具有任意基集的第一量子化化学量子模拟

IF 6.6 1区 物理与天体物理 Q1 PHYSICS, APPLIED
Timothy N. Georges, Marius Bothe, Christoph Sünderhauf, Bjorn K. Berntson, Róbert Izsák, Aleksei V. Ivanov
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引用次数: 0

摘要

分子和材料能量的量子计算是容错量子计算机最有前途的应用之一。实际应用需要开发资源需求更少的量子算法。先前的工作主要集中在量子算法上,其中哈密顿量在第二次量化中使用紧凑的基集表示,而现有的第一次量化方法仅限于基于网格的基。本文提出了一种利用任意基集求解第一量子化中一般基态化学问题的新方法。我们实现了分子轨道的Toffoli计数的渐近加速,并且使用双平面波与第二次量化相比有了数量级的提高。在某些情况下,与之前的第一次量化平面波算法相比,我们的方法提供了类似甚至更低的资源,与我们的方法不同,这些算法避免了经典数据的加载。所开发的方法可以应用于各种应用,其中第一量子化哈密顿的矩阵元素缺乏简单的电路表示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Quantum simulations of chemistry in first quantization with any basis set

Quantum simulations of chemistry in first quantization with any basis set

Quantum computation of the energy of molecules and materials is one of the most promising applications of fault-tolerant quantum computers. Practical applications require development of quantum algorithms with reduced resource requirements. Previous work has mainly focused on quantum algorithms where the Hamiltonian is represented in second quantization with compact basis sets while existing methods in first quantization are limited to a grid-based basis. In this work, we present a new method to solve the generic ground-state chemistry problem in first quantization using any basis set. We achieve asymptotic speedup in Toffoli count for molecular orbitals, and orders of magnitude improvement using dual plane waves as compared to the second quantization counterparts. In some instances, our approach provides similar or even lower resources compared to previous first quantization plane wave algorithms that, unlike our approach, avoids the loading of the classical data. The developed methodology can be applied to variety of applications, where the matrix elements of a first quantized Hamiltonian lack simple circuit representation.

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来源期刊
npj Quantum Information
npj Quantum Information Computer Science-Computer Science (miscellaneous)
CiteScore
13.70
自引率
3.90%
发文量
130
审稿时长
29 weeks
期刊介绍: The scope of npj Quantum Information spans across all relevant disciplines, fields, approaches and levels and so considers outstanding work ranging from fundamental research to applications and technologies.
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