](https://cement-psaap.github.io/)), MC/DC
-development is now led by the Center for Advancing the Radiation Resilience of
-Electronics ([CARRE](https://carre-psaapiv.org/)).
+MC/DC is an open-source, Python-based Monte Carlo radiation transport code that combines rapid methods development with scalable, high-performance execution on modern computing systems.
+Originally initiated by the Center for Exascale Monte Carlo Neutron Transport ([CEMeNT](https://cement-psaap.github.io/)), MC/DC development is now led by the Center for Advancing the Radiation Resilience of Electronics ([CARRE](https://carre-psaapiv.org/)).
 
 ## Features
 
-- Monte Carlo neutron transport (with photon and charged-particle capabilities
-  under development)
+- Monte Carlo neutron transport, with photon and charged-particle transport and coupled multi-particle capabilities under development
 - Time-dependent, steady-state, and eigenvalue simulations
-- Multiple physics fidelities (continuous-energy/multi-group,
-  single-scattering/condensed-history)
+- Multiple physics fidelities (e.g., continuous-energy and multigroup neutron transport, with single-scattering and condensed-history charged-particle transport under development)
 - Distributed-memory parallel execution with MPI
 - Machine-portable Python implementation accelerated by Numba JIT compilation
-- Extensible architecture for rapid methods development and prototyping
+- Extensible architecture for prototyping new transport methods
 
