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pymatching-decoder

// Minimum-weight perfect matching decoder skill for surface code error correction

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stars:384
forks:73
updated:March 4, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
namepymatching-decoder
descriptionMinimum-weight perfect matching decoder skill for surface code error correction
allowed-toolsBash,Read,Write,Edit,Glob,Grep
metadata[object Object]

PyMatching Decoder

Purpose

Provides expert guidance on minimum-weight perfect matching decoding for surface codes and other topological quantum error correction codes.

Capabilities

  • MWPM decoding for surface codes
  • Weighted edge matching
  • Detector error model processing
  • Logical error rate calculation
  • Integration with Stim simulations
  • Custom graph construction
  • Belief propagation integration
  • Parallelized decoding

Usage Guidelines

  1. Graph Construction: Build matching graph from detector error model
  2. Weight Assignment: Configure edge weights based on error probabilities
  3. Decoding Execution: Run MWPM algorithm on syndrome data
  4. Error Analysis: Calculate logical error rates from decoding results
  5. Optimization: Tune decoder parameters for specific code structures

Tools/Libraries

  • PyMatching
  • NetworkX
  • Stim
  • NumPy