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用于量子化学和量子材料科学的量子算法。

Quantum Algorithms for Quantum Chemistry and Quantum Materials Science.

作者信息

Bauer Bela, Bravyi Sergey, Motta Mario, Kin-Lic Chan Garnet

机构信息

Microsoft Quantum, Station Q, University of California, Santa Barbara, California 93106, United States.

IBM Quantum, IBM T. J. Watson Research Center, Yorktown Heights, New York 10598, United States.

出版信息

Chem Rev. 2020 Nov 25;120(22):12685-12717. doi: 10.1021/acs.chemrev.9b00829. Epub 2020 Oct 22.

Abstract

As we begin to reach the limits of classical computing, quantum computing has emerged as a technology that has captured the imagination of the scientific world. While for many years, the ability to execute quantum algorithms was only a theoretical possibility, recent advances in hardware mean that quantum computing devices now exist that can carry out quantum computation on a limited scale. Thus, it is now a real possibility, and of central importance at this time, to assess the potential impact of quantum computers on real problems of interest. One of the earliest and most compelling applications for quantum computers is Feynman's idea of simulating quantum systems with many degrees of freedom. Such systems are found across chemistry, physics, and materials science. The particular way in which quantum computing extends classical computing means that one cannot expect arbitrary simulations to be sped up by a quantum computer, thus one must carefully identify areas where quantum advantage may be achieved. In this review, we briefly describe central problems in chemistry and materials science, in areas of electronic structure, quantum statistical mechanics, and quantum dynamics that are of potential interest for solution on a quantum computer. We then take a detailed snapshot of current progress in quantum algorithms for ground-state, dynamics, and thermal-state simulation and analyze their strengths and weaknesses for future developments.

摘要

随着我们开始接近经典计算的极限,量子计算作为一项激发科学界想象力的技术应运而生。多年来,执行量子算法的能力一直只是一种理论上的可能性,但硬件方面的最新进展意味着现在已经存在能够在有限规模上进行量子计算的设备。因此,评估量子计算机对实际感兴趣问题的潜在影响现在已成为一种切实可行的可能性,并且在当前具有至关重要的意义。量子计算机最早且最具吸引力的应用之一是费曼提出的用具有多个自由度的量子系统进行模拟的想法。这类系统在化学、物理和材料科学领域都有发现。量子计算扩展经典计算的特殊方式意味着不能期望量子计算机能加速任意模拟,因此必须仔细确定可能实现量子优势的领域。在本综述中,我们简要描述化学和材料科学中电子结构、量子统计力学以及量子动力学等领域的核心问题,这些问题在量子计算机上求解可能具有潜在意义。然后,我们详细介绍了用于基态、动力学和热态模拟的量子算法的当前进展,并分析它们在未来发展中的优势和劣势。

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