一句话：提出面向变分量子算法的应用定制测量误差缓解方法 VarSaw，以降低 JigSaw 式子集测量的高昂开销。
变分量子算法（VQA）若要在 NISQ 设备上展现潜在量子优势，需要超越当前硬件能力的高精度，因此测量误差缓解至关重要。测量误差发生在电路执行后的量子比特测量阶段，是 VQA 中最易出错且危害最大的操作之一。已有工作 JigSaw 通过一次只测量少量量子比特子集，汇总所有子集电路结果，并结合完整电路提取的量子比特间测量相关性，来重建原电路的高保真输出分布；但其执行代价随电路量子比特数多项式增长，再乘以 VQA 所需的电路数与迭代数后，开销难以承受。VarSaw 则针对 VQA 应用定制测量误差缓解，旨在降低这一开销。摘要未展开其具体机制、实验设置与量化结果。
For potential quantum advantage, Variational Quantum Algorithms (VQAs) need high accuracy beyond the capability of today's NISQ devices, and thus will benefit from error mitigation. In this work we are interested in mitigating measurement errors which occur during qubit measurements after circuit execution and tend to be the most error-prone operations, especially detrimental to VQAs. Prior work, JigSaw, has shown that measuring only small subsets of circuit qubits at a time and collecting results across all such `subset' circuits can reduce measurement errors. Then, running the entire (`global') original circuit and extracting the qubit-qubit measurement correlations can be used in conjunction with the subsets to construct a high-fidelity output distribution of the original circuit. Unfortunately, the execution cost of JigSaw scales polynomially in the number of qubits in the circuit, and when compounded by the number of circuits and iterations in VQAs, the resulting execution cost quickly turns insurmountable.
@inproceedings{paperbot10128,
title = {VarSaw: Application-tailored Measurement Error Mitigation for Variational Quantum Algorithms},
author = {Siddharth Dangwal and Gokul Subramanian Ravi and Poulami Das and Kaitlin N. Smith and Jonathan Mark Baker and Frederic T. Chong},
booktitle = {ASPLOS},
year = {2023},
doi = {10.1145/3623278.3624764}
}