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Correlated decoding improves matching and clustering surface-code decoders by reweighting one decoding subgraph conditioned on the other’s correction. We show that standard reweighting can cause correlated decoders to fail on size- fault configurations that a distance- code should correct, reducing error suppression deep below threshold. Under circuit-level noise, a single first-pass edge can discount several correlated edges, even though their joint occurrence requires additional independent faults, so the decoder favors an over-discounted correction. Regularizing the reweighting rule restores the nominal distance scaling and a clear correlated-decoding advantage.

生成讲解博客的中文版本

生成AI智能校验的中文版本