 ## Installation
 
@@ -35,39 +30,24 @@ Install the latest stable release from PyPI:
 pip install mcdc
 ```
 
-For development installation and additional options, see the
-[Installation Guide](https://mcdc.readthedocs.io/en/latest/user_guide/getting_started/installation.html).
+For development installation and additional options, see the [Installation Guide](https://mcdc.readthedocs.io/en/dev/user_guide/getting_started/installation.html).
 
 ## Documentation
 
-Complete documentation is available on
-[Read the Docs](https://mcdc.readthedocs.io/), including:
+Complete documentation is available on [Read the Docs](https://mcdc.readthedocs.io/), including:
 
-- [User Guide](https://mcdc.readthedocs.io/en/latest/user_guide/index.html)
-- [Getting Started](https://mcdc.readthedocs.io/en/latest/user_guide/getting_started/index.html)
-- [API Reference](https://mcdc.readthedocs.io/en/latest/reference/python_api/index.html)
-- [Developer Guide](https://mcdc.readthedocs.io/en/latest/developer_guide/index.html)
-- [Contributing](https://mcdc.readthedocs.io/en/latest/contributing/index.html)
+- [User Guide](https://mcdc.readthedocs.io/en/dev/user_guide/index.html)
+- [Getting Started](https://mcdc.readthedocs.io/en/dev/user_guide/getting_started/index.html)
+- [API Reference](https://mcdc.readthedocs.io/en/dev/reference/python_api/index.html)
+- [Developer Guide](https://mcdc.readthedocs.io/en/dev/developer_guide/index.html)
+- [Contributing](https://mcdc.readthedocs.io/en/dev/contributing/index.html)
 
 ## Citing
 
-If you use MC/DC in published work, please cite one or more of the following
-references as appropriate:
+If you use MC/DC in published work, please cite the following article:
 
-- **MC/DC Origins**
-  I. Variansyah, et al. (2023). *Development of MC/DC: a performant,
-  scalable, and portable Python-based Monte Carlo neutron transport code.*
-  Proceedings of the ANS Mathematics & Computation Conference 2023,
-  Niagara Falls, Canada.
-  https://doi.org/10.48550/arXiv.2305.07636
-
-- **MC/DC JOSS Article**
-  J. Morgan, et al. (2024). *Monte Carlo / Dynamic Code (MC/DC): An
-  accelerated Python package for fully transient neutron transport and rapid
-  methods development.* Journal of Open Source Software, **9**(96), 6415.
-  https://doi.org/10.21105/joss.06415
+- J. P. Morgan et al. (2024). [*Monte Carlo / Dynamic Code (MC/DC): An accelerated Python package for fully transient neutron transport and rapid methods development*](https://doi.org/10.21105/joss.06415). *Journal of Open Source Software*, **9**(96), 6415.
 
 ## Reporting Bugs and Issues
 
-To report bugs, request features, or ask questions, please open a
-[GitHub Issue](https://github.com/mcdc-project/mcdc/issues).
+To report bugs, request features, or ask questions, please open a [GitHub Issue](https://github.com/mcdc-project/mcdc/issues).

From 143990ab2fdf35166e266b03aba54d504b47b141 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 10:02:48 +0700
Subject: [PATCH 173/202] update version banner in docs

---
 docs/source/_static/switcher.json | 7 +------
 docs/source/conf.py               | 7 ++++---
 2 files changed, 5 insertions(+), 9 deletions(-)

diff --git a/docs/source/_static/switcher.json b/docs/source/_static/switcher.json
index 3460b9166..00f7e0216 100644
--- a/docs/source/_static/switcher.json
+++ b/docs/source/_static/switcher.json
@@ -5,12 +5,7 @@
     "url": "https://mcdc.readthedocs.io/en/dev/"
   },
   {
-    "name": "latest",
-    "version": "latest",
-    "url": "https://mcdc.readthedocs.io/en/latest/"
-  },
-  {
-    "name": "stable",
+    "name": "0.15 (stable)",
     "version": "stable",
     "url": "https://mcdc.readthedocs.io/en/stable/",
     "preferred": true
diff --git a/docs/source/conf.py b/docs/source/conf.py
index 77980240d..b57a386e1 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -67,7 +67,7 @@
 # development docs as the local-build default.
 docs_version = os.environ.get("READTHEDOCS_VERSION", "dev")
 switcher_json_url = (
-    "https://mcdc.readthedocs.io/en/latest/_static/switcher.json"
+    "https://mcdc.readthedocs.io/en/dev/_static/switcher.json"
     if os.environ.get("READTHEDOCS") == "True"
     else "/_static/switcher.json"
 )
@@ -84,8 +84,9 @@
         "json_url": switcher_json_url,
         "version_match": docs_version,
     },
-    # Hosted builds share one version list from the latest documentation. Local
-    # builds use the copied static file when served from the HTML output root.
+    "show_version_warning_banner": docs_version != "stable",
+    # Hosted builds share one version list from the development documentation.
+    # Local builds use the copied static file when served from the HTML output root.
     "check_switcher": False,
     "logo": {
         "alt_text": "MC/DC Documentation - Home",

From d9249166a46cb80ab072736323d771f87511872d Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 10:22:43 +0700
Subject: [PATCH 174/202] update pyproject

---
 pyproject.toml | 22 +++-------------------
 1 file changed, 3 insertions(+), 19 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 4a7ca903a..07512bbc4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,31 +10,16 @@ authors = [
   { name = "MC/DC Development Team" },
 ]
 
-maintainers = [
-  { name = "Ilham Variansyah", email = "variansi@oregonstate.edu" },
-  { name = "Joanna Piper Morgan", email = "morgan83@llnl.gov" },
-  { name = "Melek Derman", email = "dermanm@oregonstate.edu" },
-  { name = "Nathan Glaser", email = "glaserna@oregonstate.edu" },
-  { name = "Massimo Larsen", email = "larsemas@oregonstate.edu" },
-  { name = "Braxton Cuneo", email = "bcuneo@seattleu.edu" },
-  { name = "Kyle E. Niemeyer", email = "kyle.niemeyer@oregonstate.edu" },
-  { name = "Madicken Munk", email = "madicken.munk@oregonstate.edu" },
-]
-
-description = "A performant, scalable, and machine-portable Monte Carlo radiation transport code."
+description = "A performant, scalable, and machine-portable Python-based Monte Carlo radiation transport code."
 readme = "README.md"
 requires-python = ">=3.10"
 license = { file = "LICENSE" }
 
 keywords = [
   "monte carlo",
+  "nuclear engineering",
+  "particle transport",
   "radiation transport",
-  "neutron transport",
-  "high-performance computing",
-  "hpc",
-  "gpu",
-  "numba",
-  "mpi",
 ]
 
 classifiers = [
@@ -66,7 +51,6 @@ classifiers = [
 dependencies = [
   "numba>=0.60.0",
   "numpy>=2.0.0",
-  "scipy",
   "matplotlib",
   "mpi4py>=3.1.4",
   "h5py",

From a415e737ba4dc39b4f24d56b6f4d2360c097bbb5 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 10:25:21 +0700
Subject: [PATCH 175/202] update pyproject

---
 pyproject.toml | 10 +++-------
 1 file changed, 3 insertions(+), 7 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 07512bbc4..091b8f517 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,7 +13,8 @@ authors = [
 description = "A performant, scalable, and machine-portable Python-based Monte Carlo radiation transport code."
 readme = "README.md"
 requires-python = ">=3.10"
-license = { file = "LICENSE" }
+license = "BSD-3-Clause"
+license-files = ["LICENSE"]
 
 keywords = [
   "monte carlo",
@@ -38,8 +39,6 @@ classifiers = [
   "Programming Language :: Python :: 3.12",
   "Programming Language :: Python :: 3.13",
 
-  "License :: OSI Approved :: BSD License",
-
   "Operating System :: MacOS",
   "Operating System :: POSIX :: Linux",
 
@@ -73,7 +72,7 @@ dev = [
 
 [project.urls]
 Homepage = "https://mcdc.readthedocs.io/"
-Documentation = "https://mcdc.readthedocs.io/"
+Documentation = "https://mcdc.readthedocs.io/en/stable/"
 Repository = "https://github.com/mcdc-project/mcdc"
 Issues = "https://github.com/mcdc-project/mcdc/issues"
 "Release Notes" = "https://github.com/mcdc-project/mcdc/releases"
@@ -81,9 +80,6 @@ Issues = "https://github.com/mcdc-project/mcdc/issues"
 [tool.hatch.version]
 source = "vcs"
 
-[tool.hatch.build.hooks.vcs]
-version-file = "mcdc/_version.py"
-
 [tool.black]
 force-exclude = '''
 (

From e1ee08793cb1d07d159d380a59a073aabfc33d1b Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 11:30:37 +0700
Subject: [PATCH 176/202] update typing on API

---
 mcdc/__init__.py          | 39 +++++++++++++++++++++++-----------
 mcdc/object_/base.py      |  4 ++--
 mcdc/object_/cell.py      | 16 +++++++-------
 mcdc/object_/mesh.py      | 10 ++++-----
 mcdc/object_/settings.py  |  8 +++----
 mcdc/object_/source.py    |  6 +++---
 mcdc/object_/surface.py   | 44 +++++++++++++++++++--------------------
 mcdc/object_/tally.py     | 16 +++++++-------
 mcdc/object_/technique.py | 26 ++++++++++++-----------
 mcdc/object_/universe.py  |  8 +++----
 10 files changed, 97 insertions(+), 80 deletions(-)

diff --git a/mcdc/__init__.py b/mcdc/__init__.py
index d18a80402..603e69feb 100644
--- a/mcdc/__init__.py
+++ b/mcdc/__init__.py
@@ -1,19 +1,34 @@
-from importlib.metadata import PackageNotFoundError, version
+"""Public Python interface for MC/DC."""
 
-try:
-    __version__ = version("mcdc")
-except PackageNotFoundError:
-    __version__ = "unknown"
-
-# ======================================================================================
-# Simulation building blocks
-# ======================================================================================
+from importlib.metadata import PackageNotFoundError as _PackageNotFoundError
+from importlib.metadata import version as _version
 
-from mcdc.object_.cell import Cell, Universe, Lattice
+from mcdc.object_.cell import Cell
 from mcdc.object_.material import Material
-from mcdc.object_.transport_model_data import NeutronMultigroupData
-from mcdc.object_.mesh import MeshUniform, MeshStructured
+from mcdc.object_.mesh import MeshStructured, MeshUniform
 from mcdc.object_.simulation import Simulation
 from mcdc.object_.source import Source
 from mcdc.object_.surface import Surface
 from mcdc.object_.tally import Tally
+from mcdc.object_.transport_model_data import NeutronMultigroupData
+from mcdc.object_.universe import Lattice, Universe
+
+__all__ = [
+    "__version__",
+    "Cell",
+    "Lattice",
+    "Material",
+    "MeshStructured",
+    "MeshUniform",
+    "NeutronMultigroupData",
+    "Simulation",
+    "Source",
+    "Surface",
+    "Tally",
+    "Universe",
+]
+
+try:
+    __version__: str = _version("mcdc")
+except _PackageNotFoundError:
+    __version__ = "unknown"
diff --git a/mcdc/object_/base.py b/mcdc/object_/base.py
index ab466ffeb..4845148bd 100644
--- a/mcdc/object_/base.py
+++ b/mcdc/object_/base.py
@@ -101,7 +101,7 @@ class MCDCObject(MCDCBase):
 
     ID: int
 
-    def __init__(self):
+    def __init__(self) -> None:
         # Initialize the object as unregistered
         self.ID = -1
 
@@ -151,7 +151,7 @@ def __init_subclass__(cls):
                 f"MC/DC class '{cls.__name__}' must have 'sub_type' class attribute."
             )
 
-    def __init__(self):
+    def __init__(self) -> None:
         # Initialize common object registration state
         super().__init__()
 
diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index 67825623f..a184181a8 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -52,13 +52,13 @@ class Region:
     A: Surface | Region | NoneType
     B: Region | int | NoneType
 
-    def __init__(self, type_, A, B):
+    def __init__(self, type_, A, B) -> None:
         self.type = type_
         self.A = A
         self.B = B
 
     @classmethod
-    def make_halfspace(cls, surface, sense):
+    def make_halfspace(cls, surface, sense) -> Region:
         """Create the positive or negative half-space of a surface.
 
         Parameters
@@ -77,16 +77,16 @@ def make_halfspace(cls, surface, sense):
         region = Region("halfspace", surface, sense)
         return region
 
-    def __and__(self, other):
+    def __and__(self, other) -> Region:
         return Region("intersection", self, other)
 
-    def __or__(self, other):
+    def __or__(self, other) -> Region:
         return Region("union", self, other)
 
-    def __invert__(self):
+    def __invert__(self) -> Region:
         return Region("complement", self, None)
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         return f"{str.capitalize(self.type)} Region"
 
 
@@ -192,7 +192,7 @@ def __init__(
         name: str = "",
         translation: Sequence[float] = [0.0, 0.0, 0.0],
         rotation: Sequence[float] = [0.0, 0.0, 0.0],
-    ):
+    ) -> None:
         super().__init__()
 
         self.name = name or "(Unnamed cell)"
@@ -252,7 +252,7 @@ def _compile_into_simulation(self, simulation) -> bool:
 
         return True
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
 
         text += f"  - Name: {self.name}\n"
diff --git a/mcdc/object_/mesh.py b/mcdc/object_/mesh.py
index fde373205..b2ed3779d 100644
--- a/mcdc/object_/mesh.py
+++ b/mcdc/object_/mesh.py
@@ -34,7 +34,7 @@ def __init__(self, name: str) -> None:
         self.name = name or "(Unnamed mesh)"
         self.N_bin = 0
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
 
         text += f"  - Name: {self.name}\n"
@@ -101,7 +101,7 @@ def __init__(
         x: tuple[float, float, int] = (-INF, 2 * INF, 1),
         y: tuple[float, float, int] = (-INF, 2 * INF, 1),
         z: tuple[float, float, int] = (-INF, 2 * INF, 1),
-    ):
+    ) -> None:
         super().__init__(
             name,
         )
@@ -119,7 +119,7 @@ def __init__(
 
         self.N_bin = self.Nx * self.Ny * self.Nz
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
         text += f"  - Grid specification\n"
         text += f"    - (x0, dx, Nx): ({self.x0}, {self.dx}, {self.Nx}) [cm]\n"
@@ -182,7 +182,7 @@ def __init__(
         x: Sequence[float] | NDArray[float64] = np.array([-INF, INF]),
         y: Sequence[float] | NDArray[float64] = np.array([-INF, INF]),
         z: Sequence[float] | NDArray[float64] = np.array([-INF, INF]),
-    ):
+    ) -> None:
         super().__init__(name)
 
         # Set the grid
@@ -196,7 +196,7 @@ def __init__(
 
         self.N_bin = self.Nx * self.Ny * self.Nz
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
         text += f"  - Grid specification\n"
         text += f"    - x {print_1d_array(self.x)} cm\n"
diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index 5665f6442..4b8e2f859 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -90,7 +90,7 @@ class Settings(MCDCBase):
     gpu_async_type: int = GPU_ASYNC_SIMPLE
     gpu_storage: int = GPU_STORAGE_SEPARATE
 
-    def set_time_census(self, time, tally_frequency=None):
+    def set_time_census(self, time, tally_frequency=None) -> None:
         """Configure census times for time-dependent transport.
 
         Parameters
@@ -147,7 +147,7 @@ def set_eigenmode(
         k_init=1.0,
         gyration_radius=None,
         save_particle=False,
-    ):
+    ) -> None:
         """Enable neutron k-eigenvalue mode.
 
         Parameters
@@ -214,7 +214,7 @@ def set_eigenmode(
             else:
                 print_error("Unknown gyration radius type")
 
-    def set_source_file(self, source_file_name):
+    def set_source_file(self, source_file_name) -> None:
         """Use particles from an HDF5 source file.
 
         The particle count is read from the file's ``particles_size`` dataset.
@@ -239,7 +239,7 @@ def set_source_file(self, source_file_name):
         with h5py.File(source_file_name, "r") as f:
             self.N_particle = int(f["particles_size"][()])
 
-    def set_transported_particles(self, transported_particles: List[str]):
+    def set_transported_particles(self, transported_particles: List[str]) -> None:
         """Select the particle species enabled during transport.
 
         Parameters
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index fdd24b100..04ffbfca6 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -254,7 +254,7 @@ def __init__(
         particle_type: str = "neutron",
         #
         probability: float = 1.0,
-    ):
+    ) -> None:
         super().__init__()
 
         self.name = name or "(Unnamed source)"
@@ -410,7 +410,7 @@ def __init__(
         self.move_time_grid = np.array([0.0, INF])
         self.move_translations = np.zeros((2, 3))
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
 
         text += f"  - Name: {self.name}\n"
@@ -447,7 +447,7 @@ def __repr__(self):
     # Source moving
     # ==================================================================================
 
-    def move(self, velocities, durations):
+    def move(self, velocities, durations) -> None:
         """
         Define piecewise-constant motion for the source.
 
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 343c38174..3fafaccd7 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -128,7 +128,7 @@ class Surface(MCDCObject):
     move_translations: Annotated[NDArray[float64], ("N_move_grid", 3)]
     surface_crossing_tallies: list[TallySurfaceCrossing]
 
-    def __init__(self, type_, name, boundary_condition):
+    def __init__(self, type_, name, boundary_condition) -> None:
         super().__init__()
 
         self.type = type_
@@ -180,7 +180,7 @@ def __init__(self, type_, name, boundary_condition):
         # Surface-crossing tallies
         self.surface_crossing_tallies = []
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
 
         text += f"  - Name: {self.name}\n"
@@ -284,7 +284,7 @@ def PlaneX(
         name: str = "",
         x: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create the plane ``x = constant``.
 
         Parameters
@@ -315,7 +315,7 @@ def PlaneY(
         name: str = "",
         y: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create the plane ``y = constant``.
 
         Parameters are the surface ``name``, position ``y`` in cm, and a
@@ -341,7 +341,7 @@ def PlaneZ(
         name: str = "",
         z: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create the plane ``z = constant``.
 
         Parameters are the surface ``name``, position ``z`` in cm, and a
@@ -370,7 +370,7 @@ def Plane(
         C: float = 0.0,
         D: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create a general plane ``A*x + B*y + C*z + D = 0``.
 
         The coefficients are normalized internally. ``(A, B, C)`` must be a
@@ -410,7 +410,7 @@ def CylinderX(
         center: Sequence[float] = [0.0, 0.0],
         radius: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create an infinite cylinder parallel to the x axis.
 
         ``center`` gives ``[y, z]`` in cm and ``radius`` is in cm.
@@ -441,7 +441,7 @@ def CylinderY(
         center: Sequence[float] = [0.0, 0.0],
         radius: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create an infinite cylinder parallel to the y axis.
 
         ``center`` gives ``[x, z]`` in cm and ``radius`` is in cm.
@@ -472,7 +472,7 @@ def CylinderZ(
         center: Sequence[float] = [0.0, 0.0],
         radius: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create an infinite cylinder parallel to the z axis.
 
         ``center`` gives ``[x, y]`` in cm and ``radius`` is in cm.
@@ -505,7 +505,7 @@ def Cylinder(
         axis: Sequence[float] = [0.0, 0.0, 1.0],
         point: Sequence[float] = [0.0, 0.0, 0.0],
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create an infinite cylinder with an arbitrary axis.
 
         Parameters
@@ -556,7 +556,7 @@ def Sphere(
         center: Sequence[float] = [0.0, 0.0, 0.0],
         radius: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create a sphere from its center and radius in cm."""
         type_ = SURFACE_SPHERE
         surface = cls(type_, name, boundary_condition)
@@ -586,7 +586,7 @@ def ConeX(
         apex: Sequence[float] = [0.0, 0.0, 0.0],
         t_sq: float = 1.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create a double cone aligned with the x axis.
 
         ``apex`` is in cm and ``t_sq`` is the squared tangent of the opening
@@ -618,7 +618,7 @@ def ConeY(
         apex: Sequence[float] = [0.0, 0.0, 0.0],
         t_sq: float = 1.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create a double cone aligned with the y axis.
 
         ``apex`` is in cm and ``t_sq`` is the squared tangent of the opening
@@ -650,7 +650,7 @@ def ConeZ(
         apex: Sequence[float] = [0.0, 0.0, 0.0],
         t_sq: float = 1.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create a double cone aligned with the z axis.
 
         ``apex`` is in cm and ``t_sq`` is the squared tangent of the opening
@@ -690,7 +690,7 @@ def Quadric(
         I: float = 0.0,
         J: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create a general second-degree surface.
 
         The coefficients define
@@ -728,7 +728,7 @@ def TorusX(
         R: float = 0.0,
         r: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create a torus centered at ``(A, B, C)`` and aligned with x.
 
         ``(A, B, C)`` gives the center in cm. ``R`` is the major radius and
@@ -760,7 +760,7 @@ def TorusY(
         R: float = 0.0,
         r: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create a torus centered at ``(A, B, C)`` and aligned with y.
 
         ``(A, B, C)`` gives the center in cm. ``R`` is the major radius and
@@ -792,7 +792,7 @@ def TorusZ(
         R: float = 0.0,
         r: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create a torus centered at ``(A, B, C)`` and aligned with z.
 
         ``(A, B, C)`` gives the center in cm. ``R`` is the major radius and
@@ -823,7 +823,7 @@ def Torus(
         R: float = 0.0,
         r: float = 0.0,
         boundary_condition: str = "none",
-    ):
+    ) -> "Surface":
         """Create a torus with an arbitrary axis.
 
         Parameters
@@ -867,17 +867,17 @@ def Torus(
     # Region building
     # ==================================================================================
 
-    def __pos__(self):
+    def __pos__(self) -> Region:
         return Region.make_halfspace(self, +1)
 
-    def __neg__(self):
+    def __neg__(self) -> Region:
         return Region.make_halfspace(self, -1)
 
     # ==================================================================================
     # Surface moving
     # ==================================================================================
 
-    def move(self, velocities, durations):
+    def move(self, velocities, durations) -> None:
         """Define piecewise-constant translational motion.
 
         Parameters
diff --git a/mcdc/object_/tally.py b/mcdc/object_/tally.py
index 9fe27bb87..91717b7f3 100644
--- a/mcdc/object_/tally.py
+++ b/mcdc/object_/tally.py
@@ -277,7 +277,7 @@ def __init__(
         energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
         spatial_shape: tuple[int, ...] | NoneType = None,
-    ):
+    ) -> None:
         super().__init__()
 
         # Set name
@@ -445,7 +445,7 @@ def _resolve_energy_filter(self, simulation) -> None:
             shape[2] = G
             self._set_bin_shape_and_strides(tuple(shape))
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
 
         text += f"  - Name: {self.name}\n"
@@ -515,7 +515,7 @@ def __init__(
         particle_type: str | NoneType = None,
         energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
-    ):
+    ) -> None:
         super().__init__(
             name,
             scores,
@@ -575,7 +575,7 @@ def _compile_into_simulation(self, simulation) -> bool:
 
         return True
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
 
         if isinstance(self.surface, Surface):
@@ -630,7 +630,7 @@ def __init__(
         particle_type: str | NoneType = None,
         energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
-    ):
+    ) -> None:
         spatial_shape = None
         if mesh is not None:
             spatial_shape = (mesh.Nx, mesh.Ny, mesh.Nz)
@@ -706,7 +706,7 @@ def _compile_into_simulation(self, simulation) -> bool:
 
         return True
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
         if self.cell:
             text += f"  - Cell filter: {self.cell.name}\n"
@@ -760,7 +760,7 @@ def __init__(
         particle_type: str | NoneType = None,
         energy: Sequence[float] | str | NoneType = None,
         time: Sequence[float] | NoneType = None,
-    ):
+    ) -> None:
         spatial_shape = None
         if mesh is not None:
             spatial_shape = (mesh.Nx, mesh.Ny, mesh.Nz)
@@ -836,7 +836,7 @@ def _compile_into_simulation(self, simulation) -> bool:
 
         return True
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
 
         if self.cell:
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index 59b7d56e1..b025b3ede 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -20,7 +20,7 @@ class NeutronMultigroup(MCDCBase):
 
     hybrid: bool  # Whether neutron multigroup transport is hybrid
 
-    def __init__(self):
+    def __init__(self) -> None:
         self.hybrid = True
 
 
@@ -37,10 +37,10 @@ class ImplicitCapture(MCDCBase):
 
     active: bool
 
-    def __init__(self):
+    def __init__(self) -> None:
         self.active = False
 
-    def __call__(self, active: bool = True):
+    def __call__(self, active: bool = True) -> None:
         """Configure implicit capture.
 
         Parameters
@@ -77,11 +77,11 @@ class WeightedEmission(MCDCBase):
     active: bool
     weight_target: float
 
-    def __init__(self):
+    def __init__(self) -> None:
         self.active = False
         self.weight_target = 0.0
 
