近日，365体育投注:河南省量子信息与密码学重点实验室Wan-Su Bao团队报道了通过测量调度抑制逻辑量子位的测量噪声。相关论文于2026年1月5日发表在《物理评论A》杂志上。

量子纠错对于实现可靠的量子计算至关重要，其中表面码展现了高容错阈值和硬件效率。然而，单次测量中的噪声限制了逻辑读出的保真度，成为容错量子计算的关键瓶颈。

研究组提出了一种动态测量调度协议，通过将数据量子位的测量任务从易出错节点自适应地重新分配到稳定节点，从而抑制逻辑读出错误。该协议在确保与纠错周期兼容的同时，通过在稳定子测量完成后使用浅纠缠电路进行操作，平衡了门错误和测量噪声。

在处理由退相干限制和纠错要求所决定的时间约束的实际场景时，研究组实施了强化学习来实现自适应测量调度。数值模拟显示，在码距为3到11的范围内，逻辑错误率可降低高达34.98%，并且在测量噪声占主导地位的系统中具有增强的鲁棒性。该协议为高保真量子纠错提供了一种通用且硬件高效的解决方案，从而推动了大规模量子计算的发展。

附：英文原文

Title: Suppressing measurement noise in logical qubits through measurement scheduling

Author: Xiao-Yue Xu, Chen Ding, Wan-Su Bao

Issue&Volume: 2026/01/05

Abstract: Quantum error correction is essential for reliable quantum computation, where surface codes demonstrate high fault-tolerant thresholds and hardware efficiency. However, noise in single-shot measurements limits logical readout fidelity, forming a critical bottleneck for fault-tolerant quantum computation. We propose a dynamic measurement scheduling protocol that suppresses logical readout errors by adaptively redistributing measurement tasks on data qubits from error-prone to stable nodes. The protocol balances gate errors and measurement noise while ensuring compatibility with the error correction cycle by operating after the stabilizer measurements are complete, using shallow entangled circuits. When addressing realistic scenarios where temporal constraints are governed by decoherence limits and error-correction requirements, we implement reinforcement learning to achieve adaptive measurement scheduling. Numerical simulations show that logical error rates can be reduced by up to 34.98% for code distances ranging from 3 to 11, with enhanced robustness in measurement-noise-dominated systems. Our protocol offers a versatile, hardware-efficient solution for high-fidelity quantum error correction, advancing large-scale quantum computing.

DOI: 10.1103/rs1b-mnyc

Source: https://journals.aps.org/pra/abstract/10.1103/rs1b-mnyc