ericrihm · ericrihm · May 31, 2026 · May 31, 2026
diff --git a/CITATION.cff b/CITATION.cff
@@ -0,0 +1,31 @@
+cff-version: 1.2.0
+message: "If you use this software, please cite it as below."
+title: "conformal-toolkit: Symbolic and Discrete Conformal Geometry for SageMath and PyTorch"
+abstract: >-
+  A Python toolkit for computing conformal invariants both symbolically
+  (exact formulas via SageMath/SageManifolds) and discretely (per-vertex mesh
+  features via PyTorch): tractor calculus, GJMS operators, Q-curvature, the
+  conformal fundamental forms and Willmore densities of Blitz-Gover-Waldron,
+  Carroll geometry, and Fefferman-Graham holographic data. The hypersurface
+  module implements the conformal hypersurface invariant theory of Samuel Blitz,
+  A. Rod Gover, and Andrew Waldron.
+type: software
+authors:
+  - family-names: Rihm
+    given-names: Eric
+    email: admin@strata-networks.com
+repository-code: "https://github.com/ericrihm/conformal-toolkit"
+url: "https://github.com/ericrihm/conformal-toolkit"
+license: MIT
+version: 0.1.1
+date-released: "2026-05-31"
+keywords:
+  - conformal geometry
+  - differential geometry
+  - tractor calculus
+  - Q-curvature
+  - GJMS operators
+  - Willmore energy
+  - geometric deep learning
+  - SageMath
+  - PyTorch
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
@@ -0,0 +1,55 @@
+# Contributing
+
+Thanks for your interest — corrections and contributions are genuinely welcome.
+This project values being *correctable*: if you find an error in the math, the
+code, the docs, or in [`ERRATA.md`](ERRATA.md) itself, that's the system working.
+
+## Reporting a math/correctness error (errata)
+
+This is the highest-value contribution. Follow the same method the project's own
+audit used (see [`ERRATA.md` → "How we caught them"](ERRATA.md)):
+
+1. Open an issue titled `Errata: <one-line claim>`.
+2. Give the counter-evidence as concretely as possible:
+   - a **specific geometry** (a sphere radius, a flat patch, an explicit metric)
+     on which the claim returns the wrong number; or
+   - a **conformal-weight argument** showing the terms can't match.
+   A failing check on a named anchor metric is the gold standard.
+3. Propose the corrected formula, **stating your normalization convention**
+   (Branson vs. analyst signs differ — many conformal-geometry "errors" are
+   convention clashes), with a reference if you have one.
+4. If you can, add a regression test pinning the right value on the anchor —
+   *verified-on-an-anchor beats argued-in-prose.*
+
+Open mathematical problems where help is explicitly wanted are listed at the end
+of [`ERRATA.md`](ERRATA.md) (e.g. the complete weight-4 hypersurface invariant
+basis, the Fialkow/Weyl terms in `L₂`, the full extrinsic `Q₄`).
+
+## Development & tests
+
+The suite runs on two independent tracks (see the README section
+*"How it's tested"*):
+
+```bash
+# Track B — discrete (PyTorch only, no SageMath needed):
+pip install -e ".[dev,ml]"
+pytest tests/test_discrete/ tests/test_features/ -v
+
+# Track A — symbolic (needs SageMath 10.x):
+./sage-run.sh test          # auto-detects native micromamba or the Sage Docker image
+# or target specific modules:
+./sage-run.sh pytest tests/test_core/ -v
+```
+
+Both tracks run automatically on every push and pull request via GitHub Actions
+([`.github/workflows/test.yml`](.github/workflows/test.yml)) — please make sure
+they're green. If you add or correct a formula, add a regression anchor (a known
+closed-form value on a concrete geometry) alongside it; see
+`tests/test_discrete/test_errata_anchors.py` for the pattern.
+
+## Conventions
+
+- Match the surrounding code style; keep changes focused.
+- Tag any in-code note about a known limitation or correction with a stable
+  `# ERRATA <ID>` reference so it stays traceable to the errata log.
+- By contributing you agree your contributions are licensed under the MIT License.
diff --git a/ERRATA.md b/ERRATA.md
@@ -173,8 +173,12 @@ below.
 - **Claimed:** `count_invariants(4, ambient_dim=5) = 4` with basis
   `{|L₂|², tr(L₁⁴), W·L₁, |W|²}`, presented as the complete independent set.
 - **Why it's wrong:** the algebraic quartic `(|L₁|²)²` is **independent** of
-  `tr(L₁⁴)` for `n≥4` (their eigenvalue difference is `4abc(a+b+c) ≠ 0`) yet is
-  entirely absent. A complete *pointwise* weight-4 classification also needs the
+  `tr(L₁⁴)`: in eigenvalues `λᵢ` of `L₁`, their difference is
+  `(Σλᵢ²)² − Σλᵢ⁴ = 2·Σ_{i<j} λᵢ²λⱼ²`, which is strictly positive whenever `L₁`
+  has two or more nonzero principal curvatures — e.g. trace-free eigenvalues
+  `(1, 2, −3)` give `(|L₁|²)² = 196` versus `tr(L₁⁴) = 98`. (The two are *not*
+  proportional, so neither can be dropped.) Yet `(|L₁|²)²` is entirely absent
+  from the catalogue. A complete *pointwise* weight-4 classification also needs the
   tangential-derivative invariants (`|∇̄L₁|²` / `L₁·Δ̄L₁`, `|div L₁|²`) and the
   curvature coupling `J̄|L₁|²`. The true count therefore **exceeds 4**.
 - **Status:** `count_invariants` is now documented as a **lower bound**, and the