-    def __call__(self, active: bool = True, weight_target: float = 1.0):
+    def __call__(self, active: bool = True, weight_target: float = 1.0) -> None:
         """Configure weighted emission.
 
         Parameters
@@ -126,12 +126,14 @@ class GlobalWeightRoulette(MCDCBase):
     weight_threshold: float
     weight_target: float
 
-    def __init__(self):
+    def __init__(self) -> None:
         self.active = False
         self.weight_threshold = 0.0
         self.weight_target = 1.0
 
-    def __call__(self, weight_threshold: float = 0.0, weight_target: float = 1.0):
+    def __call__(
+        self, weight_threshold: float = 0.0, weight_target: float = 1.0
+    ) -> None:
         """Enable roulette below a global weight threshold.
 
         Parameters
@@ -197,7 +199,7 @@ class WeightWindows(MCDCBase):
     target_weights: Annotated[NDArray[np.float64], ("Ne", "Nx", "Ny", "Nz")]
     upper_weights: Annotated[NDArray[np.float64], ("Ne", "Nx", "Ny", "Nz")]
 
-    def __init__(self):
+    def __init__(self) -> None:
         self.active = False
         self.energy_bounds = np.array([0.0, 1.0])
         self.Ne = 1
@@ -209,7 +211,7 @@ def __init__(self):
         self.target_weights = np.array([1.0]).reshape(*shape)
         self.upper_weights = np.array([1.0]).reshape(*shape)
 
-    def __call__(self, weight_windows, mesh=None, energy=None):
+    def __call__(self, weight_windows, mesh=None, energy=None) -> None:
         """Configure lower, target, and upper particle weights.
 
         Parameters
@@ -328,10 +330,10 @@ class PopulationControl(MCDCBase):
 
     active: bool
 
-    def __init__(self):
+    def __init__(self) -> None:
         self.active = False
 
-    def __call__(self, active: bool = True):
+    def __call__(self, active: bool = True) -> None:
         """Configure source-bank population control.
 
         Parameters
@@ -377,7 +379,7 @@ class Technique(MCDCBase):
     weight_windows: WeightWindows
     population_control: PopulationControl
 
-    def __init__(self):
+    def __init__(self) -> None:
         # Construct every simulation-wide technique configuration
         self.neutron_multigroup = NeutronMultigroup()
         self.implicit_capture = ImplicitCapture()
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index bc1019712..397182775 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -76,13 +76,13 @@ class Universe(MCDCObject):
     name: str
     cells: list[Cell]
 
-    def __init__(self, name: str = "", cells: list[Cell] = []):
+    def __init__(self, name: str = "", cells: list[Cell] = []) -> None:
         super().__init__()
 
         self.name = name or "(Unnamed universe)"
         self.cells = cells
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
 
         text += f"  - Name: {self.name}\n"
@@ -175,7 +175,7 @@ def __init__(
         y: tuple[float, float, int] | NoneType = None,
         z: tuple[float, float, int] | NoneType = None,
         universes: list[Universe] = [],
-    ):
+    ) -> None:
         super().__init__()
 
         self.name = name or "(Unnamed lattice)"
@@ -243,7 +243,7 @@ def _set_universe_IDs(self) -> None:
         universe_IDs = np.flip(universe_IDs, axis=2)
         self.universe_IDs = np.array(universe_IDs)
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         text = super().__repr__()
 
         text += f"  - Name: {self.name}\n"

From 086d0f82901a432aefac8b96c16f3f18085b6765 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 11:36:58 +0700
Subject: [PATCH 177/202] update typing on API

---
 mcdc/object_/settings.py  | 21 +++++++++++----------
 mcdc/object_/source.py    |  2 +-
 mcdc/object_/surface.py   |  6 +++---
 mcdc/object_/technique.py |  7 ++++++-
 4 files changed, 21 insertions(+), 15 deletions(-)

diff --git a/mcdc/object_/settings.py b/mcdc/object_/settings.py
index 4b8e2f859..b8b4207ae 100644
--- a/mcdc/object_/settings.py
+++ b/mcdc/object_/settings.py
@@ -1,9 +1,8 @@
-from typing import List
 import h5py
 import numpy as np
 
 from dataclasses import dataclass, field
-from numpy.typing import NDArray
+from numpy.typing import ArrayLike, NDArray
 
 ####
 
@@ -90,7 +89,9 @@ class Settings(MCDCBase):
     gpu_async_type: int = GPU_ASYNC_SIMPLE
     gpu_storage: int = GPU_STORAGE_SEPARATE
 
-    def set_time_census(self, time, tally_frequency=None) -> None:
+    def set_time_census(
+        self, time: ArrayLike, tally_frequency: int | None = None
+    ) -> None:
         """Configure census times for time-dependent transport.
 
         Parameters
@@ -142,11 +143,11 @@ def set_time_census(self, time, tally_frequency=None) -> None:
 
     def set_eigenmode(
         self,
-        N_inactive=0,
-        N_active=0,
-        k_init=1.0,
-        gyration_radius=None,
-        save_particle=False,
+        N_inactive: int = 0,
+        N_active: int = 0,
+        k_init: float = 1.0,
+        gyration_radius: str | None = None,
+        save_particle: bool = False,
     ) -> None:
         """Enable neutron k-eigenvalue mode.
 
@@ -214,7 +215,7 @@ def set_eigenmode(
             else:
                 print_error("Unknown gyration radius type")
 
-    def set_source_file(self, source_file_name) -> None:
+    def set_source_file(self, source_file_name: str) -> None:
         """Use particles from an HDF5 source file.
 
         The particle count is read from the file's ``particles_size`` dataset.
@@ -239,7 +240,7 @@ def set_source_file(self, source_file_name) -> None:
         with h5py.File(source_file_name, "r") as f:
             self.N_particle = int(f["particles_size"][()])
 
-    def set_transported_particles(self, transported_particles: List[str]) -> None:
+    def set_transported_particles(self, transported_particles: list[str]) -> None:
         """Select the particle species enabled during transport.
 
         Parameters
diff --git a/mcdc/object_/source.py b/mcdc/object_/source.py
index 04ffbfca6..b4bd3da4d 100644
--- a/mcdc/object_/source.py
+++ b/mcdc/object_/source.py
@@ -447,7 +447,7 @@ def __repr__(self) -> str:
     # Source moving
     # ==================================================================================
 
-    def move(self, velocities, durations) -> None:
+    def move(self, velocities: ArrayLike, durations: ArrayLike) -> None:
         """
         Define piecewise-constant motion for the source.
 
diff --git a/mcdc/object_/surface.py b/mcdc/object_/surface.py
index 3fafaccd7..41c00ca0c 100644
--- a/mcdc/object_/surface.py
+++ b/mcdc/object_/surface.py
@@ -2,7 +2,7 @@
 import numpy as np
 
 from numpy import float64
-from numpy.typing import NDArray
+from numpy.typing import ArrayLike, NDArray
 
 ####
 
@@ -128,7 +128,7 @@ class Surface(MCDCObject):
     move_translations: Annotated[NDArray[float64], ("N_move_grid", 3)]
     surface_crossing_tallies: list[TallySurfaceCrossing]
 
-    def __init__(self, type_, name, boundary_condition) -> None:
+    def __init__(self, type_: int, name: str, boundary_condition: str) -> None:
         super().__init__()
 
         self.type = type_
@@ -877,7 +877,7 @@ def __neg__(self) -> Region:
     # Surface moving
     # ==================================================================================
 
-    def move(self, velocities, durations) -> None:
+    def move(self, velocities: ArrayLike, durations: ArrayLike) -> None:
         """Define piecewise-constant translational motion.
 
         Parameters
diff --git a/mcdc/object_/technique.py b/mcdc/object_/technique.py
index b025b3ede..0a8ebc342 100644
--- a/mcdc/object_/technique.py
+++ b/mcdc/object_/technique.py
@@ -211,7 +211,12 @@ def __init__(self) -> None:
         self.target_weights = np.array([1.0]).reshape(*shape)
         self.upper_weights = np.array([1.0]).reshape(*shape)
 
-    def __call__(self, weight_windows, mesh=None, energy=None) -> None:
+    def __call__(
+        self,
+        weight_windows: NDArray[np.float64],
+        mesh: MeshBase | None = None,
+        energy: NDArray[np.float64] | None = None,
+    ) -> None:
         """Configure lower, target, and upper particle weights.
 
         Parameters

From b05bb27b4b2a096dbc18a8304c5a7db76214906a Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 11:50:46 +0700
Subject: [PATCH 178/202] make Region typed

---
 mcdc/object_/cell.py | 41 ++++++++++++++++++++++++++++++++---------
 1 file changed, 32 insertions(+), 9 deletions(-)

diff --git a/mcdc/object_/cell.py b/mcdc/object_/cell.py
index a184181a8..2ae400a07 100644
--- a/mcdc/object_/cell.py
+++ b/mcdc/object_/cell.py
@@ -1,5 +1,5 @@
 from __future__ import annotations
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Literal, TypeAlias
 
 if TYPE_CHECKING:
     from mcdc.object_.surface import Surface
@@ -38,27 +38,50 @@
 # Region
 # ======================================================================================
 
+RegionType: TypeAlias = Literal[
+    "all",
+    "halfspace",
+    "intersection",
+    "union",
+    "complement",
+]
+
 
 class Region:
     """Boolean combination of oriented surface half-spaces.
 
     Regions are normally built with unary ``+`` and ``-`` on
-    :class:`~mcdc.object_.surface.Surface` objects, followed by ``&`` (intersection),
-    ``|`` (union), and ``~`` (complement). During compilation, the expression is
-    converted to reverse Polish notation for evaluation by the geometry kernels.
+    :class:`~mcdc.object_.surface.Surface` objects, followed by ``&``
+    (intersection), ``|`` (union), and ``~`` (complement). During compilation,
+    the expression is converted to reverse Polish notation for evaluation by
+    the geometry kernels.
+
+    The supported region types and components are:
+
+    - ``"all"`` uses ``A=None`` and ``B=None``.
+    - ``"halfspace"`` uses a :class:`~mcdc.object_.surface.Surface` for ``A``
+      and ``-1`` or ``1`` for ``B``.
+    - ``"intersection"`` and ``"union"`` use a :class:`Region` for both
+      ``A`` and ``B``.
+    - ``"complement"`` uses a :class:`Region` for ``A`` and ``B=None``.
     """
 
-    type: str
+    type: RegionType
     A: Surface | Region | NoneType
     B: Region | int | NoneType
 
-    def __init__(self, type_, A, B) -> None:
+    def __init__(
+        self,
+        type_: RegionType,
+        A: Surface | Region | NoneType,
+        B: Region | int | NoneType,
+    ) -> None:
         self.type = type_
         self.A = A
         self.B = B
 
     @classmethod
-    def make_halfspace(cls, surface, sense) -> Region:
+    def make_halfspace(cls, surface: Surface, sense: Literal[-1, 1]) -> Region:
         """Create the positive or negative half-space of a surface.
 
         Parameters
@@ -77,10 +100,10 @@ def make_halfspace(cls, surface, sense) -> Region:
         region = Region("halfspace", surface, sense)
         return region
 
-    def __and__(self, other) -> Region:
+    def __and__(self, other: Region) -> Region:
         return Region("intersection", self, other)
 
-    def __or__(self, other) -> Region:
+    def __or__(self, other: Region) -> Region:
         return Region("union", self, other)
 
     def __invert__(self) -> Region:

From 1555e08f510f070a53c5ae97a3344f2d222b4c8e Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 11:51:53 +0700
Subject: [PATCH 179/202] update visualization typing

---
 mcdc/object_/simulation.py  | 34 ++++++++++++++++++++++++----------
 test/unit/test_visualize.py |  4 ++--
 2 files changed, 26 insertions(+), 12 deletions(-)

diff --git a/mcdc/object_/simulation.py b/mcdc/object_/simulation.py
index dd7b35933..bd9cbd06d 100644
--- a/mcdc/object_/simulation.py
+++ b/mcdc/object_/simulation.py
@@ -1,7 +1,9 @@
 from __future__ import annotations
-from typing import TYPE_CHECKING, Annotated
+from typing import TYPE_CHECKING, Annotated, Literal
 
 if TYPE_CHECKING:
+    from matplotlib.typing import ColorType
+
     from mcdc.object_.cell import Cell, Region
     from mcdc.object_.element import Element
     from mcdc.object_.electron_reaction import ElectronReactionBase
@@ -16,7 +18,8 @@
 ####
 
 import math
-from collections.abc import Sequence
+from collections.abc import Mapping, Sequence
+from os import PathLike, fspath
 
 import numpy as np
 from mpi4py import MPI
@@ -528,14 +531,14 @@ def compile(self) -> None:
 
     def visualize_model(
         self,
-        vis_plane,
-        x,
-        y,
-        z,
-        pixels,
-        colors,
-        time,
-        save_as,
+        vis_plane: Literal["xy", "xz", "yz", "yx", "zx", "zy"],
+        x: float | Sequence[float],
+        y: float | Sequence[float],
+        z: float | Sequence[float],
+        pixels: Sequence[int],
+        colors: Mapping[Material, ColorType] | None,
+        time: Sequence[float] | NDArray[float64],
+        save_as: str | PathLike[str] | None,
     ) -> None:
         """Render a two-dimensional material map of the compiled model.
 
@@ -579,6 +582,17 @@ def visualize_model(
 
         from mcdc.visualize import visualize_model
 
+        if not np.isscalar(x):
+            x = tuple(x)
+        if not np.isscalar(y):
+            y = tuple(y)
+        if not np.isscalar(z):
+            z = tuple(z)
+        pixels = tuple(pixels)
+        time = tuple(time)
+        if save_as is not None:
+            save_as = fspath(save_as)
+
         visualize_model(self, vis_plane, x, y, z, pixels, colors, time, save_as)
 
     def run(self) -> None:
diff --git a/test/unit/test_visualize.py b/test/unit/test_visualize.py
index 5b1eb80a9..155bc711f 100644
--- a/test/unit/test_visualize.py
+++ b/test/unit/test_visualize.py
@@ -15,13 +15,13 @@ def test_visualize_model(tmp_path):
     simulation = mcdc.Simulation()
     simulation.set_model([cell])
 
-    output = str(tmp_path / "model")
+    output = tmp_path / "model"
     simulation.visualize_model(
         vis_plane="xz",
         x=[-0.5, 0.5],
         y=0.0,
         z=[0.0, 1.0],
-        pixels=(2, 2),
+        pixels=[2, 2],
         colors=None,
         time=[0.0],
         save_as=output,

From d5ad9ee23cd59b903267e3c058454b82099684e6 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 12:56:54 +0700
Subject: [PATCH 180/202] add pyright api checker

---
 .github/workflows/publish-pypi.yml |  5 +++
 .github/workflows/unit_test.yml    |  3 ++
 mcdc/object_/universe.py           | 13 +++++--
 mcdc/py.typed                      |  0
 pyproject.toml                     |  6 ++++
 test/typecheck/public_api.py       | 56 ++++++++++++++++++++++++++++++
 6 files changed, 80 insertions(+), 3 deletions(-)
 create mode 100644 mcdc/py.typed
 create mode 100644 test/typecheck/public_api.py

diff --git a/.github/workflows/publish-pypi.yml b/.github/workflows/publish-pypi.yml
index 8f9a93fa7..6d17f4b45 100644
--- a/.github/workflows/publish-pypi.yml
+++ b/.github/workflows/publish-pypi.yml
@@ -46,6 +46,11 @@ jobs:
       # and the wheel into the dist/ directory.
       - name: Build distributions
         run: python -m build
+      # Confirm that type checkers can detect MC/DC's inline annotations.
+      - name: Verify typing marker
+        run: |
+          unzip -l dist/*.whl | grep "mcdc/py.typed"
+          tar -tzf dist/*.tar.gz | grep "/mcdc/py.typed"
       # Hand the built distributions over to the publish job.
       - name: Upload distributions
         uses: actions/upload-artifact@v4
diff --git a/.github/workflows/unit_test.yml b/.github/workflows/unit_test.yml
index 0d2e722ac..3da0b21a3 100644
--- a/.github/workflows/unit_test.yml
+++ b/.github/workflows/unit_test.yml
@@ -47,3 +47,6 @@ jobs:
       - name: Run unit tests
         run: |
           python -m pytest -v test/unit
+
+      - name: Run public API type checks
+        run: pyright
diff --git a/mcdc/object_/universe.py b/mcdc/object_/universe.py
index 397182775..43477f6a8 100644
--- a/mcdc/object_/universe.py
+++ b/mcdc/object_/universe.py
@@ -1,6 +1,6 @@
 from __future__ import annotations
 from types import NoneType
-from typing import TYPE_CHECKING, Annotated
+from typing import TYPE_CHECKING, Annotated, TypeAlias
 
 if TYPE_CHECKING:
     from mcdc.object_.cell import Cell
@@ -90,6 +90,11 @@ def __repr__(self) -> str:
         return text
 
 
+UniverseLayout: TypeAlias = (
+    list[Universe] | list[list[Universe]] | list[list[list[Universe]]]
+)
+
+
 # ======================================================================================
 # Lattice
 # ======================================================================================
@@ -165,7 +170,9 @@ class Lattice(MCDCObject):
     dz: float
     Nz: int
 
-    universes: list[Universe]  # Non-numba
+    universes: (  # Non-numba
+        list[Universe] | list[list[Universe]] | list[list[list[Universe]]]
+    )
     universe_IDs: Annotated[NDArray[int64], ("Nx", "Ny", "Nz")]
 
     def __init__(
@@ -174,7 +181,7 @@ def __init__(
         x: tuple[float, float, int] | NoneType = None,
         y: tuple[float, float, int] | NoneType = None,
         z: tuple[float, float, int] | NoneType = None,
-        universes: list[Universe] = [],
+        universes: UniverseLayout = [],
     ) -> None:
         super().__init__()
 
diff --git a/mcdc/py.typed b/mcdc/py.typed
new file mode 100644
index 000000000..e69de29bb
diff --git a/pyproject.toml b/pyproject.toml
index 091b8f517..f5fe738f3 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -67,6 +67,7 @@ docs = [
 dev = [
   "black",
   "pre-commit",
+  "pyright",
   "pytest",
 ]
 
@@ -89,6 +90,11 @@ force-exclude = '''
 )
 '''
 
+[tool.pyright]
+include = ["test/typecheck"]
+pythonVersion = "3.10"
+typeCheckingMode = "strict"
+
 [tool.pytest.ini_options]
 testpaths = ["test/unit"]
 # The slow suite is selected by path (`pytest test/regression`); keep the cloned
diff --git a/test/typecheck/public_api.py b/test/typecheck/public_api.py
new file mode 100644
index 000000000..b8f56f955
--- /dev/null
+++ b/test/typecheck/public_api.py
@@ -0,0 +1,56 @@
+"""Static checks for representative use of the public MC/DC API."""
+
+from pathlib import Path
+
+import numpy as np
+
+import mcdc
+
+
+def build_typed_simulation(output: Path) -> mcdc.Simulation:
+    neutron_data = mcdc.NeutronMultigroupData(capture=[0.1], scatter=[0.9])
+    material = mcdc.Material(name="Material", neutron_multigroup=neutron_data)
+
+    left = mcdc.Surface.PlaneX(x=-1.0, boundary_condition="vacuum")
+    right = mcdc.Surface.PlaneX(x=1.0, boundary_condition="vacuum")
+    cell = mcdc.Cell(region=+left & -right, fill=material)
+
+    universe = mcdc.Universe(name="Universe", cells=[cell])
+    lattice = mcdc.Lattice(x=(-1.0, 2.0, 1), universes=[[universe]])
+    root_cell = mcdc.Cell(fill=lattice)
+
+    source = mcdc.Source(position=[0.0, 0.0, 0.0], energy=1.0e6)
+    source.move(velocities=[[1.0, 0.0, 0.0]], durations=[1.0])
+    left.move(velocities=[[0.5, 0.0, 0.0]], durations=[1.0])
+
+    uniform_mesh = mcdc.MeshUniform(x=(-1.0, 0.1, 20))
+    structured_mesh = mcdc.MeshStructured(x=np.linspace(-1.0, 1.0, 21))
+    flux = mcdc.Tally(mesh=uniform_mesh, scores=["flux"])
+    density = mcdc.Tally(mesh=structured_mesh, scores=["density"])
+
+    simulation = mcdc.Simulation(name="Typed simulation")
+    simulation.set_model([root_cell])
+    simulation.set_sources([source])
+    simulation.set_tallies([flux, density])
+
+    simulation.settings.N_particle = 1_000
+    simulation.settings.set_time_census([1.0, 2.0])
+    simulation.settings.set_transported_particles(["neutron"])
+    simulation.technique.implicit_capture()
+    simulation.technique.weight_windows(
+        np.ones((1, 20, 1, 1, 3)),
+        mesh=uniform_mesh,
+        energy=np.array([0.0, 20.0e6]),
+    )
+
+    simulation.visualize_model(
+        vis_plane="xy",
+        x=[-1.0, 1.0],
+        y=[-1.0, 1.0],
+        z=0.0,
+        pixels=[100, 100],
+        colors={material: "red"},
+        time=[0.0],
+        save_as=output,
+    )
+    return simulation

From d0ae75130538433d79694b0d4c370322041c3243 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 13:13:34 +0700
Subject: [PATCH 181/202] consolidate mcdc logo files

---
 .../images/home/mcdc_square.svg => assets/mcdc-favicon.svg    | 0
 docs/source/conf.py                                           | 4 ++--
 docs/source/images/home/mcdc.svg                              | 1 -
 3 files changed, 2 insertions(+), 3 deletions(-)
 rename docs/source/images/home/mcdc_square.svg => assets/mcdc-favicon.svg (100%)
 delete mode 100644 docs/source/images/home/mcdc.svg

diff --git a/docs/source/images/home/mcdc_square.svg b/assets/mcdc-favicon.svg
similarity index 100%
rename from docs/source/images/home/mcdc_square.svg
rename to assets/mcdc-favicon.svg
diff --git a/docs/source/conf.py b/docs/source/conf.py
index b57a386e1..eba9bddb5 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -60,8 +60,8 @@
 # in-page table of contents, search, and light/dark mode.
 html_theme = "pydata_sphinx_theme"
 html_title = "MC/DC Documentation"
-html_logo = "images/home/mcdc.svg"
-html_favicon = "images/home/mcdc_square.svg"
+html_logo = "../../assets/mcdc-logo.svg"
+html_favicon = "../../assets/mcdc-favicon.svg"
 
 # Read the Docs provides the active version slug during hosted builds. Use the
 # development docs as the local-build default.
diff --git a/docs/source/images/home/mcdc.svg b/docs/source/images/home/mcdc.svg
deleted file mode 100644
index 366ea9230..000000000
--- a/docs/source/images/home/mcdc.svg
+++ /dev/null
@@ -1 +0,0 @@
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From f2b7ff4662a4d21e04881cd5cc67f02ad458fa65 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 13:20:36 +0700
Subject: [PATCH 182/202] support only the tested Python 3.13

---
 .github/workflows/black_lint.yml                        | 2 +-
 .pre-commit-config.yaml                                 | 2 +-
 .readthedocs.yaml                                       | 2 +-
 containers/Dockerfile                                   | 2 +-
 containers/Dockerfile.cuda                              | 2 +-
 containers/Dockerfile.rocm                              | 2 +-
 docs/source/contributing/continuous_integration.rst     | 4 ++--
 docs/source/user_guide/container.rst                    | 2 +-
 docs/source/user_guide/execution/batch_systems.rst      | 8 ++++----
 docs/source/user_guide/faq.rst                          | 3 +--
 docs/source/user_guide/getting_started/installation.rst | 6 +++---
 docs/source/user_guide/troubleshooting.rst              | 4 ++--
 pyproject.toml                                          | 8 +++-----
 13 files changed, 22 insertions(+), 25 deletions(-)

diff --git a/.github/workflows/black_lint.yml b/.github/workflows/black_lint.yml
index 366d1174c..a526643a0 100644
--- a/.github/workflows/black_lint.yml
+++ b/.github/workflows/black_lint.yml
@@ -16,7 +16,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.14"
+          python-version: "3.13"
           cache: pip
 
       - name: Install Black
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 036d92446..698c34800 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -8,4 +8,4 @@ repos:
         # supported by your project here, or alternatively use
         # pre-commit's default_language_version, see
         # https://pre-commit.com/#top_level-default_language_version
-        language_version: python3.11
+        language_version: python3.13
diff --git a/.readthedocs.yaml b/.readthedocs.yaml
index 4baf2f1d8..aef563578 100644
--- a/.readthedocs.yaml
+++ b/.readthedocs.yaml
@@ -9,7 +9,7 @@ version: 2
 build:
   os: ubuntu-22.04
   tools:
-    python: "3.11"
+    python: "3.13"
   apt_packages:
     - libopenmpi-dev
     - openmpi-bin
diff --git a/containers/Dockerfile b/containers/Dockerfile
index 57a103cb1..07731fbdf 100644
--- a/containers/Dockerfile
+++ b/containers/Dockerfile
@@ -1,4 +1,4 @@
-FROM python:3.11-slim
+FROM python:3.13-slim
 
 LABEL org.opencontainers.image.source="https://github.com/mcdc-project/mcdc"
 LABEL org.opencontainers.image.description="MC/DC: Monte Carlo Dynamic Code"
diff --git a/containers/Dockerfile.cuda b/containers/Dockerfile.cuda
index 00d74a541..c11fc878d 100644
--- a/containers/Dockerfile.cuda
+++ b/containers/Dockerfile.cuda
@@ -30,7 +30,7 @@ ENV PATH="/opt/conda/bin:$PATH"
 # Install Python environment (matching Harmonize prereqs: CUDA=11.8, Numba>=0.60.0)
 RUN conda install -y \
     gxx \
-    python=3.11 \
+    python=3.13 \
     numba \
     numpy \
     && conda clean -afy
diff --git a/containers/Dockerfile.rocm b/containers/Dockerfile.rocm
index 05505cd62..c0d67f713 100644
--- a/containers/Dockerfile.rocm
+++ b/containers/Dockerfile.rocm
@@ -30,7 +30,7 @@ ENV PATH="/opt/conda/bin:$PATH"
 # Install Python environment (matching Harmonize prereqs: ROCm=6.0.0, Numba>=0.60.0)
 RUN conda install -y \
     gxx \
-    python=3.11 \
+    python=3.13 \
     numba \
     numpy \
     && conda clean -afy
diff --git a/docs/source/contributing/continuous_integration.rst b/docs/source/contributing/continuous_integration.rst
index c2943f376..16860c4f4 100644
--- a/docs/source/contributing/continuous_integration.rst
+++ b/docs/source/contributing/continuous_integration.rst
@@ -31,9 +31,9 @@ The standard dev env for MC/DC install on this machine can be ascertained with
 
 .. code-block:: bash
 
-    module load cuda/11.8 gcc/10.3 mpich/4.0h_gcc-10 python/3.11
+    module load cuda/11.8 gcc/10.3 mpich/4.0h_gcc-10 python/3.13
