Quantum Error Correction Simulator

A Python-based quantum error correction (QEC) simulator built with Qiskit, focused on syndrome extraction, noise modelling, and Minimum Weight Perfect Matching (MWPM) decoding for topological quantum error-correcting codes.

The current implementation supports configurable planar surface-code distances with multi-round syndrome extraction, noise modelling, and MWPM-based decoding. The project is being developed into a modular quantum error correction research platform for threshold studies, decoder benchmarking, and alternative decoder backends.

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Features

• Configurable odd code distances (d = 3, 5, 7, ...)
• Multi-round syndrome extraction
• MWPM decoding
• Space-time decoding
• Depolarising and readout noise models
• Monte Carlo simulation framework
• Unit tests and reproducible experiments

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Repository Structure

src/qec/
├── geometry.py
├── circuit.py
├── syndrome.py
├── decoder.py
├── noise.py
├── simulation.py
└── visualization.py

experiments/
└── compare_decoders.py

results/
└── comparison/
    └── decoder_comparison.png

tests/
├── test_geometry.py
├── test_circuit.py
├── test_syndrome.py
├── test_decoder.py
└── test_simulation.py

notebooks/
├── demo.ipynb
├── repetition-code-simulation.ipynb
└── 3-distance-surface-code.ipynb

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Example Experiment

Compare single-round and space-time decoding:

python experiments/compare_decoders.py

This runs a sweep over physical error rates and generates:

results/comparison/decoder_comparison.png

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Example Result

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Testing

Run the unit test suite:

pytest

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Future Work

• Improved logical-failure detection
• Threshold analysis
• Stim integration
• PyMatching backend
• Decoder benchmarking
• GitHub Actions CI

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Requirements

• Python 3.10+
• Qiskit
• NumPy
• NetworkX
• Matplotlib
• Pytest

Install dependencies:

pip install qiskit numpy networkx matplotlib pytest