优化对称性信息启发的概率误差消除
Optimizing Symmetry Informed Probabilistic Error Cancellation
AI总结：
结合量子错误检测与概率误差消除，通过优化对称性测量配置，在GHZ态和费米-哈伯德模型中实现比单独PEC更准确、方差更低的估计。
摘要：
我们表明，将量子错误检测（QED）与概率误差消除（PEC）相结合，在精心选择QED所需的对称性测量的条件下，比单独使用PEC能得到更准确且方差更低的估计。由于有噪声的对称性测量可能抵消PEC+QED方法的优势，我们将测量配置的选择视为一个经典优化问题，系统地抑制噪声的影响。将优化的PEC+QED应用于GHZ态输出分布以及模拟广义超快编码费米-哈伯德模型的时间动力学，我们发现相对于PEC有持续改进。对于GHZ态，对称性测量配置的优化对于实现优势至关重要。对于费米-哈伯德模型，PEC+QED改进了$2 \ imes 2$格点上的可观测量估计，并且对于更大的系统，可以通过仅测量稳定子子集来降低缓解开销。我们的结果证明了针对特定电路定制QEM技术的重要性，并且容错设计原则可能已经为近期设备提供了价值。
英文摘要：
We show that combining quantum error detection (QED) with probabilistic error cancellation (PEC) gives more accurate and lower-variance estimates than PEC alone, provided that the symmetry measurements required for QED are carefully chosen. Because noisy symmetry measurements can negate the benefits of the PEC+QED approach, we cast the selection of measurement configurations as a classical optimization problem that systematically suppresses the impact of noise. Applying optimized PEC+QED to GHZ-state output distributions and to simulating the time-dynamics of a generalized superfast encoded Fermi-Hubbard model, we find consistent improvements over PEC. For GHZ states, the optimization over symmetry measurement configurations is essential for achieving an advantage. For the Fermi-Hubbard model, PEC+QED improves observable estimation on a $2 \times 2$ lattice and for larger systems the mitigation overheads can be reduced by measuring only subsets of stabilizers. Our results demonstrate the importance of circuit-specific tailoring of QEM techniques and that fault-tolerant design principles may already provide value for near-term devices.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