     python -m venv <MCDC_venv>
-    module unload python/3.11
+    module unload python/3.13
     source <MCDC_venv>/bin/activate
 
 Then MC/DC and harmonize can be installed there in the normal manner for GPU capabilities.
diff --git a/docs/source/user_guide/container.rst b/docs/source/user_guide/container.rst
index b74af97c3..2089bae41 100644
--- a/docs/source/user_guide/container.rst
+++ b/docs/source/user_guide/container.rst
@@ -33,7 +33,7 @@ Tested Platforms
 | COE (OSU)   | Rocky 8.10 | x86_64 | Apptainer 1.4.5    | ✓      |
 +-------------+------------+--------+--------------------+--------+
 
-All platforms produce identical containers: Debian 13, Python 3.11,
+All platforms produce identical containers: Debian 13, Python 3.13,
 MPICH 4.2.1, MC/DC 0.12.0.
 
 Getting Started (New Users)
diff --git a/docs/source/user_guide/execution/batch_systems.rst b/docs/source/user_guide/execution/batch_systems.rst
index bfc3cf458..61daa5aed 100644
--- a/docs/source/user_guide/execution/batch_systems.rst
+++ b/docs/source/user_guide/execution/batch_systems.rst
@@ -34,7 +34,7 @@ as well as many university and national lab clusters.
    #SBATCH --time=01:00:00
    #SBATCH --partition=pbatch
 
-   module load python/3.11
+   module load python/3.13
    source /path/to/your/venv/bin/activate
 
    srun python input.py --mode=numba --caching
@@ -51,7 +51,7 @@ as well as many university and national lab clusters.
    #SBATCH --time=00:30:00
    #SBATCH --partition=gpu
 
-   module load python/3.11 cuda/11.8
+   module load python/3.13 cuda/11.8
    source /path/to/your/venv/bin/activate
 
    srun python input.py --mode=numba --target=gpu --gpu_strategy=event
@@ -69,7 +69,7 @@ El Capitan systems (AMD MI250X / MI300A GPUs).
 
    #!/bin/bash
 
-   module load cray-mpich python/3.11
+   module load cray-mpich python/3.13
    source /path/to/your/venv/bin/activate
 
    flux run -N 2 -n 72 python input.py --mode=numba --caching
@@ -80,7 +80,7 @@ El Capitan systems (AMD MI250X / MI300A GPUs).
 
    #!/bin/bash
 
-   module load cray-mpich rocm/6.0.0 python/3.11
+   module load cray-mpich rocm/6.0.0 python/3.13
    source /path/to/your/venv/bin/activate
 
    flux run -N 2 -n 8 -g 1 --queue=mi300a \
diff --git a/docs/source/user_guide/faq.rst b/docs/source/user_guide/faq.rst
index e1dba8b3f..49170a262 100644
--- a/docs/source/user_guide/faq.rst
+++ b/docs/source/user_guide/faq.rst
@@ -9,8 +9,7 @@ General
 
 **What Python versions does MC/DC support?**
 
-MC/DC supports Python ``>3.10``.
-We recommend Python 3.11 for the best performance and compatibility with Numba.
+MC/DC supports Python 3.13.
 
 **What platforms are supported?**
 
diff --git a/docs/source/user_guide/getting_started/installation.rst b/docs/source/user_guide/getting_started/installation.rst
index e671c73a7..8218a35b4 100644
--- a/docs/source/user_guide/getting_started/installation.rst
+++ b/docs/source/user_guide/getting_started/installation.rst
@@ -109,12 +109,12 @@ or `Anaconda <https://www.anaconda.com/>`_. HPC instructions:
 
 
 Then create and activate a new conda environment called *mcdc-env* in
-which to install MC/DC. MC/DC supports Python ``>3.10``;
-we recommend Python 3.11:
+which to install MC/DC.
+MC/DC supports Python 3.13:
 
 .. code-block:: sh
 
-    conda create -n mcdc-env python=3.11
+    conda create -n mcdc-env python=3.13
     conda activate mcdc-env
 
 Then, MC/DC can be installed from source by first cloning the MC/DC repository:
diff --git a/docs/source/user_guide/troubleshooting.rst b/docs/source/user_guide/troubleshooting.rst
index a604b8300..397830b00 100644
--- a/docs/source/user_guide/troubleshooting.rst
+++ b/docs/source/user_guide/troubleshooting.rst
@@ -105,10 +105,10 @@ Incorrect or missing modules are the most common source of build failures.
      - **Module loads**
      - **Notes**
    * - Quartz (LLNL)
-     - ``module load python/3.11``
+     - ``module load python/3.13``
      - Default ``intel-classic`` + ``mvapich2`` are sufficient
    * - Dane (LLNL)
-     - ``module load python/3.11``
+     - ``module load python/3.13``
      - x86_64, similar to Quartz
    * - Lassen (LLNL)
      - ``module load gcc/8 cuda/11.8``
diff --git a/pyproject.toml b/pyproject.toml
index f5fe738f3..7625c0562 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -12,7 +12,7 @@ authors = [
 
 description = "A performant, scalable, and machine-portable Python-based Monte Carlo radiation transport code."
 readme = "README.md"
-requires-python = ">=3.10"
+requires-python = ">=3.13"
 license = "BSD-3-Clause"
 license-files = ["LICENSE"]
 
@@ -34,9 +34,6 @@ classifiers = [
   "Programming Language :: Python",
   "Programming Language :: Python :: 3",
   "Programming Language :: Python :: 3 :: Only",
-  "Programming Language :: Python :: 3.10",
-  "Programming Language :: Python :: 3.11",
-  "Programming Language :: Python :: 3.12",
   "Programming Language :: Python :: 3.13",
 
   "Operating System :: MacOS",
@@ -82,6 +79,7 @@ Issues = "https://github.com/mcdc-project/mcdc/issues"
 source = "vcs"
 
 [tool.black]
+target-version = ["py313"]
 force-exclude = '''
 (
   mcdc/numba_types\.py
@@ -92,7 +90,7 @@ force-exclude = '''
 
 [tool.pyright]
 include = ["test/typecheck"]
-pythonVersion = "3.10"
+pythonVersion = "3.13"
 typeCheckingMode = "strict"
 
 [tool.pytest.ini_options]

From 3a087d691faeab2783ba8818de5ca282722ee758 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 13:40:13 +0700
Subject: [PATCH 183/202] minor edit

---
 docs/source/project/release_policy.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/source/project/release_policy.rst b/docs/source/project/release_policy.rst
index 4241bbb34..24a4431bd 100644
--- a/docs/source/project/release_policy.rst
+++ b/docs/source/project/release_policy.rst
@@ -11,7 +11,7 @@ Minor Releases
 
 MC/DC plans one minor release each calendar quarter.
 These releases collect compatible features, improvements, and fixes that have passed the project's required review and validation.
-For planning convenience, the four release cycles may be referred to informally as winter (Dec-Feb), spring (Mar-May), summer (Jun-Aug), and autumn (Sep-Nov) releases.
+For planning convenience, the four release cycles may be referred to informally as winter (Dec-Feb), spring (Mar-May), summer (Jun-Aug), and autumn/fall (Sep-Nov) releases.
 
 The quarterly schedule is a target rather than a reason to release unverified work.
 A minor release may be delayed when additional testing, documentation, or integration work is needed; it may also be brought forward when the accumulated changes are substantial and users would benefit from earlier availability.

From f33eed2dd063a0d2f0f57cb2ec07b0891bed5e93 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 13:45:42 +0700
Subject: [PATCH 184/202] make release policy language consistent

---
 docs/source/project/release_policy.rst | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/docs/source/project/release_policy.rst b/docs/source/project/release_policy.rst
index 24a4431bd..bfd7c0d2f 100644
--- a/docs/source/project/release_policy.rst
+++ b/docs/source/project/release_policy.rst
@@ -9,17 +9,17 @@ MC/DC follows `Semantic Versioning <https://semver.org/>`_ and maintains a human
 Minor Releases
 --------------
 
-MC/DC plans one minor release each calendar quarter.
+MC/DC plans one minor release in each three-month seasonal cycle.
 These releases collect compatible features, improvements, and fixes that have passed the project's required review and validation.
-For planning convenience, the four release cycles may be referred to informally as winter (Dec-Feb), spring (Mar-May), summer (Jun-Aug), and autumn/fall (Sep-Nov) releases.
+For planning convenience, these cycles follow the Northern Hemisphere meteorological seasons: winter (Dec-Feb), spring (Mar-May), summer (Jun-Aug), and autumn/fall (Sep-Nov).
 
-The quarterly schedule is a target rather than a reason to release unverified work.
+The seasonal schedule is a target rather than a reason to release unverified work.
 A minor release may be delayed when additional testing, documentation, or integration work is needed; it may also be brought forward when the accumulated changes are substantial and users would benefit from earlier availability.
 
 Patch Releases
 --------------
 
-Bug fixes are not held until the next quarterly minor release.
+Bug fixes are not held until the next seasonal minor release.
 Once a fix has passed review and the relevant validation and release checks, MC/DC publishes a patch release as soon as practical.
 
 Published versions and release notes are available from the `MC/DC releases page <https://github.com/mcdc-project/mcdc/releases>`_.

From 29a2562621315d7fbc9164fd5398e0f49708c4ea Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 15:06:35 +0700
Subject: [PATCH 185/202] update CHANGELOG and CITATION

---
 CHANGELOG.md | 12 ++++-----
 CITATION.cff | 69 ++++++++++++++++++++++++++++++++++++++++++----------
 2 files changed, 62 insertions(+), 19 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 044192510..c0d9c1907 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -4,11 +4,12 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/2.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [Unreleased]
+## [0.15.0] - 2026-08-11
 
 ### Added
 
 - Add `NeutronMultigroupData` and hybrid neutron multigroup transport with material-local physical energy grids and energy-representation policies, together with the `Material.multigroup()` convenience interface, from [@ilhamv]
+- Add PEP 561-compatible inline type information and strict Pyright checks for the public Python API
 
 ### Changed
 
@@ -18,14 +19,12 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/2.0.0/),
 - Move model-specific finalization into simulation compilation and reserve runtime preparation for framework-level packing and execution setup from [@ilhamv]
 - **Breaking:** Encapsulate MC/DC model building and execution within an explicit `mcdc.Simulation` instance, replacing the global simulation state and interface from [@ilhamv]
 - Move regression tests from the custom `run.py` harness to pytest-based collection and reporting from [@massimolarsen]
-
-### Deprecated
+- **Breaking:** Declare Python 3.13 as the only currently supported and tested Python version
+- Adopt a three-month seasonal cycle for minor releases while continuing to publish patch releases as needed
 
 ### Removed
 
-### Fixed
-
-### Security
+- Remove the legacy `install.sh` installation helper
 
 ## [0.14.2] - 2026-07-15
 
@@ -137,6 +136,7 @@ The pre-refactor implementation remains available in the `cement` branch as a re
 - Multi-table distribution table selection sampling from [@melekderman]
 
 [Unreleased]: https://github.com/mcdc-project/mcdc/tree/dev
+[0.15.0]: https://github.com/mcdc-project/mcdc/releases/tag/v0.15.0
 [0.14.2]: https://github.com/mcdc-project/mcdc/releases/tag/v0.14.2
 [0.14.1]: https://github.com/mcdc-project/mcdc/releases/tag/v0.14.1
 [0.14.0]: https://github.com/mcdc-project/mcdc/releases/tag/v0.14.0
diff --git a/CITATION.cff b/CITATION.cff
index a86cffad3..5a29e24ff 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -1,21 +1,14 @@
-# This CITATION.cff file was generated with cffinit.
-# Visit https://bit.ly/cffinit to generate yours today!
+# This CITATION.cff file was initially generated with cffinit
+# and is maintained manually.
 
 cff-version: 1.2.0
 title: 'MC/DC: Monte Carlo Dynamic Code'
 message: >-
-  If you use this software, please cite it using the
-  metadata from this file.
+  If you use MC/DC in published work, please cite the JOSS
+  article listed as the preferred citation.
 type: software
 authors:
   - name: The MC/DC Development Team
-identifiers:
-  - type: doi
-    value: 10.48550/arXiv.2305.07636
-    description: MC/DC Origins
-  - type: doi
-    value: 10.21105/joss.06415
-    description: MC/DC JOSS Article
 repository-code: 'https://github.com/mcdc-project/mcdc'
 url: 'https://mcdc.readthedocs.io/en/stable/'
 abstract: >-
@@ -41,5 +34,55 @@ keywords:
   - Numba
   - GPU
 license: BSD-3-Clause
-version: 0.14.1
-date-released: '2026-07-04'
+version: 0.15.0
+date-released: '2026-08-11'
+preferred-citation:
+  type: article
+  authors:
+    - family-names: Morgan
+      given-names: Joanna Piper
+    - family-names: Variansyah
+      given-names: Ilham
+    - family-names: Pasmann
+      given-names: Samuel L.
+    - family-names: Clements
+      given-names: Kayla B.
+    - family-names: Cuneo
+      given-names: Braxton
+    - family-names: Mote
+      given-names: Alexander
+    - family-names: Goodman
+      given-names: Charles
+    - family-names: Shaw
+      given-names: Caleb
+    - family-names: Northrop
+      given-names: Jordan
+    - family-names: Pankaj
+      given-names: Rohan
+    - family-names: Lame
+      given-names: Ethan
+    - family-names: Whewell
+      given-names: Benjamin
+    - family-names: McClarren
+      given-names: Ryan G.
+    - family-names: Palmer
+      given-names: Todd S.
+    - family-names: Chen
+      given-names: Lizhong
+    - family-names: Anistratov
+      given-names: Dmitriy Y.
+    - family-names: Kelley
+      given-names: C. T.
+    - family-names: Palmer
+      given-names: Camille J.
+    - family-names: Niemeyer
+      given-names: Kyle E.
+  title: >-
+    Monte Carlo / Dynamic Code (MC/DC): An accelerated Python package for
+    fully transient neutron transport and rapid methods development
+  journal: Journal of Open Source Software
+  year: 2024
+  volume: '9'
+  issue: '96'
+  start: '6415'
+  doi: 10.21105/joss.06415

From 5c1607b19a9719f713b3f32fef9ef78a816d6171 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 15:25:46 +0700
Subject: [PATCH 186/202] temporary python compatibility test workflow

---
 .github/workflows/black_lint.yml           |  2 +
 .github/workflows/docker.yml               |  2 +
 .github/workflows/docs_test.yml            |  4 +-
 .github/workflows/python_compatibility.yml | 49 ++++++++++++++++++++++
 .github/workflows/regression_test.yml      |  2 +
 .github/workflows/unit_test.yml            |  2 +
 6 files changed, 60 insertions(+), 1 deletion(-)
 create mode 100644 .github/workflows/python_compatibility.yml

diff --git a/.github/workflows/black_lint.yml b/.github/workflows/black_lint.yml
index a526643a0..7f31c9067 100644
--- a/.github/workflows/black_lint.yml
+++ b/.github/workflows/black_lint.yml
@@ -6,6 +6,8 @@ on:
 
 jobs:
   black-lint:
+    # Temporary suppression while validating Python compatibility on make_release.
+    if: github.ref_name != 'make_release' && github.head_ref != 'make_release'
     name: Lint with Black
     runs-on: ubuntu-latest
 
diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml
index 97f81d0bc..0977e5514 100644
--- a/.github/workflows/docker.yml
+++ b/.github/workflows/docker.yml
@@ -32,6 +32,8 @@ jobs:
   # Stage 0: Detect what changed (drives downstream job decisions)
   # ---------------------------------------------------------------------------
   changes:
+    # Temporary suppression while validating Python compatibility on make_release.
+    if: github.ref_name != 'make_release' && github.head_ref != 'make_release'
     name: Detect changes
     runs-on: ubuntu-latest
     outputs:
diff --git a/.github/workflows/docs_test.yml b/.github/workflows/docs_test.yml
index 24e1ca536..b71c7ee83 100644
--- a/.github/workflows/docs_test.yml
+++ b/.github/workflows/docs_test.yml
@@ -7,6 +7,8 @@ on:
 
 jobs:
   build-docs:
+    # Temporary suppression while validating Python compatibility on make_release.
+    if: github.ref_name != 'make_release' && github.head_ref != 'make_release'
     runs-on: "ubuntu-latest"
     timeout-minutes: 60
 
@@ -39,4 +41,4 @@ jobs:
 
       - name: Build the docs
         working-directory: docs
-        run: make html
\ No newline at end of file
+        run: make html
diff --git a/.github/workflows/python_compatibility.yml b/.github/workflows/python_compatibility.yml
new file mode 100644
index 000000000..dce73270e
--- /dev/null
+++ b/.github/workflows/python_compatibility.yml
@@ -0,0 +1,49 @@
+name: Python Compatibility Tests
+
+on:
+  workflow_dispatch:
+  # Temporary trigger for validating this workflow before it reaches the default branch.
+  push:
+    branches: [make_release]
+
+jobs:
+  compatibility-test:
+    name: Python ${{ matrix.python-version }}
+    runs-on: ubuntu-latest
+
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.11", "3.12", "3.13", "3.14"]
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache: pip
+
+      - name: Set up MPI
+        uses: mpi4py/setup-mpi@v1
+
+      - name: Install mpi4py
+        run: |
+          pip install --upgrade pip
+          pip install --no-binary=mpi4py mpi4py
+
+      - name: Install MC/DC
+        if: matrix.python-version == '3.13' || matrix.python-version == '3.14'
+        run: pip install -e ".[dev]"
+
+      - name: Install MC/DC for exploratory compatibility testing
+        if: matrix.python-version == '3.11' || matrix.python-version == '3.12'
+        run: pip install --ignore-requires-python -e ".[dev]"
+
+      - name: Run unit tests
+        run: python -m pytest -v test/unit
+
+      - name: Run regression tests
+        run: python -m pytest -v test/regression
diff --git a/.github/workflows/regression_test.yml b/.github/workflows/regression_test.yml
index 6ed94566f..c5c3fed60 100644
--- a/.github/workflows/regression_test.yml
+++ b/.github/workflows/regression_test.yml
@@ -24,6 +24,8 @@ env:
 
 jobs:
   regression-test:
+    # Temporary suppression while validating Python compatibility on make_release.
+    if: github.ref_name != 'make_release' && github.head_ref != 'make_release'
     name: ${{ matrix.mode }} (py${{ matrix.python-version }})
     runs-on: ubuntu-latest
     timeout-minutes: ${{ matrix.timeout }}
diff --git a/.github/workflows/unit_test.yml b/.github/workflows/unit_test.yml
index 3da0b21a3..727b8d3cc 100644
--- a/.github/workflows/unit_test.yml
+++ b/.github/workflows/unit_test.yml
@@ -6,6 +6,8 @@ on:
 
 jobs:
   unit-test:
+    # Temporary suppression while validating Python compatibility on make_release.
+    if: github.ref_name != 'make_release' && github.head_ref != 'make_release'
     name: (py${{ matrix.python-version }})
     runs-on: ubuntu-latest
 

From 0be945263d2834fd06be29a171552a4c593ee9ae Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 15:41:10 +0700
Subject: [PATCH 187/202] update workflow test

---
 .github/workflows/python_compatibility.yml | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/python_compatibility.yml b/.github/workflows/python_compatibility.yml
index dce73270e..a13a3c0cf 100644
--- a/.github/workflows/python_compatibility.yml
+++ b/.github/workflows/python_compatibility.yml
@@ -34,16 +34,17 @@ jobs:
           pip install --upgrade pip
           pip install --no-binary=mpi4py mpi4py
 
+      - name: Relax the MC/DC Python requirement for exploratory testing
+        if: matrix.python-version == '3.11' || matrix.python-version == '3.12'
+        run: sed -i 's/requires-python = ">=3.13"/requires-python = ">=3.11"/' pyproject.toml
+
       - name: Install MC/DC
-        if: matrix.python-version == '3.13' || matrix.python-version == '3.14'
+        id: install
         run: pip install -e ".[dev]"
 
-      - name: Install MC/DC for exploratory compatibility testing
-        if: matrix.python-version == '3.11' || matrix.python-version == '3.12'
-        run: pip install --ignore-requires-python -e ".[dev]"
-
       - name: Run unit tests
         run: python -m pytest -v test/unit
 
       - name: Run regression tests
+        if: always() && steps.install.outcome == 'success'
         run: python -m pytest -v test/regression

From 6a856693fc5cee9520cb94dd037318b5b541a9f4 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 15:45:42 +0700
Subject: [PATCH 188/202] update workflow test

---
 pyproject.toml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 7625c0562..32ccd9ab1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -45,8 +45,9 @@ classifiers = [
 ]
 
 dependencies = [
-  "numba>=0.60.0",
+  "numba>=0.61.0",
   "numpy>=2.0.0",
+  "scipy",
   "matplotlib",
   "mpi4py>=3.1.4",
   "h5py",

From 69fb2bfd21e80b4f5b343cc770881dfede637492 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 15:57:14 +0700
Subject: [PATCH 189/202] temporary numba only test

---
 .github/workflows/python_compatibility.yml | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/python_compatibility.yml b/.github/workflows/python_compatibility.yml
index a13a3c0cf..32988a5a5 100644
--- a/.github/workflows/python_compatibility.yml
+++ b/.github/workflows/python_compatibility.yml
@@ -42,9 +42,12 @@ jobs:
         id: install
         run: pip install -e ".[dev]"
 
-      - name: Run unit tests
-        run: python -m pytest -v test/unit
+      #- name: Run unit tests
+      #  run: python -m pytest -v test/unit
 
+      #- name: Run regression tests
+      #  if: always() && steps.install.outcome == 'success'
+      #  run: python -m pytest -v test/regression
+      
       - name: Run regression tests
-        if: always() && steps.install.outcome == 'success'
-        run: python -m pytest -v test/regression
+        run: python -m pytest -v test/regression --mode numba

From a1247a1945767f0460dcc3d3dd9005380bce5244 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 16:09:26 +0700
Subject: [PATCH 190/202] temporary numba only test

---
 .github/workflows/python_compatibility.yml | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.github/workflows/python_compatibility.yml b/.github/workflows/python_compatibility.yml
index 32988a5a5..a2623da32 100644
--- a/.github/workflows/python_compatibility.yml
+++ b/.github/workflows/python_compatibility.yml
@@ -6,6 +6,9 @@ on:
   push:
     branches: [make_release]
 
+env:
+  UCX_TLS: self,sm,tcp
+
 jobs:
   compatibility-test:
     name: Python ${{ matrix.python-version }}

From 5a47a33764cad09a672fa01008f6498b26a702da Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 18:44:24 +0700
Subject: [PATCH 191/202] python version compatibility update

---
 CHANGELOG.md   | 12 +++++++-----
 README.md      |  2 ++
 pyproject.toml |  9 ++++++---
 3 files changed, 15 insertions(+), 8 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index c0d9c1907..028688608 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,22 +9,24 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/2.0.0/),
 ### Added
 
 - Add `NeutronMultigroupData` and hybrid neutron multigroup transport with material-local physical energy grids and energy-representation policies, together with the `Material.multigroup()` convenience interface, from [@ilhamv]
-- Add PEP 561-compatible inline type information and strict Pyright checks for the public Python API
+- Add manually triggered unit and serial regression compatibility testing for Python 3.11, 3.12, and 3.14 while retaining Python 3.13 for automatic testing, from [@ilhamv]
+- Add PEP 561-compatible inline type information and strict Pyright checks for the public Python API, from [@ilhamv]
 
 ### Changed
 
 - **Breaking:** Unify native and neutron multigroup materials under one non-polymorphic `Material` and runtime layout, replacing `MaterialMG` and the separate native and multigroup material structures, from [@ilhamv]
 - Group transport techniques under `simulation.technique`, from [@ilhamv]
+- **Breaking:** Encapsulate MC/DC model building and execution within an explicit `mcdc.Simulation` instance, replacing the global simulation state and interface from [@ilhamv]
 - Modernize and reorganize the documentation around distinct user, API reference, theory, project, and developer paths; adopt the PyData Sphinx Theme; and expand the architecture and extension guidance from [@ilhamv]
 - Move model-specific finalization into simulation compilation and reserve runtime preparation for framework-level packing and execution setup from [@ilhamv]
-- **Breaking:** Encapsulate MC/DC model building and execution within an explicit `mcdc.Simulation` instance, replacing the global simulation state and interface from [@ilhamv]
 - Move regression tests from the custom `run.py` harness to pytest-based collection and reporting from [@massimolarsen]
-- **Breaking:** Declare Python 3.13 as the only currently supported and tested Python version
-- Adopt a three-month seasonal cycle for minor releases while continuing to publish patch releases as needed
+- **Breaking:** Require Python 3.11 or newer and designate Python 3.13 as the primary automatic test version, from [@ilhamv]
+- Run Black and Pyright with Python 3.14 while keeping Black output compatible with every supported Python version, from [@ilhamv]
+- Adopt a three-month seasonal cycle for minor releases while continuing to publish patch releases as needed, from [@ilhamv]
 
 ### Removed
 
-- Remove the legacy `install.sh` installation helper
+- Remove the legacy `install.sh` installation helper, from [@ilhamv]
 
 ## [0.14.2] - 2026-07-15
 
diff --git a/README.md b/README.md
index adeb2847d..fbf6cc806 100644
--- a/README.md
+++ b/README.md
@@ -24,6 +24,8 @@ Originally initiated by the Center for Exascale Monte Carlo Neutron Transport ([
 
 ## Installation
 
+MC/DC requires Python 3.11 or newer.
+
 Install the latest stable release from PyPI:
 
