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docs: verify and upgrade all documentation for v0.6.2 (full Mac Intel+ARM support, hypergraph rejection details, sdist, accurate limits, install examples, roadmap reality)
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INSTALL.md

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Install Rust first from rustup, then run:
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```powershell
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git clone https://github.com/qectorlab/qector-decoder.git
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git clone https://github.com/GuillaumeLessard/qector-decoder.git
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cd qector-decoder
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py -3.11 -m venv .venv
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## Git Bash on Windows
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```bash
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git clone https://github.com/qectorlab/qector-decoder.git
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git clone https://github.com/GuillaumeLessard/qector-decoder.git
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cd qector-decoder
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python -m venv .venv

PYPI_README.md

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Supported package target for the public release workflow:
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- Python 3.9 to 3.13
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- Linux x86_64 wheels
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- Linux x86_64 wheels (manylinux)
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- Windows x64 wheels
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- macOS arm64 wheels
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- Source distribution for custom/source builds
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- macOS Intel x86_64 + Apple Silicon arm64 wheels
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- Source distribution (sdist) for custom/source builds
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Optional research and validation extras:
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README.md

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| GPU performance | Correctness is artifact-backed for tested machines. Speedup is not universal. |
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| OpenCL wheels | OpenCL support depends on build configuration and target environment. Confirm locally. |
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| SparseBlossom | Near-optimal, not exact MWPM. Use `BlossomDecoder` for exact minimum-weight matching. |
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| UnionFind | Fast approximate path; not a universal decoder for arbitrary graphs. |
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| UnionFind / FastUnionFind | Fast approximate; only for codes where each qubit participates in ≤2 checks (graph-like matching codes). Explicitly rejects hypergraphs (v0.6.2+). Use Blossom/SparseBlossom/BPOSD for general cases. |
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| REST/gRPC/MCP surfaces | Not hardened as public SaaS without a separate deployment/security review. |
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docs/CORRECTNESS_AUDIT.md

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|---|---|---|---|
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| `BlossomDecoder` | Syndrome-faithful and exact minimum-weight on audited small matching codes | Exhaustive brute-force oracle + PyMatching cross-checks | Exact MWPM on the tested audited graph families; do not claim universal hardware layout equivalence |
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| `SparseBlossomDecoder` | Syndrome-faithful and near-optimal | Brute-force small-code audit + PyMatching-compatible matching-graph tests | Region-growing decoder, not exact MWPM by design |
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| `UnionFindDecoder` | Syndrome-faithful on supported QEC matching graphs | Exhaustive small-code tests + family tests + property tests | Fast approximate decoder; not minimum-weight and not guaranteed on arbitrary adversarial hypergraphs |
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| `FastUnionFindDecoder` | Same as Union-Find, lower-overhead path | Cross-decoder faithfulness tests | Fast approximate decoder, not exact MWPM |
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| `UnionFindDecoder` | Syndrome-faithful on supported QEC matching graphs (each qubit in ≤2 checks) | Exhaustive small-code tests + family tests + property tests + hypergraph-rejection tests (v0.6.2) | Fast approximate; explicitly rejects hypergraphs (qubit degree >2) with clear error since v0.6.2. Not minimum-weight. |
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| `FastUnionFindDecoder` | Same as Union-Find (≤2 checks per qubit), lower-overhead path | Cross-decoder faithfulness + rejection tests (v0.6.2) | Same rejection and limits as UnionFindDecoder. |
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| `LookupTableDecoder` | Exact/faithful on stored table entries; faithful fallback on larger cases | Exhaustive table tests + d=5 fallback test | Table size and fallback behavior must be stated |
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| `BPOSDDecoder` / `BpOsdDecoder` | Syndrome-faithful on LDPC/qLDPC-style CSS checks | BP-OSD reference-package comparison + CSS commutation tests | Quote LER from the harness, not from faithfulness alone |
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| `BeliefMatching` | Lower observed LER on selected correlated workloads | Seeded Stim/PyMatching comparison tests and benchmark artifacts | Accuracy mode, not fast path; selected workload only |

docs/PLATFORM_ARTIFACT_ROADMAP.md

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| GPU bit-identity | Tested configurations and docs | Safe as bit-identity claim, not throughput claim |
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| GPU throughput | Not yet a stable public proof asset | Do not claim speedup without regenerated local artifacts |
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| Linux/macOS benchmark corpus | Not yet published as comparable artifacts | Do not imply cross-platform benchmark equivalence |
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| Prebuilt wheels | Not yet published as release assets | Source build remains the public path |
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| Prebuilt wheels | Published for v0.6.2+ (Linux, Windows, macOS Intel+ARM) | Full matrix in CI; attach attestations |
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## Planned artifact classes
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### 3. Prebuilt wheels
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Goal: reduce install friction once release automation and license packaging are ready.
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As of v0.6.2, CPU-safe wheels are published via CI for:
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Candidate wheel targets:
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- Linux x86_64 (manylinux)
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- Windows x64
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- macOS Intel x86_64 + Apple Silicon arm64
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sdist is also published.
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Candidate / supported targets (v0.6.2+):
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```text
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Windows x86_64 CPython 3.10/3.11/3.12 CPU-safe
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Linux x86_64 CPython 3.10/3.11/3.12 CPU-safe
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macOS arm64 CPython 3.10/3.11/3.12 CPU-safe
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Linux x86_64 CPython 3.9–3.13
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Windows x64 CPython 3.9–3.13
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macOS x86_64 CPython 3.9–3.13
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macOS arm64 CPython 3.9–3.13
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```
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Constraints:
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Constraints / notes:
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```text
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Do not publish GPU-enabled wheels until CUDA/OpenCL runtime assumptions are documented.
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Do not publish commercial-use language that conflicts with LICENSE and COMMERCIAL.md.
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Attach license and source-available terms to every release.
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Keep source build path documented even if wheels become available.
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GPU wheels (CUDA feature) are built in CI but require runtime support on the target machine.
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OpenCL support depends on build configuration and host drivers.
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Attach license and source-available terms.
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Keep source build documented for full auditability.
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```
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### 4. SBOM and dependency audit outputs
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```text
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QECTOR already has universal cross-platform benchmark proof.
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QECTOR already ships production wheels for every platform.
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QECTOR ships production wheels for Linux, Windows, macOS Intel x86_64 and Apple Silicon.
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QECTOR GPU throughput is generally faster than PyMatching.
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```

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