Toward Fault-Tolerant Variational Optimization: QAOA under [[4,2,2]] Error Detection

2026-09-07

AI Summary

本文针对Max-Cut问题，提出基于[[4,2,2]]错误检测码的部分容错QAOA实现，并通过新的逻辑$R_{ZZ}$门提高算法在噪声环境下的性能。

Abstract

We present a partially fault-tolerant implementation of QAOA based on the $[[4,2,2]]$ error-detection code, targeting the Max-Cut problem on a square graph. Our main contribution is a novel ancilla-mediated logical $R_{ZZ}$ gate enabling interactions between qubits in different $[[4,2,2]]$ blocks. We evaluate unencoded and encoded circuits under five noise models, with both all-to-all and grid-routed connectivity, using the Cirq and qsimcirq frameworks with parallel CPU execution. Post-selection on stabilizer measurements consistently improves the probability of sampling optimal bitstrings, with five measurements providing the strongest benefit. These results support error-detection as a practical near-term strategy for improving the quality of variational quantum algorithms.

Problem

• QAOA
• error-detection
• Max-Cut

Innovation

• fault-tolerant QAOA
• [[4,2,2]] error-detection code
• ancilla-mediated logical $R_{ZZ}$ gate