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Quantum Algorithms for Quantum Chemistry and Quantum Materials Science
Chemical Reviews ( IF 51.4 ) Pub Date : 2020-10-22 , DOI: 10.1021/acs.chemrev.9b00829
Bela Bauer 1 , Sergey Bravyi 2 , Mario Motta 3 , Garnet Kin-Lic Chan 4
Affiliation  

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.

中文翻译:

量子化学和量子材料科学的量子算法

随着我们开始达到经典计算的极限,量子计算已经成为一种吸引了科学界想象力的技术。尽管多年来,执行量子算法的能力只是一个理论上的可能性,但是硬件的最新进展意味着现在存在可以在有限规模上进行量子计算的量子计算设备。因此,评估量子计算机对感兴趣的实际问题的潜在影响现在是真正的可能性,并且在此时至关重要。量子计算机最早且最引人注目的应用之一是费曼(Feynman)的模拟具有许多自由度的量子系统的想法。在化学,物理和材料科学中都可以找到这样的系统。量子计算扩展经典计算的一种特殊方式意味着人们不能指望量子计算机会加速任意模拟,因此必须仔细确定可以实现量子优势的领域。在这篇综述中,我们简要介绍了化学和材料科学中的核心问题,这些问题是电子计算机,量子统计力学和量子动力学领域中可能在量子计算机上解决的潜在问题。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最新进展,并分析了它们在未来发展中的优缺点。我们简要描述了化学和材料科学,电子结构,量子统计力学和量子动力学领域中的核心问题,这些问题对于解决量子计算机上的潜在问题很重要。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最新进展,并分析了它们在未来发展中的优缺点。我们简要描述了化学和材料科学,电子结构,量子统计力学和量子动力学领域中的核心问题,这些问题对于解决量子计算机上的潜在问题很重要。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最新进展,并分析了它们在未来发展中的优缺点。
更新日期:2020-11-25
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