 ```bash
diff --git a/pyproject.toml b/pyproject.toml
index 32ccd9ab1..b370a26df 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -12,7 +12,7 @@ authors = [
 
 description = "A performant, scalable, and machine-portable Python-based Monte Carlo radiation transport code."
 readme = "README.md"
-requires-python = ">=3.13"
+requires-python = ">=3.11"
 license = "BSD-3-Clause"
 license-files = ["LICENSE"]
 
@@ -34,7 +34,10 @@ classifiers = [
   "Programming Language :: Python",
   "Programming Language :: Python :: 3",
   "Programming Language :: Python :: 3 :: Only",
+  "Programming Language :: Python :: 3.11",
+  "Programming Language :: Python :: 3.12",
   "Programming Language :: Python :: 3.13",
+  "Programming Language :: Python :: 3.14",
 
   "Operating System :: MacOS",
   "Operating System :: POSIX :: Linux",
@@ -80,7 +83,7 @@ Issues = "https://github.com/mcdc-project/mcdc/issues"
 source = "vcs"
 
 [tool.black]
-target-version = ["py313"]
+target-version = ["py311", "py312", "py313", "py314"]
 force-exclude = '''
 (
   mcdc/numba_types\.py
@@ -91,7 +94,7 @@ force-exclude = '''
 
 [tool.pyright]
 include = ["test/typecheck"]
-pythonVersion = "3.13"
+pythonVersion = "3.14"
 typeCheckingMode = "strict"
 
 [tool.pytest.ini_options]

From 3c03afd08cc0ca71117654cb66e7450e0adef128 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 18:44:53 +0700
Subject: [PATCH 192/202] python version compatibility update

---
 containers/Dockerfile.cuda | 2 +-
 containers/Dockerfile.rocm | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/containers/Dockerfile.cuda b/containers/Dockerfile.cuda
index c11fc878d..b7112543e 100644
--- a/containers/Dockerfile.cuda
+++ b/containers/Dockerfile.cuda
@@ -27,7 +27,7 @@ RUN wget -q https://github.com/conda-forge/miniforge/releases/latest/download/Mi
 
 ENV PATH="/opt/conda/bin:$PATH"
 
-# Install Python environment (matching Harmonize prereqs: CUDA=11.8, Numba>=0.60.0)
+# Install Python environment (matching Harmonize prerequisites: CUDA 11.8 and Numba 0.61 or newer)
 RUN conda install -y \
     gxx \
     python=3.13 \
diff --git a/containers/Dockerfile.rocm b/containers/Dockerfile.rocm
index c0d67f713..8ad296a17 100644
--- a/containers/Dockerfile.rocm
+++ b/containers/Dockerfile.rocm
@@ -27,7 +27,7 @@ RUN wget -q https://github.com/conda-forge/miniforge/releases/latest/download/Mi
 
 ENV PATH="/opt/conda/bin:$PATH"
 
-# Install Python environment (matching Harmonize prereqs: ROCm=6.0.0, Numba>=0.60.0)
+# Install Python environment (matching Harmonize prerequisites: ROCm 6.0.0 and Numba 0.61 or newer)
 RUN conda install -y \
     gxx \
     python=3.13 \

From ef73d244b458d72a7a703581be1cc12444c6a8fd Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 18:48:01 +0700
Subject: [PATCH 193/202] python version compatibility update

---
 .github/pull_request_template.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md
index abf14f19f..70d1226e8 100644
--- a/.github/pull_request_template.md
+++ b/.github/pull_request_template.md
@@ -19,8 +19,8 @@
     Put an `x` in all boxes once completed.
 -->
 
-- [ ] I have read the [contributing guide](https://mcdc.readthedocs.io/en/latest/contributing/index.html).
-- [ ] My code follows the [code style](https://mcdc.readthedocs.io/en/latest/contributing/index.html#code-styling) of this project.
+- [ ] I have read the [contributing guide](https://mcdc.readthedocs.io/en/dev/contributing/index.html).
+- [ ] My code follows the [code style](https://mcdc.readthedocs.io/en/dev/contributing/index.html#code-styling) of this project.
 - [ ] I have updated the documentation as needed. <!-- Delete if not applicable -->
 - [ ] I have updated `CHANGELOG.md` as needed. <!-- Delete if not applicable -->
 - [ ] I have added or updated tests to cover my changes. <!-- Delete if not applicable -->

From 31eaeb2c31f568ec5040d30c3e4b81e63e2310bc Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 18:50:17 +0700
Subject: [PATCH 194/202] finalize python compatibility runner and clearn up
 the others

---
 .github/workflows/black_lint.yml           |  4 +---
 .github/workflows/docker.yml               |  2 --
 .github/workflows/docs_test.yml            |  5 -----
 .github/workflows/publish-pypi.yml         |  2 +-
 .github/workflows/python_compatibility.yml | 24 ++++++++--------------
 .github/workflows/regression_test.yml      |  2 --
 .github/workflows/unit_test.yml            |  2 --
 7 files changed, 11 insertions(+), 30 deletions(-)

diff --git a/.github/workflows/black_lint.yml b/.github/workflows/black_lint.yml
index 7f31c9067..366d1174c 100644
--- a/.github/workflows/black_lint.yml
+++ b/.github/workflows/black_lint.yml
@@ -6,8 +6,6 @@ on:
 
 jobs:
   black-lint:
-    # Temporary suppression while validating Python compatibility on make_release.
-    if: github.ref_name != 'make_release' && github.head_ref != 'make_release'
     name: Lint with Black
     runs-on: ubuntu-latest
 
@@ -18,7 +16,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.13"
+          python-version: "3.14"
           cache: pip
 
       - name: Install Black
diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml
index 0977e5514..97f81d0bc 100644
--- a/.github/workflows/docker.yml
+++ b/.github/workflows/docker.yml
@@ -32,8 +32,6 @@ jobs:
   # Stage 0: Detect what changed (drives downstream job decisions)
   # ---------------------------------------------------------------------------
   changes:
-    # Temporary suppression while validating Python compatibility on make_release.
-    if: github.ref_name != 'make_release' && github.head_ref != 'make_release'
     name: Detect changes
     runs-on: ubuntu-latest
     outputs:
diff --git a/.github/workflows/docs_test.yml b/.github/workflows/docs_test.yml
index b71c7ee83..6e5fb85ea 100644
--- a/.github/workflows/docs_test.yml
+++ b/.github/workflows/docs_test.yml
@@ -7,8 +7,6 @@ on:
 
 jobs:
   build-docs:
-    # Temporary suppression while validating Python compatibility on make_release.
-    if: github.ref_name != 'make_release' && github.head_ref != 'make_release'
     runs-on: "ubuntu-latest"
     timeout-minutes: 60
 
@@ -33,10 +31,7 @@ jobs:
       - name: Install docs dependencies
         run: |
           python -m pip install --upgrade pip
-          # If you have extras for docs, use this:
           python -m pip install ".[docs]"
-          # Otherwise, something like:
-          # python -m pip install . sphinx sphinx-autodoc-typehints ...
           python -m pip list
 
       - name: Build the docs
diff --git a/.github/workflows/publish-pypi.yml b/.github/workflows/publish-pypi.yml
index 6d17f4b45..a8d3187d6 100644
--- a/.github/workflows/publish-pypi.yml
+++ b/.github/workflows/publish-pypi.yml
@@ -27,7 +27,7 @@ jobs:
         uses: actions/checkout@v4
         with:
           fetch-depth: 0
-      # Set up the Python version supported by this project.
+      # Set up the project's primary automatically tested Python version.
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
diff --git a/.github/workflows/python_compatibility.yml b/.github/workflows/python_compatibility.yml
index a2623da32..8ca813b40 100644
--- a/.github/workflows/python_compatibility.yml
+++ b/.github/workflows/python_compatibility.yml
@@ -2,9 +2,6 @@ name: Python Compatibility Tests
 
 on:
   workflow_dispatch:
-  # Temporary trigger for validating this workflow before it reaches the default branch.
-  push:
-    branches: [make_release]
 
 env:
   UCX_TLS: self,sm,tcp
@@ -17,7 +14,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.11", "3.12", "3.13", "3.14"]
+        python-version: ["3.11", "3.12", "3.14"]
 
     steps:
       - name: Checkout repository
@@ -37,20 +34,17 @@ jobs:
           pip install --upgrade pip
           pip install --no-binary=mpi4py mpi4py
 
-      - name: Relax the MC/DC Python requirement for exploratory testing
-        if: matrix.python-version == '3.11' || matrix.python-version == '3.12'
-        run: sed -i 's/requires-python = ">=3.13"/requires-python = ">=3.11"/' pyproject.toml
-
       - name: Install MC/DC
         id: install
         run: pip install -e ".[dev]"
 
-      #- name: Run unit tests
-      #  run: python -m pytest -v test/unit
+      - name: Run unit tests
+        run: python -m pytest -v test/unit
+
+      - name: Run regression tests (Python)
+        if: always() && steps.install.outcome == 'success'
+        run: python -m pytest -v test/regression
 
-      #- name: Run regression tests
-      #  if: always() && steps.install.outcome == 'success'
-      #  run: python -m pytest -v test/regression
-      
-      - name: Run regression tests
+      - name: Run regression tests (Numba)
+        if: always() && steps.install.outcome == 'success'
         run: python -m pytest -v test/regression --mode numba
diff --git a/.github/workflows/regression_test.yml b/.github/workflows/regression_test.yml
index c5c3fed60..6ed94566f 100644
--- a/.github/workflows/regression_test.yml
+++ b/.github/workflows/regression_test.yml
@@ -24,8 +24,6 @@ env:
 
 jobs:
   regression-test:
-    # Temporary suppression while validating Python compatibility on make_release.
-    if: github.ref_name != 'make_release' && github.head_ref != 'make_release'
     name: ${{ matrix.mode }} (py${{ matrix.python-version }})
     runs-on: ubuntu-latest
     timeout-minutes: ${{ matrix.timeout }}
diff --git a/.github/workflows/unit_test.yml b/.github/workflows/unit_test.yml
index 727b8d3cc..3da0b21a3 100644
--- a/.github/workflows/unit_test.yml
+++ b/.github/workflows/unit_test.yml
@@ -6,8 +6,6 @@ on:
 
 jobs:
   unit-test:
-    # Temporary suppression while validating Python compatibility on make_release.
-    if: github.ref_name != 'make_release' && github.head_ref != 'make_release'
     name: (py${{ matrix.python-version }})
     runs-on: ubuntu-latest
 

From 01e7817631a5364f37c6de4d3d2e69f9394ce048 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 18:50:35 +0700
Subject: [PATCH 195/202] python version compatibility update

