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<h1 style="font-size:2.25rem;font-weight:800;letter-spacing:-0.02em;margin:0 0 1rem;color:#f1f5f9;">Production-Grade QEC Decoding for Python</h1><p style="font-size:1.05rem;color:#b6c2d2;margin:0 0 1.25rem;">QECTOR Decoder v3 is a Rust-core Python library of 20+ production and research quantum error correction decoders — MWPM Blossom, Belief-Matching, BP-OSD, Union-Find, GPU batch and more — behind one consistent API, with exact logical-error-rate parity to PyMatching through distance 15.</p><pre style="background:#0b1329;border:1px solid #1e2a45;border-radius:0.75rem;padding:1rem;font-family:'JetBrains Mono',ui-monospace,monospace;font-size:0.85rem;color:#67e8f9;overflow-x:auto;margin:0 0 1.25rem;">pip install qector-decoder-v3==0.7.0
import numpy as np
from qector_decoder_v3 import BlossomDecoder
decoder = BlossomDecoder([[0, 1], [1, 2], [2, 3], [3, 4]], n_qubits=5)
correction = decoder.decode(np.array([0, 1, 0, 0], dtype=np.uint8))</pre><h2 style="font-size:1.3rem;font-weight:700;margin:1.75rem 0 0.75rem;color:#67e8f9;">Validated claims, each linked to an artifact</h2><ul style="margin:0 0 1.25rem;padding-left:1.25rem;color:#b6c2d2;"><li style="margin-bottom:0.4rem;">Exact LER parity with PyMatching from d=3 to d=15 (adaptive-k MWPM; Stim circuit-level noise).</li><li style="margin-bottom:0.4rem;">+35.7% LER reduction with Belief-Matching vs plain MWPM at d=5 under depolarizing circuit noise (p=0.001).</li><li style="margin-bottom:0.4rem;">100% syndrome faithfulness: every graph-like decoder satisfies H · correction ≡ syndrome (mod 2), d=3–19.</li><li style="margin-bottom:0.4rem;">CUDA / OpenCL batch decoding bit-identical to CPU output; peak 13.5M shots/s on a GTX 1660 Ti (d=3).</li><li style="margin-bottom:0.4rem;">PyMatching remains the latency leader for standard MWPM — QECTOR’s value is multi-algorithm diversity, accuracy modes, and reproducibility.</li></ul><h2 style="font-size:1.3rem;font-weight:700;margin:1.75rem 0 0.75rem;color:#67e8f9;">The decoders</h2><p style="font-size:1.05rem;color:#b6c2d2;margin:0 0 1.25rem;">UnionFind, FastUnionFind, Blossom MWPM, SparseBlossom, BeliefMatching, BP-OSD (qLDPC), BatchDecoder, CUDA and OpenCL batch decoders, AutoDecoder (7-tier fallback), plus research-stage Hybrid/Cascade, Predecoded, Lookup-Table, Sliding-Window, Streaming, and GNN Belief Matcher decoders.</p><h2 style="font-size:1.3rem;font-weight:700;margin:1.75rem 0 0.75rem;color:#67e8f9;">Evidence</h2><ul style="margin:0 0 1.25rem;padding-left:1.25rem;color:#b6c2d2;"><li style="margin-bottom:0.4rem;">PyPI package: <a href="https://pypi.org/project/qector-decoder-v3/" style="color:#67e8f9;">qector-decoder-v3 0.7.0</a></li><li style="margin-bottom:0.4rem;">Artifacts and reproduction harness: <a href="https://github.com/GuillaumeLessard/qector-decoder" style="color:#67e8f9;">github.com/GuillaumeLessard/qector-decoder</a></li><li style="margin-bottom:0.4rem;">Benchmark datasets: edge-hardware sweep (v0.6.8) and 105-run master report, published in the reproduction harness above.</li></ul><nav style="margin-top:2.5rem;padding-top:1.25rem;border-top:1px solid #1e2a45;font-size:0.9rem;"><a href="/" style="color:#67e8f9;margin-right:1rem;text-decoration:none;">Home</a><a href="/decoder" style="color:#67e8f9;margin-right:1rem;text-decoration:none;">Decoder</a><a href="/benchmarks" style="color:#67e8f9;margin-right:1rem;text-decoration:none;">Benchmarks</a><a href="/evidence" style="color:#67e8f9;margin-right:1rem;text-decoration:none;">Evidence</a><a href="/pricing" style="color:#67e8f9;margin-right:1rem;text-decoration:none;">Pricing</a><a href="/installer" style="color:#67e8f9;margin-right:1rem;text-decoration:none;">Install</a><a href="/docs" style="color:#67e8f9;margin-right:1rem;text-decoration:none;">Docs</a><a href="/changelog" style="color:#67e8f9;margin-right:1rem;text-decoration:none;">Changelog</a><a href="/contact" style="color:#67e8f9;margin-right:1rem;text-decoration:none;">Contact</a></nav>
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