利用非局域伪势对现实材料一阶量子化的量子模拟

IF 6.6 1区 物理与天体物理 Q1 PHYSICS, APPLIED
Dominic W. Berry, Nicholas C. Rubin, Ahmed O. Elnabawy, Gabriele Ahlers, A. Eugene DePrince, Joonho Lee, Christian Gogolin, Ryan Babbush
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引用次数: 0

摘要

本文改进并证明了第一个量子化平面波算法在电子结构量子模拟中的实用性。我们描述了我们的量子算法的第一个量化模拟,准确地包括伪势。我们专注于goedecker - tter- hutter伪势,尽管其形式复杂,但我们对相关算子进行了块编码,而不会显著增加量子模拟的总体成本。这是令人惊讶的,因为模拟核势要简单得多,没有假势,但仍然是瓶颈。我们还推广了先前的方法,使具有非立方单元的材料的模拟成为可能,这需要不平凡的修改。最后,我们结合这些技术来估计商业上相关的多相催化实例(如一氧化碳吸附)的块编码成本,并与二次量化模拟材料所需的量子资源进行比较。我们的结论是,对于具有许多粒子的计算细胞,第一次量子化通常需要更少的时空体积。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Quantum simulation of realistic materials in first quantization using non-local pseudopotentials

Quantum simulation of realistic materials in first quantization using non-local pseudopotentials

This paper improves and demonstrates the usefulness of the first quantized plane-wave algorithms for the quantum simulation of electronic structure. We describe our quantum algorithm for first quantized simulation that accurately includes pseudopotentials. We focus on the Goedecker-Tetter-Hutter pseudopotential, and despite its complicated form, we block encode the associated operator without significantly increasing the overall cost of quantum simulation. This is surprising since simulating the nuclear potential is much simpler without pseudopotentials, yet is still the bottleneck. We also generalize prior methods to enable the simulation of materials with non-cubic unit cells, which requires nontrivial modifications. Finally, we combine these techniques to estimate block-encoding costs for commercially relevant instances of heterogeneous catalysis (e.g. carbon monoxide adsorption) and compare to the quantum resources needed to simulate materials in second quantization. We conclude that for computational cells with many particles, first quantization often requires meaningfully less spacetime volume.

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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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