---
 tools/data_library_generator/electron/README.md | 2 +-
 tools/data_library_generator/neutron/README.md  | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/tools/data_library_generator/electron/README.md b/tools/data_library_generator/electron/README.md
index 96b14caf2..f4f9d6b2c 100644
--- a/tools/data_library_generator/electron/README.md
+++ b/tools/data_library_generator/electron/README.md
@@ -100,5 +100,5 @@ only CDFs for EPRDATA14; sampling from the CDF is handled on the MC/DC side.
 ```
 
 ## See Also
-- [Continuous Energy Theory Guide](../../docs/source/theory/continuous_energy.rst)
+- [Continuous Energy Theory Guide](../../../docs/source/theory/continuous_energy.rst)
 - [Installation — CE Library Configuration](../../../docs/source/user_guide/getting_started/installation.rst)
diff --git a/tools/data_library_generator/neutron/README.md b/tools/data_library_generator/neutron/README.md
index 41d7c50ce..526fdacb2 100644
--- a/tools/data_library_generator/neutron/README.md
+++ b/tools/data_library_generator/neutron/README.md
@@ -76,5 +76,5 @@ For each ACE file in `$MCDC_ACELIB`, the generator:
 
 ## See Also
 
-- [Continuous Energy Theory Guide](../../docs/source/theory/continuous_energy.rst)
+- [Continuous Energy Theory Guide](../../../docs/source/theory/continuous_energy.rst)
 - [Installation — CE Library Configuration](../../../docs/source/user_guide/getting_started/installation.rst)

From d6e1d715c6f1a6dee36e22bb4f61bb8813572f6b Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 18:51:26 +0700
Subject: [PATCH 196/202] remove duplicate

---
 docs/source/project/publications.rst | 2 --
 1 file changed, 2 deletions(-)

diff --git a/docs/source/project/publications.rst b/docs/source/project/publications.rst
index c504117b0..2c770eac3 100644
--- a/docs/source/project/publications.rst
+++ b/docs/source/project/publications.rst
@@ -53,8 +53,6 @@ Hybrid Monte Carlo Transport
 
 - Pasmann, Sam, et al. "A quasi–Monte Carlo method with Krylov linear solvers for multigroup neutron transport simulations." Nuclear Science and Engineering 197.6 (2023): 1159-1173. https://www.tandfonline.com/doi/abs/10.1080/00295639.2022.2143704
 
-- Pasmann, Sam, et al. "A quasi–Monte Carlo method with Krylov linear solvers for multigroup neutron transport simulations." Nuclear Science and Engineering 197.6 (2023): 1159-1173. https://www.tandfonline.com/doi/abs/10.1080/00295639.2022.2143704
-
 - Pasmann, Samuel, et al. “iQMC: Iterative Quasi-Monte Carlo with Krylov Linear Solvers for k-Eigenvalue Neutron Transport Simulations.” In International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering. Niagara Falls, Ontario, Canada (2023). Preprint: https://arxiv.org/abs/2306.11600
 
 - Pasmann, Samuel, Ilham Variansyah, and R. G. McClarren. "Convergent transport source iteration calculations with Quasi-Monte Carlo." Transactions of the American Nuclear Society 124 (2021): 192-195.

From f5860390ea9775d3fdd5c9f83ad96b5c5e5ad5a4 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 18:57:55 +0700
Subject: [PATCH 197/202] python version compatibility update

---
 .../developer_guide/documentation/sphinx.rst     | 16 ++--------------
 1 file changed, 2 insertions(+), 14 deletions(-)

diff --git a/docs/source/developer_guide/documentation/sphinx.rst b/docs/source/developer_guide/documentation/sphinx.rst
index 5bb486700..4cd05814b 100644
--- a/docs/source/developer_guide/documentation/sphinx.rst
+++ b/docs/source/developer_guide/documentation/sphinx.rst
@@ -118,18 +118,6 @@ Make sure you're in ``mcdc/docs/``:
    Check your work: has your content been added or changed as you expected?
 #. Continue making changes to your local rst files, building locally, and launching the built html files until you're satisfied with how the website will look.
 
-.. warning::
-   In the process of creating MC/DC's documentation, ``autodoc`` *imports every python module that MC/DC imports*.
+The API reference imports MC/DC during the documentation build, so run a complete local build after changing package imports or dependencies.
 
-   This doesn't cause any issues when you build the webpages locally, because you already have all of MC/DC's requisite packages installed.
-
-   However, this *WILL* cause issues with our documentation website host, readthedocs.
-   Like you just did, readthedocs will checkout our repo and use Sphinx to build html files from our rst files, attempting to import all of MC/DC's packages along the way.
-   There are some python packages, like ``mpi4py``, that readthedocs is unable to import, causing the documentation build to fail.
-
-   **If you've added any new package imports to MC/DC's source code, add them to the** ``MOCK_MODULES`` **list in** ``mcdc/docs/source/conf.py``.
-
-   This will allow readthedocs to get past the imports without issue.
-
-
-Once you're satisfied with your changes and have added any new modules to ``conf.py``, submit a PR!
+Once you are satisfied with the local build, submit a PR.

From db1e8b99a10d51d20d071c5d161a0e29f482527b Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 18:58:57 +0700
Subject: [PATCH 198/202] one-sentence-per-line format

---
 docs/source/theory/continuous_energy.rst | 47 +++++++++---------------
 1 file changed, 17 insertions(+), 30 deletions(-)

diff --git a/docs/source/theory/continuous_energy.rst b/docs/source/theory/continuous_energy.rst
index 5691a4d1f..92eecef1b 100644
--- a/docs/source/theory/continuous_energy.rst
+++ b/docs/source/theory/continuous_energy.rst
@@ -40,7 +40,8 @@ Collision Physics
 
 CE collision processing implements full center-of-mass (COM) kinematics:
 
-- **Elastic scattering** (MT-2): Thermal motion of the target nucleus is sampled from a Maxwellian distribution parameterized by :math:`\beta = \sqrt{A m / (2 k_B T)}`, where :math:`A` is the mass ratio. Rejection sampling is used for the relative speed.
+- **Elastic scattering** (MT-2): Thermal motion of the target nucleus is sampled from a Maxwellian distribution parameterized by :math:`\beta = \sqrt{A m / (2 k_B T)}`, where :math:`A` is the mass ratio.
+  Rejection sampling is used for the relative speed.
 - **Inelastic scattering**: Multiple MT channels with tabulated energy-angle distributions (Kalbach-Mann, evaporation, Maxwellian, N-body, level scattering).
 - **Capture**: Particle is absorbed; implicit capture can be enabled as a variance reduction technique.
 - **Fission**: Secondary particles are emitted using :math:`\nu(E)/k_\text{eff}` scaling, with prompt and delayed components sampled separately.
@@ -55,9 +56,8 @@ Relativistic particle speed is computed as:
 Generating a Data Library from ACE Files
 -----------------------------------------
 
-MC/DC ships with a conversion tool in ``tools/data_library_generator/`` that reads
-standard ACE-format nuclear data files and writes them into MC/DC's per-nuclide
-HDF5 format.  This is the primary path for creating CE libraries.
+MC/DC ships with a conversion tool in ``tools/data_library_generator/neutron/`` that reads standard ACE-format nuclear data files and writes them into MC/DC's per-nuclide HDF5 format.
+This is the primary path for creating CE libraries.
 
 **Prerequisites:**
 
@@ -65,8 +65,7 @@ HDF5 format.  This is the primary path for creating CE libraries.
 
    pip install ACEtk h5py numpy tqdm
 
-You also need a set of ACE files (e.g., from `NJOY <http://www.njoy21.io/>`_ or
-an ENDF/B distribution).
+You also need a set of ACE files from a source such as `NJOY <http://www.njoy21.io/>`_ or an ENDF/B distribution.
 
 **Environment variables:**
 
@@ -88,12 +87,11 @@ an ENDF/B distribution).
    export MCDC_ACELIB=/path/to/ace/files
    export MCDC_LIB=/path/to/mcdc/library
 
-   cd tools/data_library_generator
+   cd tools/data_library_generator/neutron
    python generate.py
 
-By default the tool only converts nuclides that do not already have a corresponding
-HDF5 file in ``$MCDC_LIB``.  Use ``--rewrite`` to regenerate all files, or
-``--verbose`` for detailed per-nuclide output:
+By default, the tool converts only nuclides without a corresponding HDF5 file in ``$MCDC_LIB``.
+Use ``--rewrite`` to regenerate all files or ``--verbose`` for detailed per-nuclide output:
 
 .. code-block:: sh
 
@@ -101,26 +99,18 @@ HDF5 file in ``$MCDC_LIB``.  Use ``--rewrite`` to regenerate all files, or
 
 The generator processes each ACE file as follows:
 
-#. Reads the ACE header to determine nuclide identity (Z, A, isomeric state)
-   and temperature.
-#. Extracts the principal cross-section block (energy grid, elastic, capture,
-   fission, inelastic channels) and writes them as HDF5 datasets grouped by
-   reaction type (elastic scattering, capture, inelastic scattering, fission).
-#. Extracts angular distributions (tabulated cosine PDFs) and energy
-   distributions (level scattering, evaporation, Maxwellian, Kalbach-Mann,
-   N-body phase space, tabulated outgoing energy) for each reaction channel.
-#. For fissionable nuclides, extracts prompt/delayed :math:`\nu(E)` multiplicities,
-   delayed neutron precursor fractions, decay constants, and energy spectra.
+#. Reads the ACE header to determine nuclide identity and temperature.
+#. Extracts the principal cross-section block and writes HDF5 datasets grouped by reaction type.
+#. Extracts angular and energy distributions for each reaction channel.
+#. Extracts prompt and delayed :math:`\nu(E)` data, precursor fractions, decay constants, and energy spectra for fissionable nuclides.
 
-The resulting HDF5 file (e.g., ``U235-293.6K.h5``) is ready for use with
-``mcdc.Material()``.
+The resulting HDF5 file, such as ``U235-293.6K.h5``, is ready for use with ``mcdc.Material()``.
 
 
 Using CE Materials in an Input Deck
 ------------------------------------
 
-Once the library is generated, set the ``MCDC_LIB`` environment variable and
-define materials with ``mcdc.Material()``:
+Once the library is generated, set the ``MCDC_LIB`` environment variable and define materials with ``mcdc.Material()``:
 
 .. code-block:: python3
 
@@ -141,9 +131,7 @@ Note on External Data Sources
 ------------------------------
 
 MC/DC's internal HDF5 format is independent of the original data source.
-While the shipped tool converts from **ACE format**, users with data in other
-formats (e.g., OpenMC HDF5 nuclear data) can write their own converter
-following the same HDF5 schema used by ``generate.py``.
+The shipped tool converts ACE data, but users can implement converters for other formats by following the same HDF5 schema used by ``generate.py``.
 
 The key HDF5 structure expected by MC/DC is:
 
@@ -175,6 +163,5 @@ The key HDF5 structure expected by MC/DC is:
                ├── nu_delayed/
                └── delayed_neutron/ ...
 
-A converter from OpenMC's ``IncidentNeutron`` HDF5 format to this schema is
-a planned future addition.  Contributions are welcome — see
-`Issue #333 <https://github.com/mcdc-project/mcdc/issues/333>`_.
+A converter from OpenMC's ``IncidentNeutron`` HDF5 format to this schema is a planned future addition.
+Contributions are welcome through `Issue #333 <https://github.com/mcdc-project/mcdc/issues/333>`_.

From 8f63f85bbd10baedb500d94a083c1d4feb5a2af8 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 19:01:08 +0700
Subject: [PATCH 199/202] python-compatibility update. one-sentence-per-line
 format

---
 .../contributing/container_development.rst    | 11 +--
 .../contributing/continuous_integration.rst   |  2 +
 docs/source/contributing/index.rst            | 72 +++++++++++--------
 3 files changed, 50 insertions(+), 35 deletions(-)

diff --git a/docs/source/contributing/container_development.rst b/docs/source/contributing/container_development.rst
index 7dbfd7334..892fb8bc7 100644
--- a/docs/source/contributing/container_development.rst
+++ b/docs/source/contributing/container_development.rst
@@ -40,7 +40,7 @@ Option A:
 
 .. code-block:: bash
 
-    apptainer build --sandbox mcdc_sandbox docker://ghcr.io/cement-psaap/mcdc:dev
+    apptainer build --sandbox mcdc_sandbox docker://ghcr.io/mcdc-project/mcdc:dev
 
 Option B:
 
@@ -127,8 +127,8 @@ On Apple Silicon:
 .. code-block:: bash
 
     docker build --platform linux/amd64 -f containers/Dockerfile -t mcdc:dev-amd64 .
-    docker tag mcdc:dev-amd64 ghcr.io/cement-psaap/mcdc:dev
-    docker push ghcr.io/cement-psaap/mcdc:dev
+    docker tag mcdc:dev-amd64 ghcr.io/mcdc-project/mcdc:dev
+    docker push ghcr.io/mcdc-project/mcdc:dev
 
 .. rubric:: Making the Package Public
 
@@ -143,5 +143,6 @@ File Overview
 
     containers/
     ├── Dockerfile
-    ├── docker-compose.yml
-    └── README.md
+    ├── Dockerfile.cuda
+    ├── Dockerfile.rocm
+    └── docker-compose.yml
diff --git a/docs/source/contributing/continuous_integration.rst b/docs/source/contributing/continuous_integration.rst
index 16860c4f4..a1493f561 100644
--- a/docs/source/contributing/continuous_integration.rst
+++ b/docs/source/contributing/continuous_integration.rst
@@ -9,6 +9,8 @@ We use `GitHub Actions <https://github.com/mcdc-project/mcdc/actions>`_ to host
 We run pure python unit tests and regression testing in pure Python, pure Python + MPI, numba, numba + MPI, and numba+GPU+harmonize.
 When running regression tests we compare small particle count outputs to saved files in the testing directory.
 If the RNG seed has not changed the results should be deterministic.
+The Black workflow runs on Python 3.14 and formats for all supported Python versions, while Pyright checks the typed public API against Python 3.14.
+Automatic runtime tests use Python 3.13, while maintainers manually test Python 3.11, 3.12, and 3.14 in Python and Numba modes before a release.
 
 
 GPU COE Machine
diff --git a/docs/source/contributing/index.rst b/docs/source/contributing/index.rst
index 698db5278..78ba61aaf 100644
--- a/docs/source/contributing/index.rst
+++ b/docs/source/contributing/index.rst
@@ -15,12 +15,14 @@ For software architecture and documentation practices, see the :doc:`../develope
 
 For implementation guidance specific to compiled transport functions, see :doc:`../developer_guide/extending/writing_numba_compatible_transport_code`.
 
-Contributions target the ``dev`` branch. To prepare a development checkout:
+Contributions target the ``dev`` branch.
+Prepare a development checkout with the following steps:
 
 #. Fork ``mcdc-project/mcdc`` to your GitHub account.
 #. ``git clone git@github.com:<YOUR_GITHUB>/mcdc.git``
 #. ``git switch dev``
-#. Run the installation script to install MC/DC as an editable package.
+#. Create and activate a Python 3.14 environment for contributor tooling.
+#. ``python -m pip install -e ".[dev]"``
 
 Development Workflow
 --------------------
@@ -42,18 +44,28 @@ Please note our `code of conduct <https://github.com/mcdc-project/mcdc/blob/dev/
 Code Styling
 ------------
 
-Our code is auto-linted for the `Black code style <https://black.readthedocs.io/en/stable/the_black_code_style/current_style.html>`_.
-Your contributions will not be merged unless you follow this code style.
-It's pretty easy to do this locally, just run,
+MC/DC uses the `Black code style <https://black.readthedocs.io/en/stable/the_black_code_style/current_style.html>`_.
+Run Black with Python 3.14 from the repository root before submitting a contribution:
 
 .. code-block:: sh
 
-
-    pip install black
     black .
 
+Black is included in the ``dev`` optional dependency group installed during development setup.
+Black formats for every supported Python version listed in ``pyproject.toml``.
+
+Public API Typing
+-----------------
+
+MC/DC ships inline type information for its public Python interface.
+Run Pyright from the repository root after changing a public class, annotation, or export:
+
+.. code-block:: sh
 
-in the top level MC/DC directory and all necessary changes will be automatically made for you.
+    pyright
+
+The strict public API checks are defined in ``test/typecheck/public_api.py``.
+Pyright checks the public API against Python 3.14.
 
 ---------
 Debugging
@@ -72,11 +84,16 @@ The most useful set of debug options for MC/DC can be enabled with
 Which will toggle the following debug and compiler options in Numba:
 
 * ``DISABLE_JIT=False`` turns on the jitter
-* ``NUMBA_OPT=0`` Forces the compilers to form un-optimized code (other options for this are ``1``, ``2``, and ``3`` with ``3`` being the most optimized). This option might need to be changed if errors only result from more optimization.
-* ``DEBUG=False`` turns on all debugging options. This is still disabled in ``mcdc numba_debug`` as it will print ALOT of info on your terminal screen
+* ``NUMBA_OPT=0`` forces the compilers to form unoptimized code, while values ``1``, ``2``, and ``3`` enable increasing optimization.
+  Change this option when an error appears only at higher optimization levels.
+* ``DEBUG=False`` controls all debugging options.
+  MC/DC leaves this disabled in ``numba_debug`` because it produces extensive terminal output.
 * ``NUMBA_FULL_TRACEBACKS=1`` allows errors from sub-packages to be printed (i.e. Numpy)
-* ``NUMBA_BOUNDSCHECK=1`` numba will check vectors for bounds errors. If this is disabled it bound errors will result in a ``seg_fault``. This in consort with the previous option allows for the exact location of a bound error to be printed from Numpy subroutines
-* ``NUMBA_DEBUG_NRT=1`` enables the `Numba run time (NRT) statistics counter <https://numba.readthedocs.io/en/stable/developer/numba-runtime.html>`_ This helps with debugging memory leaks.
+* ``NUMBA_BOUNDSCHECK=1`` makes Numba check vectors for bounds errors.
+  Without this check, a bounds error can result in a segmentation fault.
+  Together with full tracebacks, this option identifies the location of a bounds error in NumPy operations.
+* ``NUMBA_DEBUG_NRT=1`` enables the `Numba runtime statistics counter <https://numba.readthedocs.io/en/stable/developer/numba-runtime.html>`_.
+  This counter helps diagnose memory leaks.
 * ``NUMBA_DEBUG_TYPEINFER= 1`` print out debugging information about type inferences that numba might need to make if a function is ill-defined
 * ``NUMBA_ENABLE_PROFILING=1`` enables profiler use
 * ``NUMBA_DUMP_CFG=1`` prints out a control flow diagram
@@ -103,7 +120,8 @@ To disable caching, omit the ``--caching`` flag (the default).
 Alternatively a developer could delete the ``__pycache__`` directory or other cache directory which is system dependent (`see more about clearing the numba cache <https://numba.readthedocs.io/en/stable/developer/caching.html>`_)
 
 
-At some point MC/DC will enable `Numba's Ahead of Time compilation abilities <https://numba.readthedocs.io/en/stable/user/pycc.html>`_. But the core development team is holding off until scheduled `upgrades to AOT functionality in Numba are implemented <https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-numba-pycc>`_.
+MC/DC may eventually enable `Numba's ahead-of-time compilation capabilities <https://numba.readthedocs.io/en/stable/user/pycc.html>`_.
+The core development team is waiting for planned `upgrades to Numba's AOT functionality <https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-numba-pycc>`_.
 However if absolutely required by users numba does allow for some `cache sharing <https://numba.readthedocs.io/en/stable/developer/caching.html>`_.
 
 ------------------
@@ -130,18 +148,10 @@ Testing
 
 See :doc:`continuous_integration` for more information on how we run these tests automatically.
 
-MC/DC has a robust testing suite that your changes must be able to pass before a PR is accepted.
-Unit tests for functions that have them are ran in a pure python from.
-Mostly this is for ensuring input operability
-A regression test suite (including models with analytical and experimental solutions) is provided to ensure accuracy and precision of MC/DC.
-
-Our test suite runs on every PR, and Push.
-Our github based CI runs for, 
-
-* linux-64 (x86)
-* osx-64 (x86, intel based macs)
-
-while we do not have continuous integration we have validated MC/DC on other systems.
+MC/DC has unit and regression test suites that contributions must pass before they are accepted.
+Unit tests exercise focused behavior in both Python and Numba modes.
+Regression tests compare representative simulations against saved reference results.
+GitHub Actions runs the CPU suites on Linux, and a self-hosted runner provides GPU regression coverage.
 
 To run the default fast unit-test suite locally, run,
 
@@ -162,7 +172,8 @@ To run the regression tests locally, run,
     python -m pytest test/regression <OPTION_FLAG(s)>
 
 
-and all the tests will run. Various option ``OPTION_FLAG`` are accepted to control the tests ran,
+The command runs all regression tests.
+The following options control test selection and execution:
 
 * Run a specific test (with wildcard ``*`` support): ``--name=<test_name>``
 * Skip a specific test (with wildcard ``*`` support): ``--skip=<test_name>``
@@ -171,11 +182,12 @@ and all the tests will run. Various option ``OPTION_FLAG`` are accepted to contr
 * Run in multiple MPI ranks (currently support ``mpiexec`` and ``srun``): ``--mpiexec=<number of ranks>``
 * Run with Slurm ``srun`` instead of ``mpiexec``: ``--srun=<number of ranks>``
 
-Note that flags can be combined. To add a new test:
+The flags can be combined.
+Add a new test with the following steps:
 
-#. Create a folder. The name of the folder will be the test name.
-#. Add the input file. Name it`input.py`.
-#. Add the answer key file. Name it `answer.h5`.
+#. Create a folder whose name identifies the test.
+#. Add the input file as ``input.py``.
+#. Add the answer key as ``answer.h5``.
 #. Make sure that the number of particles run is large enough for a good test.
 #. If the test runs longer than 5 seconds, consider decreasing the number of particles.
 

From b62e4851e70bb5627b0242e4873e23182ebab918 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 19:01:42 +0700
Subject: [PATCH 200/202] python-compatibility update. one-sentence-per-line
 format

---
 docs/source/user_guide/container.rst          |  47 +++---
 docs/source/user_guide/faq.rst                |  46 +++---
 .../getting_started/installation.rst          | 142 +++++++-----------
 docs/source/user_guide/troubleshooting.rst    |  51 ++-----
 4 files changed, 105 insertions(+), 181 deletions(-)

diff --git a/docs/source/user_guide/container.rst b/docs/source/user_guide/container.rst
index 2089bae41..a5b7aef4c 100644
--- a/docs/source/user_guide/container.rst
+++ b/docs/source/user_guide/container.rst
@@ -4,17 +4,14 @@ MC/DC Container Guide
 What Are Containers?
 --------------------
 
-A container is a lightweight, portable package that bundles an application
-together with everything it needs to run: code, libraries, system tools,
-and settings. Think of it like a shipping container — no matter what ship
-(computer) carries it, the contents inside stay the same.
+A container is a lightweight, portable package that bundles an application with its code, libraries, system tools, and settings.
+Like a shipping container, it keeps its contents consistent across host systems.
 
 **Why does this matter for MC/DC?**
 
-Installing MC/DC requires Python, MPI, Numba, and many other dependencies.
-Getting all of these working together — especially on HPC systems where you
-don't have admin access — can be painful. A container solves this by giving
-you a pre-built environment where everything is already installed and tested.
+Installing MC/DC requires Python, MPI, Numba, and other dependencies.
+Coordinating these dependencies can be difficult on HPC systems without administrator access.
+A container provides a pre-built environment where the dependencies are already installed and tested.
 
 Tested Platforms
 ----------------
@@ -33,32 +30,30 @@ Tested Platforms
 | COE (OSU)   | Rocky 8.10 | x86_64 | Apptainer 1.4.5    | ✓      |
 +-------------+------------+--------+--------------------+--------+
 
-All platforms produce identical containers: Debian 13, Python 3.13,
-MPICH 4.2.1, MC/DC 0.12.0.
+The published CPU image contains the current MC/DC branch build, Python 3.13, MPICH, and the development tools needed to run the test suites.
 
 Getting Started (New Users)
 ---------------------------
 
-This section is for anyone who just wants to **run MC/DC** in a container.
+This section is for anyone who wants to **run MC/DC** in a container.
 No prior container experience needed.
 
 Step 1: Pull the Pre-Built Image
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-You don't need to build anything. A ready-to-use image is available on
-the GitHub Container Registry.
+You do not need to build the image because a ready-to-use image is available on the GitHub Container Registry.
 
 .. rubric:: Local Machine (Docker)
 
-First, install Docker Desktop if you haven't already. Then open a terminal
-and run:
+Install Docker Desktop, open a terminal, and run:
 
 .. code-block:: bash
 
-    docker pull ghcr.io/cement-psaap/mcdc:dev
-    docker run --rm -it ghcr.io/cement-psaap/mcdc:dev
+    docker pull ghcr.io/mcdc-project/mcdc:dev
+    docker run --rm -it ghcr.io/mcdc-project/mcdc:dev
 
-You are now inside the container. Try:
+You are now inside the container.
+Try importing MC/DC:
 
 .. code-block:: bash
 
@@ -68,17 +63,17 @@ Type ``exit`` to leave the container.
 
 .. rubric:: LLNL Systems — Tuolumne, Tioga, Dane (Podman)
 
-Podman is already installed on LLNL systems. It works just like Docker.
+Podman is already installed on LLNL systems.
+It uses the same commands as Docker in these examples.
 
 .. code-block:: bash
 
-    podman pull ghcr.io/cement-psaap/mcdc:dev
-    podman run --rm -it ghcr.io/cement-psaap/mcdc:dev
+    podman pull ghcr.io/mcdc-project/mcdc:dev
+    podman run --rm -it ghcr.io/mcdc-project/mcdc:dev
 
 .. note::
 
-    If you see ``lsetxattr: operation not supported``,
-    see *LLNL Storage Setup* in Part 2.
+    If you see ``lsetxattr: operation not supported``, see *LLNL Storage Setup* in Part 2.
 
 .. rubric:: OSU Systems — COE (Apptainer)
 
@@ -86,7 +81,7 @@ Apptainer is already installed on COE.
 
 .. code-block:: bash
 
-    apptainer build --sandbox mcdc_sandbox docker://ghcr.io/cement-psaap/mcdc:dev
+    apptainer build --sandbox mcdc_sandbox docker://ghcr.io/mcdc-project/mcdc:dev
     apptainer exec mcdc_sandbox python -c "import mcdc; print('MC/DC OK')"
 
 .. note::
@@ -100,8 +95,8 @@ Step 2: Run Your Simulation
 
 .. code-block:: bash
 
-    docker run --rm -v $(pwd):/work -w /work mcdc:dev python input.py
-    docker run --rm mcdc:dev mpirun -n 4 python input.py
