Enhancing Fault-Tolerant Surface Code Decoding with Iterative Lattice Reweighting

Yi Tian et al. · 2025 · arXiv.org

| 编号 QE270 | 主题 译码算法 | 链接 arXiv:2509.06756 |

摘要

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Efficient and realistic error decoding is crucial for fault-tolerant quantum computation (FTQC) on near-term devices. While decoding is a classical post-processing task, its effectiveness depends on accurately modeling quantum noise, which is hardware-dependent. In particular, correlated bit-flip ($X$) and phase-flip ($Z$) errors often arise under circuit-level noise. We introduce the Iterative Reweighting Minimum-Weight Perfect Matching (IRMWPM) decoder, which systematically incorporates such correlations to enhance quantum error correction. Our method leverages fault-detection patterns to guide reweighting: correlated $X$ and $Z$ detection events are identified, and their conditional probabilities update weights on the primal and dual lattices. This iterative procedure improves handling of realistic error propagation in a hardware-agnostic yet noise-aware manner. We prove that IRMWPM converges in finite time while preserving the distance guarantee of MWPM. Numerical results under circuit-level noise show substantial improvements. For distances $\ge 17$ and physical error rates $\le 0.001$, IRMWPM reduces logical error rates by over 20x with only a few iterations. It also raises

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