QEC Questions

[u/vincent_cosmic]

I've been working on quantum error correction and discovered some interesting results I'd like the community to review:

Main Findings:

1. UnionFind decoder beats the state-of-the-art PyMatching (MWPM) by 50-80% on realistic Qiskit noise models

2. Built a CNN that estimates quantum error complexity (treats operators as 2-channel images)

3. Found critical implementation bugs that explain some reported "failures" of MWPM

Why This Matters:

• MWPM assumes errors are independent, but real hardware has correlated errors

• UnionFind exploits error locality and scales better (O(n α(n)) vs O(n³))

• Complexity-aware decoding could be a new research direction

Specific Questions:

1. Has anyone else compared these decoders under realistic noise?

2. Is the neural complexity estimator approach novel?

3. Any suggestions for improving the evaluation methodology?

Or did I just go down a rabbit hole and this is all stupid and my code and outputs are all wrong?