diff --git a/conformal_features/__init__.py b/conformal_features/__init__.py
@@ -1,6 +1,6 @@
 """Discrete conformal invariants for geometric deep learning."""
 
-__version__ = "0.1.0"
+__version__ = "0.1.1"
 
 from conformal_features.features.pipeline import mesh_conformal_features
 from conformal_features.discrete.spectral import (

diff --git a/conformal_toolkit/__init__.py b/conformal_toolkit/__init__.py
@@ -1,5 +1,5 @@
 """Symbolic conformal geometry toolkit built on SageManifolds."""
-__version__ = "0.1.0"
+__version__ = "0.1.1"
 
 from conformal_toolkit.core import ConformalStructure
 

diff --git a/conformal_toolkit/hypersurface/invariant_enumeration.py b/conformal_toolkit/hypersurface/invariant_enumeration.py
@@ -10,8 +10,10 @@
 KNOWN INCOMPLETENESS at weight 4 (see ERRATA M5). The weight-4 catalogue
 below is a PARTIAL (purely algebraic, leading) basis. It under-counts:
   * it omits the independent algebraic quartic (|L_1|^2)^2, which is
-    distinct from tr(L_1^4) for n >= 4 (their difference is 4abc(a+b+c)
-    in eigenvalues, generically nonzero); and
+    distinct from tr(L_1^4): in eigenvalues their difference is
+    (sum lam_i^2)^2 - sum lam_i^4 = 2 * sum_{i<j} lam_i^2 lam_j^2 > 0
+    whenever L_1 has >= 2 nonzero principal curvatures (e.g. trace-free
+    eigenvalues (1,2,-3) give 196 vs 98); and
   * it omits the tangential-derivative invariants (e.g. |nabla_bar L_1|^2 /
     L_1 . Delta_bar L_1, |div L_1|^2) and the curvature coupling
     J_bar |L_1|^2 that a complete pointwise weight-4 classification carries.

diff --git a/docs/outreach/blitz-email-draft.md b/docs/outreach/blitz-email-draft.md
@@ -14,7 +14,7 @@ I'm Eric Rihm, a software engineer working at the intersection of differential g
 2. **Research paper** -- Extend the classification computationally to higher-order L_k and use the toolkit to discover new identities or verify conjectured ones. The software can search spaces that are infeasible by hand.
 3. **ML/applications paper** -- I've also built a pipeline that uses conformal invariants as features for graph neural networks, applied to shape analysis. This is a novel bridge between conformal geometry and geometric deep learning -- could be a good fit for an ICML or NeurIPS workshop.
 
-The repo is public with 125 tests and 6 example notebooks:
+The repo is public with 160 tests and 6 example notebooks:
 https://github.com/ericrihm/conformal-toolkit
 
 Notebook 02 directly demonstrates your classification and would be the best place to start.

diff --git a/pyproject.toml b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "conformal-toolkit"
-version = "0.1.0"
+version = "0.1.1"
 description = "Computational conformal geometry and conformal invariants for geometric deep learning"
 readme = "README.md"
 license = "MIT"