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通过能量排序降低幺正耦合簇近似的电路深度

Circuit-Depth Reduction of Unitary-Coupled-Cluster Ansatz by Energy Sorting.

作者信息

Fan Yi, Cao Changsu, Xu Xusheng, Li Zhenyu, Lv Dingshun, Yung Man-Hong

机构信息

Central Research Institute, 2012 Laboratories, Huawei Technologies, Shenzhen 518129, China.

Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, Anhui 230026, China.

出版信息

J Phys Chem Lett. 2023 Nov 2;14(43):9596-9603. doi: 10.1021/acs.jpclett.3c01804. Epub 2023 Oct 20.

Abstract

Quantum computation represents a revolutionary approach to solving problems in quantum chemistry. However, due to the limited quantum resources in the current noisy intermediate-scale quantum (NISQ) devices, quantum algorithms for large chemical systems remain a major task. In this work, we demonstrate that the circuit depth of the unitary coupled cluster (UCC) and UCC-based ansatzes in the algorithm of the variational quantum eigensolver can be significantly reduced by an energy-sorting strategy. Specifically, subsets of excitation operators are first prescreened from the operator pool according to its contribution to the total energy. The quantum circuit ansatz is then iteratively constructed until convergence of the final energy to a typical accuracy. For demonstration, this method has been successfully applied to molecular and periodic systems. Particularly, a reduction of 50%-98% in the number of operators is observed while retaining the accuracy of the original UCCSD operator pools. This method can be straightforwardly extended to general parametric variational ansatzes.

摘要

量子计算代表了一种解决量子化学问题的革命性方法。然而,由于当前嘈杂的中尺度量子(NISQ)设备中的量子资源有限,用于大型化学系统的量子算法仍然是一项主要任务。在这项工作中,我们证明了通过能量排序策略,可以显著降低变分量子本征求解器算法中幺正耦合簇(UCC)和基于UCC的近似的电路深度。具体而言,首先根据激发算符对总能量的贡献从算符池中预先筛选出子集。然后迭代构建量子电路近似,直到最终能量收敛到典型精度。为作演示,该方法已成功应用于分子和周期性系统。特别是,在保持原始UCCSD算符池精度的同时,观察到算符数量减少了50% - 98%。该方法可以直接扩展到一般的参数变分近似。

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