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分子量子动力学:量子计算视角

Molecular Quantum Dynamics: A Quantum Computing Perspective.

作者信息

Ollitrault Pauline J, Miessen Alexander, Tavernelli Ivano

机构信息

IBM Quantum, IBM Research-Zürich, 8803 Rüschlikon, Switzerland.

出版信息

Acc Chem Res. 2021 Dec 7;54(23):4229-4238. doi: 10.1021/acs.accounts.1c00514. Epub 2021 Nov 17.

DOI:10.1021/acs.accounts.1c00514
PMID:34787398
Abstract

ConspectusSimulating molecular dynamics (MD) within a comprehensive quantum framework has been a long-standing challenge in computational chemistry. An exponential scaling of computational cost renders solving the time dependent Schrödinger equation (TDSE) of a molecular Hamiltonian, including both electronic and nuclear degrees of freedom (DOFs), as well as their couplings, infeasible for more than a few DOFs. In the Born-Oppenheimer (BO), or adiabatic, picture, electronic and nuclear parts of the wave function are decoupled and treated separately. Within this framework, the nuclear wave function evolves along potential energy surfaces (PESs) computed as solutions to the electronic Schrödinger equation parametrized in the nuclear DOFs. This approximation, together with increasingly elaborate numerical approaches to solve the nuclear time dependent Schrödinger equation (TDSE), enabled the treatment of up to a few dozens of degrees of freedom (DOFs). However, for particular applications, such as photochemistry, the BO approximation breaks down. In this regime of non-adiabatic dynamics, solving the full molecular problem including electron-nuclear couplings becomes essential, further increasing the complexity of the numerical solution. Although valuable methods such as multiconfigurational time-dependent Hartree (MCTDH) have been proposed for the solution of the coupled electron-nuclear dynamics, they remain hampered by an exponential scaling in the number of nuclear DOFs and by the difficulty of finding universal variational forms.In this Account, we present a perspective on novel quantum computational algorithms, aiming to alleviate the exponential scaling inherent to the simulation of many-body quantum dynamics. In particular, we focus on the derivation and application of quantum algorithms for adiabatic and non-adiabatic quantum dynamics, which include efficient approaches for the calculation of the BO potential energy surfaces (PESs). Thereafter, we study the time-evolution of a model system consisting of two coupled PESs in first and second quantization. In a first application, we discuss a recently introduced quantum algorithm for the evolution of a wavepacket in first quantization and exploit the potential quantum advantage of mapping its spatial grid representation to logarithmically many qubits. For the second demonstration, we move to the second quantization framework and review the scaling properties of two alternative time-evolution algorithms, namely, a variational quantum algorithm (VQA) (based on the McLachlan variational principle) and conventional Trotter-type evolution (based on a Lie-Trotter-Suzuki formula). Both methods clearly demonstrate the potential of quantum algorithms and their favorable scaling compared to the available classical approaches. However, a clear demonstration of quantum advantage in the context of molecular quantum dynamics may require the implementation of these algorithms in fault-tolerant quantum computers, while their application in near-term, noisy quantum devices is still unclear and deserves further investigation.

摘要

综述

在全面的量子框架内模拟分子动力学(MD)一直是计算化学领域长期面临的挑战。计算成本的指数级增长使得求解包含电子和核自由度(DOF)及其耦合的分子哈密顿量的含时薛定谔方程(TDSE)对于超过几个自由度的情况变得不可行。在玻恩 - 奥本海默(BO)近似或绝热图景中,波函数的电子部分和核部分解耦并分别处理。在此框架内,核波函数沿着作为核自由度参数化的电子薛定谔方程解计算得到的势能面(PES)演化。这种近似以及求解核含时薛定谔方程(TDSE)的日益精细的数值方法,使得能够处理多达几十个自由度(DOF)。然而,对于诸如光化学等特定应用,BO近似失效。在这种非绝热动力学 regime 中,求解包括电子 - 核耦合的完整分子问题变得至关重要,这进一步增加了数值解的复杂性。尽管已经提出了诸如多组态含时哈特里(MCTDH)等有价值的方法来求解耦合的电子 - 核动力学,但它们仍然受到核自由度数量的指数级增长以及寻找通用变分形式的困难的阻碍。

在本综述中,我们提出了关于新型量子计算算法的观点,旨在缓解多体量子动力学模拟中固有的指数级增长问题。特别是,我们专注于绝热和非绝热量子动力学的量子算法的推导和应用,其中包括计算BO势能面(PES)的有效方法。此后,我们研究了由两个耦合PES组成的模型系统在一次量子化和二次量子化中的时间演化。在第一个应用中,我们讨论了最近引入的用于一次量子化中波包演化的量子算法,并利用将其空间网格表示映射到对数多个量子比特的潜在量子优势。对于第二个演示,我们转向二次量子化框架,并回顾两种替代时间演化算法的缩放特性,即变分量子算法(VQA)(基于麦克拉克伦变分原理)和传统的 Trotter 型演化(基于李 - 特罗特 - 铃木公式)。与现有的经典方法相比,这两种方法都清楚地展示了量子算法的潜力及其良好的缩放特性。然而,在分子量子动力学背景下明确证明量子优势可能需要在容错量子计算机中实现这些算法,而它们在近期有噪声量子设备中的应用仍不明确,值得进一步研究。

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