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用于量子化学模拟的全量子本征求解器。

A Full Quantum Eigensolver for Quantum Chemistry Simulations.

作者信息

Wei Shijie, Li Hang, Long GuiLu

机构信息

Beijing Academy of Quantum Information Sciences, Beijing 100193, China.

State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics, Tsinghua University, Beijing 100084, China.

出版信息

Research (Wash D C). 2020 Mar 23;2020:1486935. doi: 10.34133/2020/1486935. eCollection 2020.

Abstract

Quantum simulation of quantum chemistry is one of the most compelling applications of quantum computing. It is of particular importance in areas ranging from materials science, biochemistry, and condensed matter physics. Here, we propose a full quantum eigensolver (FQE) algorithm to calculate the molecular ground energies and electronic structures using quantum gradient descent. Compared to existing classical-quantum hybrid methods such as variational quantum eigensolver (VQE), our method removes the classical optimizer and performs all the calculations on a quantum computer with faster convergence. The gradient descent iteration depth has a favorable complexity that is logarithmically dependent on the system size and inverse of the precision. Moreover, the FQE can be further simplified by exploiting a perturbation theory for the calculations of intermediate matrix elements and obtaining results with a precision that satisfies the requirement of chemistry application. The full quantum eigensolver can be implemented on a near-term quantum computer. With the rapid development of quantum computing hardware, the FQE provides an efficient and powerful tool to solve quantum chemistry problems.

摘要

量子化学的量子模拟是量子计算最引人注目的应用之一。它在材料科学、生物化学和凝聚态物理等领域尤为重要。在此,我们提出一种全量子本征解算器(FQE)算法,利用量子梯度下降来计算分子基态能量和电子结构。与现有的经典 - 量子混合方法(如变分量子本征解算器(VQE))相比,我们的方法去除了经典优化器,并在量子计算机上进行所有计算,收敛速度更快。梯度下降迭代深度具有良好的复杂度,它对数依赖于系统大小和精度的倒数。此外,通过利用微扰理论计算中间矩阵元,并以满足化学应用要求的精度获得结果,FQE 可以进一步简化。全量子本征解算器可以在近期量子计算机上实现。随着量子计算硬件的快速发展,FQE 为解决量子化学问题提供了一种高效且强大的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da12/7125455/87474c74e205/RESEARCH2020-1486935.001.jpg

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