+    docker run --rm -v $(pwd):/work -w /work ghcr.io/mcdc-project/mcdc:dev python input.py
+    docker run --rm ghcr.io/mcdc-project/mcdc:dev mpirun -n 4 python input.py
 
 For Podman, replace ``docker`` with ``podman``.
 
diff --git a/docs/source/user_guide/faq.rst b/docs/source/user_guide/faq.rst
index 49170a262..57d2aa029 100644
--- a/docs/source/user_guide/faq.rst
+++ b/docs/source/user_guide/faq.rst
@@ -9,20 +9,16 @@ General
 
 **What Python versions does MC/DC support?**
 
-MC/DC supports Python 3.13.
+MC/DC supports Python 3.11 and newer.
 
 **What platforms are supported?**
 
-MC/DC is validated on linux-64 (x86), win-64, osx-64 (Intel), osx-arm64 (Apple Silicon),
-linux-ppc64 (IBM POWER9), linux-nvidia-cuda, and linux-amd-rocm.
+MC/DC is validated on linux-64 (x86), win-64, osx-64 (Intel), osx-arm64 (Apple Silicon), linux-ppc64 (IBM POWER9), linux-nvidia-cuda, and linux-amd-rocm.
 
 **Should I use pip or conda to install MC/DC?**
 
-For **personal machines and simple setups**, ``pip`` inside a ``venv`` is the easiest route
-(see :ref:`user_guide/getting_started/installation:Installing with pip`).
-For **HPCs or non-standard hardware** (e.g., POWER9 on Lassen, or when mpi4py is
-troublesome), a **conda environment** with the ``install.sh`` script is more robust
-(see :ref:`user_guide/getting_started/installation:Installing MC/DC via conda`).
+For **personal machines and simple setups**, ``pip`` inside a ``venv`` is the easiest route (see :ref:`user_guide/getting_started/installation:Installing with pip`).
+For **HPCs or non-standard hardware**, a **conda environment** can provide more robust environment management while pip installs MC/DC (see :ref:`user_guide/getting_started/installation:Installing MC/DC via conda`).
 
 .. list-table:: pip vs. conda at a glance
    :widths: 30 35 35
@@ -42,15 +38,13 @@ troublesome), a **conda environment** with the ``install.sh`` script is more rob
      - Excellent
    * - MPI support
      - Needs system MPI
-     - Can build mpi4py from source via ``install.sh``
+     - Can isolate an ``mpi4py`` build matched to the system MPI
 
 **Where can I find cross-section data for continuous-energy simulations?**
 
 CE data libraries are provided to CEMeNT members via an internal repository.
 Due to export controls they cannot be publicly distributed.
-If you need cross-section data, we recommend using
-`OpenMC <https://docs.openmc.org>`_ or `NJOY <http://www.njoy21.io/>`_ to generate it,
-then converting to MC/DC format with the tool in ``tools/data_library_generator/``.
+If you need cross-section data, we recommend using `OpenMC <https://docs.openmc.org>`_ or `NJOY <http://www.njoy21.io/>`_ to generate it, then converting it to MC/DC format with the tool in ``tools/data_library_generator/neutron/``.
 See :ref:`install-data-library` for setup instructions.
 
 Installation
@@ -79,22 +73,18 @@ Load the correct MPI module first, then install from source:
    module load <mpi_module>        # e.g., mvapich2, openmpi, spectrum-mpi
    CC=mpicc pip install --no-binary mpi4py mpi4py
 
-Or use the conda path with ``bash install.sh --hpc``, which handles this automatically.
-See :ref:`user_guide/troubleshooting:Building mpi4py from Source` for more
-details.
+See :ref:`user_guide/troubleshooting:Building mpi4py from Source` for more details.
 
 **I get Numba version errors or** ``TypingError`` **on older Numba versions.**
 
-MC/DC requires **Numba >= 0.60.0**.
+MC/DC requires **Numba >= 0.61.0**.
 If you are on an older version, upgrade:
 
 .. code-block:: sh
 
-   pip install 'numba>=0.60.0'
+   pip install 'numba>=0.61.0'
 
-If your system constrains the Numba version (e.g., due to CUDA toolkit compatibility),
-see :ref:`user_guide/troubleshooting:Numba Version Compatibility` for patching
-guidance.
+If your system constrains the Numba version, see :ref:`user_guide/troubleshooting:Numba Version Compatibility` for compatibility guidance.
 
 Running Simulations
 -------------------
@@ -105,15 +95,15 @@ Running Simulations
 
    mpiexec -n <nprocs> python input.py --mode=numba
 
-On HPCs, use the appropriate launcher (``srun``, ``jsrun``, ``flux run``).
-See :ref:`user_guide/execution/batch_systems:Batch Job Scripts` for ready-to-use
-templates.
+On HPCs, use the appropriate launcher, such as ``srun``, ``jsrun``, or ``flux run``.
+See :ref:`user_guide/execution/batch_systems:Batch Job Scripts` for ready-to-use templates.
 
 **My simulation is very slow — what should I check?**
 
-#. Are you running in ``--mode=numba``?  Python mode is orders of magnitude slower.
-#. First Numba run incurs JIT compilation overhead (15–80 s).
-   Subsequent runs with ``--caching`` are much faster.
+#. Are you running in ``--mode=numba``?
+   Python mode is orders of magnitude slower.
+#. The first Numba run incurs JIT compilation overhead of approximately 15–80 seconds.
+#. Subsequent runs with ``--caching`` are much faster.
 #. Check your particle count — start small and scale up.
 
 **I see** ``SyntaxWarning: invalid escape sequence`` **on import.**
@@ -137,9 +127,7 @@ Use ``h5py`` to read them:
        print(list(f.keys()))                    # ['runtime', 'tallies']
        print(list(f["tallies"].keys()))          # list of tally names
 
-See the post-processing section in
-:ref:`user_guide/getting_started/first_simulation:First MC/DC Simulation` for a complete
-example.
+See the post-processing section in :ref:`user_guide/getting_started/first_simulation:First MC/DC Simulation` for a complete example.
 
 **What visualization tools work with MC/DC output?**
 
diff --git a/docs/source/user_guide/getting_started/installation.rst b/docs/source/user_guide/getting_started/installation.rst
index 8218a35b4..12cfcecc1 100644
--- a/docs/source/user_guide/getting_started/installation.rst
+++ b/docs/source/user_guide/getting_started/installation.rst
@@ -4,12 +4,11 @@
 Installation
 ============
 
-Whether installing MC/DC as a user or from source as a developer, 
-we recommend doing so using an environment manager like venv or conda.
-This will avoid the need for any admin access and keep dependencies clean.
+Use an environment manager such as venv or conda when installing MC/DC as a user or developer.
+An isolated environment avoids administrator access and keeps dependencies clean.
 
-In general, :ref:`creating-a-venv-environment` and :ref:`installing-with-pip` is easier and recommended.
-Creating a conda environment and :ref:`installing-with-conda` is more robust and reliable, but is also more difficult. 
+In general, :ref:`creating-a-venv-environment` and :ref:`installing-with-pip` are the easiest options.
+Creating a conda environment and :ref:`installing-with-conda` requires more steps but can be more robust on specialized systems.
 A conda environment is necessary to install MC/DC on LLNL's Lassen machine.
 
 
@@ -20,29 +19,24 @@ A conda environment is necessary to install MC/DC on LLNL's Lassen machine.
 Creating a venv environment
 ---------------------------
 
-Python `virtual environments <https://docs.python.org/3/library/venv.html>`_ are the easy and 
-recommended way to get MC/DC operating on personal machines as well as HPCs;
-all you need is a working Python version with venv installed.
-Particularly on HPCs, using a Python virtual environment is convenient because
-system admins will have already configured venv and the pip within it to load packages and dependencies
-from the proper sources. 
-HPCs often use a module system, so before doing anything else, 
-``module load python/<version_number>``.
+Python `virtual environments <https://docs.python.org/3/library/venv.html>`_ are the recommended way to run MC/DC on personal machines and HPC systems.
+MC/DC supports Python 3.11 and newer, and the selected Python installation must provide ``venv``.
+On HPC systems, administrators often provide Python and its package sources through a module system, so load a supported module such as ``python/3.13`` before creating the environment.
 
-A python virtual environment can (usually) be created using
+Create a Python virtual environment with:
 
 .. code-block:: sh
 
     python -m venv <name_of_venv>
 
-Once you have created a venv, you will need to activate it
+Activate the environment after creating it:
 
 .. code-block:: sh
 
     source <name_of_venv>/bin/activate
 
-and will need to do so every time a new terminal instance is launched.
-Once your environment is active, you can move on to :ref:`installing-with-pip`.
+Activate the environment in each new terminal session before using MC/DC.
+Once the environment is active, continue to :ref:`installing-with-pip`.
 
 
 .. _installing-with-pip:
@@ -50,12 +44,9 @@ Once your environment is active, you can move on to :ref:`installing-with-pip`.
 -------------------
 Installing with pip
 -------------------
-Assuming you have a working Python environment, you can install using pip. 
-Doing so within an active venv or conda environment avoids the need for any admin access
-and keeps dependencies clean.
+Install MC/DC with pip inside an active venv or conda environment to avoid administrator access and keep dependencies isolated.
 
-If you would like to run MC/DC as published in the main branch *and* 
-do not need to develop in MC/DC, you can install from PyPI: 
+Install the latest stable release from PyPI when you do not need to modify MC/DC:
  
 .. code-block:: sh
 
@@ -64,17 +55,14 @@ do not need to develop in MC/DC, you can install from PyPI:
 ----------------------
 Installing from Source
 ----------------------
-If you would like to execute a version of MC/DC from a specific branch or 
-*do* plan to develop in MC/DC, you'll need to install from source: 
+Install MC/DC from source when you need a specific branch or plan to contribute changes:
+Use Python 3.14 for a contributor environment that will run Black locally; runtime-only source installations may use any supported Python version.
 
 #. Clone the MC/DC repository: ``git clone https://github.com/mcdc-project/mcdc.git``
-#. Go to your new MC/DC directory: ``cd MCDC``
-#. Install the package from your MC/DC files: ``pip install -e .``
+#. Enter the repository: ``cd mcdc``
+#. Install MC/DC and its development tools: ``python -m pip install -e ".[dev]"``
 
-This should install all needed dependencies without a hitch. 
-The `-e` flag installs MC/DC as an editable package, meaning that any changes
-you make to the MC/DC source files, including checking out a different
-branch,  will be immediately reflected without needing to do any re-installation.
+The ``-e`` flag installs MC/DC as an editable package, so source changes and branch switches take effect without reinstalling the package.
 
 .. _installing-with-conda:
 
@@ -82,15 +70,11 @@ branch,  will be immediately reflected without needing to do any re-installation
 Installing MC/DC via conda
 --------------------------
 
-Conda is the most robust (works even on bespoke systems) option to install MC/DC.
-`Conda <https://conda.io/en/latest/>`_ is an open source package and environment management system 
-that runs on Windows, macOS, and Linux. It allows for easy installing and switching between multiple
-versions of software packages and their dependencies. 
-Conda is really useful on systems with non-standard hardware (e.g. not x86 CPUs) like Lassen, where
-mpi4py is often the most troublesome dependency. 
+`Conda <https://conda.io/en/latest/>`_ provides robust environment management on systems with non-standard hardware or constrained software stacks.
+It is particularly useful on HPC systems such as Lassen, where ``mpi4py`` must match the system MPI implementation.
 
-First, ``conda`` should be installed with `Miniconda <https://docs.conda.io/en/latest/miniconda.html>`_
-or `Anaconda <https://www.anaconda.com/>`_. HPC instructions: 
+Install conda with `Miniconda <https://docs.conda.io/en/latest/miniconda.html>`_ or `Anaconda <https://www.anaconda.com/>`_.
+The following commands install Miniconda on selected HPC architectures.
 
 `Dane <https://hpc.llnl.gov/hardware/compute-platforms/dane>`_ (LLNL, x86_64), 
 
@@ -108,46 +92,35 @@ or `Anaconda <https://www.anaconda.com/>`_. HPC instructions:
     bash Miniconda3-latest-Linux-ppc64le.sh
 
 
-Then create and activate a new conda environment called *mcdc-env* in
-which to install MC/DC.
-MC/DC supports Python 3.13:
+The following example creates and activates a Python 3.13 conda environment named ``mcdc-env``:
 
 .. code-block:: sh
 
     conda create -n mcdc-env python=3.13
     conda activate mcdc-env
 
-Then, MC/DC can be installed from source by first cloning the MC/DC repository:
+Clone MC/DC and enter the repository:
 
 .. code-block:: sh
 
     git clone https://github.com/mcdc-project/mcdc.git
-    cd MCDC
+    cd mcdc
 
-then using the the ``install.sh`` within it. The install script will
-build MC/DC and all of its dependencies and execute any necessary patches.
-This has been tested on Quartz, Dane, Tioga, Lassen, and Apple M2. 
-The ``install.sh`` script **will fail outside of a conda environment**.
-
-On HPC machines, the script will install mpi4py 
-`from source <https://mpi4py.readthedocs.io/en/stable/install.html#using-distutils>`_.
-This means that all appropriate modules must be loaded prior to executing.
-
-On Quartz, the default modules are sufficient (``intel-classic`` and ``mvapich2``). 
-On Lassen, ``module load gcc/8 cuda/11.8``. Then, 
+On an HPC system, load the appropriate MPI module and build ``mpi4py`` against that implementation before installing MC/DC:
 
 .. code-block:: sh
 
-    bash install.sh --hpc
-
+    module load <mpi_module>
+    CC=mpicc python -m pip install --no-cache-dir --no-binary=mpi4py mpi4py
+    python -m pip install -e ".[dev]"
 
-On local machines, mpi4py will be installed using conda,
+On a local machine where pip can provide a compatible ``mpi4py`` installation, install MC/DC directly:
 
 .. code-block:: sh
 
-    bash install.sh 
+    python -m pip install -e ".[dev]"
 
-To confirm that everything is properly installed, execute ``pytest`` from the MCDC directory. 
+Run ``python -m pytest`` from the repository root to verify the installation.
 
 .. _installing-via-containers:
 
@@ -155,18 +128,16 @@ To confirm that everything is properly installed, execute ``pytest`` from the MC
 Installing via Containers
 --------------------------
 
-For container-based installation and execution, see
-:doc:`../container`.
+For container-based installation and execution, see :doc:`../container`.
 
 .. _install-data-library:
 
------------------------------------------
-Generating a Data Library from ACE Files
------------------------------------------
+-------------------------------------------------
+Generating a Neutron Data Library from ACE Files
+-------------------------------------------------
 
-MC/DC ships with a conversion tool in ``tools/data_library_generator/`` that reads
-standard ACE-format nuclear data files and writes them into MC/DC's per-nuclide
-HDF5 format.  This is the primary path for creating CE libraries.
+MC/DC ships with a neutron conversion tool in ``tools/data_library_generator/neutron/`` that reads standard ACE-format nuclear data files and writes them into MC/DC's per-nuclide HDF5 format.
+This is the primary path for creating continuous-energy neutron libraries.
 
 **Prerequisites:**
 
@@ -174,8 +145,7 @@ HDF5 format.  This is the primary path for creating CE libraries.
 
    pip install ACEtk h5py numpy tqdm
 
-You also need a set of ACE files (e.g., from `NJOY <http://www.njoy21.io/>`_ or
-an ENDF/B distribution).
+You also need a set of ACE files from a source such as `NJOY <http://www.njoy21.io/>`_ or an ENDF/B distribution.
 
 **Environment variables:**
 
@@ -197,12 +167,11 @@ an ENDF/B distribution).
    export MCDC_ACELIB=/path/to/ace/files
    export MCDC_LIB=/path/to/mcdc/library
 
-   cd tools/data_library_generator
+   cd tools/data_library_generator/neutron
    python generate.py
 
-By default the tool only converts nuclides that do not already have a corresponding
-HDF5 file in ``$MCDC_LIB``.  Use ``--rewrite`` to regenerate all files, or
-``--verbose`` for detailed per-nuclide output:
+By default, the tool converts only nuclides without a corresponding HDF5 file in ``$MCDC_LIB``.
+Use ``--rewrite`` to regenerate all files or ``--verbose`` for detailed per-nuclide output:
 
 .. code-block:: sh
 
@@ -210,16 +179,10 @@ HDF5 file in ``$MCDC_LIB``.  Use ``--rewrite`` to regenerate all files, or
 
 The generator processes each ACE file as follows:
 
-#. Reads the ACE header to determine nuclide identity (Z, A, isomeric state)
-   and temperature.
-#. Extracts the principal cross-section block (energy grid, elastic, capture,
-   fission, inelastic channels) and writes them as HDF5 datasets grouped by
-   reaction type (elastic scattering, capture, inelastic scattering, fission).
-#. Extracts angular distributions (tabulated cosine PDFs) and energy
-   distributions (level scattering, evaporation, Maxwellian, Kalbach-Mann,
-   N-body phase space, tabulated outgoing energy) for each reaction channel.
-#. For fissionable nuclides, extracts prompt/delayed :math:`\nu(E)` multiplicities,
-   delayed neutron precursor fractions, decay constants, and energy spectra.
+#. Reads the ACE header to determine nuclide identity (Z, A, isomeric state) and temperature.
+#. Extracts the principal cross-section block and writes HDF5 datasets grouped by reaction type.
+#. Extracts angular and energy distributions for each reaction channel.
+#. Extracts prompt and delayed :math:`\nu(E)` data, precursor fractions, decay constants, and energy spectra for fissionable nuclides.
 
 The resulting HDF5 file (e.g., ``U235-293.6K.h5``) is ready for use with ``mcdc.Material()``.
 
@@ -230,16 +193,14 @@ GPU Operability (MC/DC+Harmonize)
 
 MC/DC supports most of its Numba enabled features for GPU compilation and execution.
 When targeting GPUs, MC/DC uses the `Harmonize <https://github.com/CEMeNT-PSAAP/harmonize>`_ library as its GPU runtime, a.k.a. the thing that actually executes MC/DC functions.
-How Harmonize works gets a little involved, but in short, 
-Harmonize acts as MC/DC's GPU runtime by using two major scheduling schemes: an event schedular similar to those implemented in OpenMC and Shift, plus a novel scheduler.
+Harmonize provides an event scheduler similar to those implemented in OpenMC and Shift, along with a novel asynchronous scheduler.
 For more information on Harmonize and how we compile MC/DC with it, see this `TOMACs article describing the async scheduler <https://doi.org/10.1145/3626957>`_ or our publications in American Nuclear Society: Math and Comp Meeting in 2025.
 
-If you encounter problems with configuration, please file `GitHub issues promptly <https://github.com/mcdc-project/mcdc/issues>`_ ,
-especially when on supported super computers (LLNL's `Tioga <https://hpc.llnl.gov/hardware/compute-platforms/tioga>`_, `El Capitan <https://hpc.llnl.gov/documentation/user-guides/using-el-capitan-systems>`_, and `Lassen <https://hpc.llnl.gov/hardware/compute-platforms/lassen>`_).
+If you encounter configuration problems, please file a `GitHub issue <https://github.com/mcdc-project/mcdc/issues>`_, especially when using supported supercomputers such as LLNL's `Tioga <https://hpc.llnl.gov/hardware/compute-platforms/tioga>`_, `El Capitan <https://hpc.llnl.gov/documentation/user-guides/using-el-capitan-systems>`_, or `Lassen <https://hpc.llnl.gov/hardware/compute-platforms/lassen>`_.
 
 .. rubric:: Nvidia GPUs
 
-To compile and execute MC/DC on Nvidia GPUs first ensure you have the `Harmonize prerecs <https://github.com/CEMeNT-PSAAP/harmonize/blob/main/install.sh>`_ (CUDA=11.8, Numba>=0.60.0) and a working MC/DC version >=0.10.0. Then,
+To compile and execute MC/DC on Nvidia GPUs, first satisfy the `Harmonize prerequisites <https://github.com/CEMeNT-PSAAP/harmonize/blob/main/install.sh>`_ (CUDA 11.8 and Numba 0.61 or newer).
 
 #. Clone the harmonize repo: ``git clone https://github.com/CEMeNT-PSAAP/harmonize.git``
 #. Install into the proper Python env: ``pip install -e .``
@@ -250,11 +211,10 @@ Operability should now be enabled.
 
 .. rubric:: AMD GPUs
 
-The prerequisites for AMD operability are slightly more complex and
-require a patch to Numba to allow for AMD target triple LLVM-IR.
+The prerequisites for AMD operability require a Numba patch that enables the AMD target triple in LLVM IR.
 It is recommended that this is done within a Python venv virtual environment.
 
-To compile and execute MC/DC on AMD GPUs first ensure you have the `Harmonize prerecs <https://github.com/CEMeNT-PSAAP/harmonize/blob/main/install.sh>`_ (ROCm=6.0.0, Numba>=0.60.0) and a working MC/DC version >=0.11.0. Then,
+To compile and execute MC/DC on AMD GPUs, first satisfy the `Harmonize prerequisites <https://github.com/CEMeNT-PSAAP/harmonize/blob/main/install.sh>`_ (ROCm 6.0.0 and Numba 0.61 or newer).
 
 #. Patch Numba to enable HIP (`instructions here <https://github.com/ROCm/numba-hip>`_)
 #. Clone harmonize and `switch to the AMD <https://github.com/CEMeNT-PSAAP/harmonize/tree/amd_event_interop_revamp>`_ branch with ``git switch amd_event_interop_revamp``
diff --git a/docs/source/user_guide/troubleshooting.rst b/docs/source/user_guide/troubleshooting.rst
index 397830b00..7c7fc75c4 100644
--- a/docs/source/user_guide/troubleshooting.rst
+++ b/docs/source/user_guide/troubleshooting.rst
@@ -5,16 +5,13 @@ Troubleshooting
 ===============
 
 This page collects solutions to common installation and runtime problems.
-If your issue is not listed here, please check our
-`GitHub issues <https://github.com/mcdc-project/mcdc/issues>`_
-or open a new one.
+If your issue is not listed here, check the `GitHub issues <https://github.com/mcdc-project/mcdc/issues>`_ or open a new one.
 
 Numba Version Compatibility
 ----------------------------
 
-MC/DC requires **Numba >= 0.60.0**.
-Symptoms of version mismatch include ``TypingError``, unexpected ``LoweringError``,
-or missing ``@njit`` features.
+MC/DC requires **Numba >= 0.61.0**.
+Symptoms of version mismatch include ``TypingError``, unexpected ``LoweringError``, or missing ``@njit`` features.
 
 Check your version:
 
@@ -27,26 +24,24 @@ Check your version:
 .. code-block:: sh
 
    # pip
-   pip install --upgrade 'numba>=0.60.0'
+   pip install --upgrade 'numba>=0.61.0'
 
    # conda
-   conda install numba>=0.60.0 -c conda-forge
+   conda install 'numba>=0.61.0' -c conda-forge
 
 **Pinning Numba for CUDA compatibility:**
 
-If your system requires a specific CUDA toolkit,
-Numba and ``cuda-toolkit`` versions must match.
-For example, CUDA 11.8 works best with Numba 0.60.x:
+If your system requires a specific CUDA toolkit, Numba and ``cuda-toolkit`` versions must match.
+Use a Numba release compatible with both the installed Python version and the selected CUDA toolkit:
 
 .. code-block:: sh
 
-   conda install numba=0.60 cudatoolkit=11.8 -c conda-forge
+   conda install 'numba>=0.61.0' cuda-toolkit=11.8 -c conda-forge
 
 **Patching Numba for AMD GPUs (HIP):**
 
 AMD ROCm GPU support requires a patched Numba build.
-Follow the `numba-hip instructions <https://github.com/ROCm/numba-hip>`_
-to apply the HIP target triple patch.
+Follow the `numba-hip instructions <https://github.com/ROCm/numba-hip>`_ to apply the HIP target triple patch.
 This is required before installing Harmonize for AMD targets.
 See also :ref:`install-amd-gpus`.
 
@@ -55,8 +50,7 @@ Building mpi4py from Source
 ----------------------------
 
 On most HPCs, prebuilt mpi4py wheels are incompatible with the system MPI library.
-Symptoms include ``MPI_Init`` failures, segfaults at launch, or
-``ImportError: libmpi.so: cannot open shared object file``.
+Symptoms include ``MPI_Init`` failures, segfaults at launch, or ``ImportError: libmpi.so: cannot open shared object file``.
 
 **Step 1 — Load the correct MPI module:**
 
@@ -73,15 +67,6 @@ Symptoms include ``MPI_Init`` failures, segfaults at launch, or
 
    CC=mpicc pip install --no-cache-dir --no-binary mpi4py mpi4py
 
-Or, if using conda with the ``install.sh`` script:
-
-.. code-block:: sh
-
-   bash install.sh --hpc
-
-The ``--hpc`` flag instructs the install script to build mpi4py from source
-using the currently loaded MPI module.
-
 **Verifying the installation:**
 
 .. code-block:: sh
@@ -120,8 +105,7 @@ Incorrect or missing modules are the most common source of build failures.
      - ``module load cray-mpich rocm/6.0.0``
      - AMD MI300A GPUs
 
-After loading modules, activate your Python environment (venv or conda)
-before running ``pip install`` or ``bash install.sh``.
+After loading modules, activate your Python environment before running ``pip install``.
 
 Container Errors
 ----------------
@@ -140,7 +124,7 @@ Fix:
 
 .. code-block:: bash
 
-    podman run --rm -it --user root mcdc:dev
+    podman run --rm -it --user root ghcr.io/mcdc-project/mcdc:dev
 
 ``Out of memory`` (Apptainer)
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -189,8 +173,7 @@ Use ``--caching`` to save compiled binaries:
    python input.py --mode=numba --caching
 
 Subsequent runs will skip compilation.
-If compilation seems stuck, check that you are not running
-on a login node with limited resources.
+If compilation seems stuck, check that you are not running on a login node with limited resources.
 
 **Segmentation fault during MPI runs**
 
@@ -204,8 +187,7 @@ Also ensure that the number of MPI ranks does not exceed available cores:
 
 **"AttributeError: 'list' object has no attribute 'ID'" in** ``mcdc.Cell()``
 
-This error occurs when passing a Python list instead of using the ``&`` (intersection)
-and ``|`` (union) region operators.
+This error occurs when passing a Python list instead of using the ``&`` (intersection) and ``|`` (union) region operators.
 Use the operator syntax:
 
 .. code-block:: python3
@@ -222,9 +204,8 @@ See `#348 <https://github.com/mcdc-project/mcdc/issues/348>`_.
 Bugs and Issues
 ---------------
 
-Our documentation is in the early stages of development, so thank you for bearing with us 
-while we bring it up to snuff. If you find a novel bug or anything else you feel we should 
-be aware of, feel free to `open an issue <https://github.com/mcdc-project/mcdc/issues>`_.
+Our documentation remains under development, so thank you for bearing with us while we improve it.
+If you find a bug or another problem, please `open an issue <https://github.com/mcdc-project/mcdc/issues>`_.
 
 Getting More Help
 ~~~~~~~~~~~~~~~~~

