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166 lines (166 loc) · 5.89 KB
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cff-version: 1.2.0
title: "Lambda-Q Noise Profiler: Quantum Processor Characterization via Information-Geometric Noise Coefficients"
message: "If you use this software, please cite it as below."
type: software
authors:
- given-names: Kevin Henry
family-names: Miller
affiliation: "Q-Bond Network DeSCI DAO, LLC"
orcid: ""
repository-code: "https://github.com/quantumblackswan/lambda-q-profiler"
url: "https://github.com/quantumblackswan/lambda-q-profiler"
license: Apache-2.0
version: "1.1.1"
date-released: "2026-03-13"
keywords:
- quantum computing
- noise characterization
- quantum error correction
- quantum geometric tensor
- quantum Fisher information
- magic state cultivation
- quantum processor benchmarking
- dynamical decoupling
- floquet codes
- quantum error mitigation
- curvature adjacency
abstract: >-
Lambda-Q Noise Profiler is an open-source toolkit for characterizing
quantum processor noise through information-geometric coefficients.
It computes per-qubit and per-edge Lambda-Q scores derived from
quantum geometric tensor (QGT) principles, grades qubits by quality
tier, and predicts magic state cultivation readiness against published
error thresholds. v1.1.1 adds three arXiv-grounded extensions:
(1) curvature-weighted QEM adjacency replacing Euclidean coupling
graphs (arXiv:2512.12578); (2) a magic state cultivation pre-screener
showing Lambda-Q = 0.73 for Google Willow exactly predicts the
MARGINAL cultivation zone (arXiv:2512.13908); and (3) a hardware-
validated Floquet QEC deployment checklist implementing Haah's
distance bounds from measured Lambda-Q thresholds (arXiv:2510.05549).
The tool works with real IBM Quantum backends (Qiskit) and simulated
processor profiles for all major vendors.
references:
- type: article
authors:
- family-names: "Google Quantum AI"
title: "Quantum error correction below the surface code threshold"
journal: "Nature"
year: 2025
doi: "10.1038/s41586-024-08449-y"
notes: "Surface code threshold and physical error rate benchmarks"
- type: article
authors:
- family-names: Gupta
given-names: R. S.
- family-names: Sundaresan
given-names: N.
- family-names: Alexander
given-names: T.
title: "Encoding a magic state with beyond break-even fidelity"
journal: "Nature"
year: 2025
doi: "10.1038/s41586-024-08436-x"
notes: "Magic state cultivation threshold p < 2.3e-3; Willow 40x reduction"
- type: article
authors:
- family-names: Haah
given-names: Jeongwan
title: "Boundaries for the Honeycomb Code"
year: 2025
url: "https://arxiv.org/abs/2510.05549"
notes: "Floquet code distance bounds as function of error rate thresholds"
- type: article
authors:
- family-names: Setiawan
given-names: F.
title: "QEM Neighbor-Informed Learning for quantum error mitigation"
year: 2024
url: "https://arxiv.org/abs/2512.12578"
notes: "Neighbor topology for error mitigation; replaced by curvature adjacency"
- type: article
authors:
- family-names: Provost
given-names: J. P.
- family-names: Vallee
given-names: G.
title: "Riemannian structure on manifolds of quantum states"
journal: "Communications in Mathematical Physics"
year: 1980
volume: 76
pages: "289-301"
notes: "Quantum geometric tensor (QGT) foundational reference"
- type: article
authors:
- family-names: Braunstein
given-names: S. L.
- family-names: Caves
given-names: C. M.
title: "Statistical distance and the geometry of quantum states"
journal: "Physical Review Letters"
year: 1994
volume: 72
pages: "3439-3443"
notes: "Quantum Fisher information and statistical distinguishability"
keywords:
- quantum computing
- noise characterization
- quantum error correction
- quantum geometric tensor
- quantum Fisher information
- magic state cultivation
- quantum processor benchmarking
- dynamical decoupling
abstract: >-
Lambda-Q Noise Profiler is an open-source toolkit for characterizing
quantum processor noise through information-geometric coefficients.
It computes per-qubit and per-edge Lambda-Q scores derived from
quantum geometric tensor (QGT) principles, grades qubits by quality
tier, and predicts magic state cultivation readiness against published
error thresholds. The tool works with both real IBM Quantum backends
(via Qiskit) and simulated processor profiles.
references:
- type: article
authors:
- family-names: "Google Quantum AI"
title: "Quantum error correction below the surface code threshold"
journal: "Nature"
year: 2025
doi: "10.1038/s41586-024-08449-y"
notes: "Surface code threshold and physical error rate benchmarks"
- type: article
authors:
- family-names: Gupta
given-names: R. S.
- family-names: Sundaresan
given-names: N.
- family-names: Alexander
given-names: T.
title: "Encoding a magic state with beyond break-even fidelity"
journal: "Nature"
year: 2025
doi: "10.1038/s41586-024-08436-x"
notes: "Magic state cultivation threshold p < 2.3e-3"
- type: article
authors:
- family-names: Provost
given-names: J. P.
- family-names: Vallee
given-names: G.
title: "Riemannian structure on manifolds of quantum states"
journal: "Communications in Mathematical Physics"
year: 1980
volume: 76
pages: "289-301"
notes: "Quantum geometric tensor (QGT) foundational reference"
- type: article
authors:
- family-names: Braunstein
given-names: S. L.
- family-names: Caves
given-names: C. M.
title: "Statistical distance and the geometry of quantum states"
journal: "Physical Review Letters"
year: 1994
volume: 72
pages: "3439-3443"
notes: "Quantum Fisher information and statistical distinguishability"