PyMatching Decoder
SkillDev toolsMinimum-weight perfect matching decoder skill for surface code error correction
Use PyMatching Decoder in Claude, ChatGPT or Ahel Desktop
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Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/quantum-computing/skills/pymatching-decoder/SKILL.md and read by Ahel’s review.
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
- Graph Construction: Build matching graph from detector error model
- Weight Assignment: Configure edge weights based on error probabilities
- Decoding Execution: Run MWPM algorithm on syndrome data
- Error Analysis: Calculate logical error rates from decoding results
- Optimization: Tune decoder parameters for specific code structures
Tools/Libraries
- PyMatching
- NetworkX
- Stim
- NumPy
Signals
- GitHub stars
- 2k
- Forks
- 113
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
pymatching-decoder- Source
- github.com/a5c-ai/babysitter