From 3781a2c183c216e4bffea7f4fa16c0594746408c Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 19:12:38 +0700
Subject: [PATCH 201/202] add a helper component map

---
 mcdc/README.md | 14 ++++++++++++++
 1 file changed, 14 insertions(+)
 create mode 100644 mcdc/README.md

diff --git a/mcdc/README.md b/mcdc/README.md
new file mode 100644
index 000000000..f9754e2f2
--- /dev/null
+++ b/mcdc/README.md
@@ -0,0 +1,14 @@
+# MC/DC Package Map
+
+This directory contains the main MC/DC Python package.
+
+- `__init__.py` defines the public Python interface.
+- `object_/` defines the user-facing model objects and is the model-side home for methods development.
+- `config.py`, `constant.py`, and `literals.py` provide shared execution configuration and values.
+- `main.py` coordinates runtime preparation, transport execution, and output.
+- `code_factory/` compiles Python models into runtime data and backend-specific code.
+- `mcdc_get/` and `mcdc_set/` contain runtime-data accessors generated during preparation and used during transport.
+- `transport/` implements the shared Monte Carlo algorithms and is the primary place to study or extend particle transport.
+- `output.py` processes and serializes simulation results.
+
+See the [architecture guide](../docs/source/developer_guide/architecture/index.rst) for the detailed design and component responsibilities.

From 0b8ffd43a3510fae778556f65c39efc461736812 Mon Sep 17 00:00:00 2001
From: Ilham Variansyah <variansi@oregonstate.edu>
Date: Tue, 11 Aug 2026 19:26:14 +0700
Subject: [PATCH 202/202] fix docs workflow runner

---
 .github/workflows/docs_test.yml | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.github/workflows/docs_test.yml b/.github/workflows/docs_test.yml
index 6e5fb85ea..f82593865 100644
--- a/.github/workflows/docs_test.yml
+++ b/.github/workflows/docs_test.yml
@@ -5,6 +5,9 @@ on:
   pull_request:
   workflow_dispatch:
 
+env:
+  UCX_TLS: self,sm,tcp
+
 jobs:
   build-docs:
     runs-on: "ubuntu-latest"