Python Tools for Quantum Error Correction
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Updated
Apr 27, 2026 - Python
Python Tools for Quantum Error Correction
Deterministic quantum error-correction labs, proof receipts, and reproducible evidence.
Frontier decoder for quantum LDPC codes: pruned dynamic programming over boundary states for approximate logical maximum-likelihood decoding of sparse parity-check and detector-error-model matrices.
Construct bivariate-bicycle / generalized-bicycle qLDPC codes and decode them with a from-scratch BP+OSD decoder, benchmarked against the surface code on encoding rate.
This repository contains a few asymptotically good qLDPC code construction (HGP and LP codes).
Kernel-checked certification of QLDPC decoder outputs: Lean 4 verified checkers, two-sided per-run certificates (success AND failure witnesses), HMAC-chained audit logs, and Lean-emitted synthesizable RTL (1–2k gates, measured). Bivariate bicycle codes, 72–288 qubits. GPLv3 / commercial dual-license.
Vendor-portable GPU decoders for quantum LDPC codes — Triton min-sum BP & Relay-BP on NVIDIA (CUDA), AMD (ROCm), and Apple-silicon (Metal), consuming any stim DetectorErrorModel.
Open-source QEC decoders: Pathfinder — a direction-aware neural surface-code decoder (real-time-budget Triton kernel) whose multi-seed ensemble lowers logical error below the prior open-source GNN at operational noise rates — plus a kernel-grounded, MLE-anchored latency–LER benchmark for circuit-level qLDPC (bivariate-bicycle) codes.
Certified exact distances for six PBB codes: signed certificates, inline witnesses, one-command verifier, and a forgery-laden stranger-verification challenge
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