文章基本信息

标题：Robust Control Optimization for Quantum Approximate Optimization Algorithms
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作者：Yulong Dong ; Xiang Meng ; Lin Lin 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：242-249
DOI：10.1016/j.ifacol.2020.12.130
语种：English
出版社：Elsevier
摘要：AbstractQuantum variational algorithms have garnered significant interest recently, due to their feasibility of being implemented and tested on noisy intermediate scale quantum (NISQ) devices. We examine the robustness of the quantum approximate optimization algorithm (QAOA), which can be used to solve certain quantum control problems, state preparation problems, and combinatorial optimization problems. We demonstrate that the error of QAOA simulation can be significantly reduced by robust control optimization techniques, specifically, by sequential convex programming (SCP), to ensure error suppression in situations where the source of the error is known but not necessarily its magnitude. We show that robust optimization improves both the objective landscape of QAOA as well as overall circuit fidelity in the presence of coherent errors and errors in initial state preparation.
关键词：Keywordsquantum approximate optimization algorithmrobust controlsequential convex programmingerror mitigation