mwpm

Production-grade Rust/Python quantum error correction decoder. 25+ decoder families: MWPM Blossom, Union-Find, BP-OSD, LDPC/qLDPC, belief-matching, CUDA/GPU batch decoding, AutoDecoder 7-tier fallback. PyMatching/Stim/Sinter compatible. Ed25519 license verification. Benchmark evidence included.

A benchmarking framework for surface-code decoders: MWPM, union-find and belief propagation compared on accuracy, runtime and memory.

Reproduction of 'Testing the Accuracy of Surface Code Decoders' (arXiv:2311.12503): exact MWPM vs optimal maximum-likelihood decoder.

A benchmark harness you can't fool: compare neural QEC decoders against minimum-weight perfect matching on identical shots, with Wilson intervals and honest three-way verdicts.

A Python simulation toolkit for toric-code decoding with minimum-weight perfect matching under perfect and noisy syndrome measurements.

Does fitting a matching decoder's prior from syndromes help? Exact risk theory, certified bounds over prior families, shot-budget frontiers under noise heterogeneity, and Willow hardware analysis — with the result tables behind every number.

Neural vs. classical decoders for the surface code: benchmarking MWPM, CNN, and Transformers on simulated and real IBM quantum hardware.

Autonomous Quantum Error Correction (QEC) Syndrome Decoder using Stim, PyMatching MWPM, Qiskit & Streamlit