量子蒙特卡洛模拟——随机级数展开方法  

Quantum Monte Carlo Simulation——Stochastic Series Expansion Method

作　　者：张学锋 ZHANG Xuefeng(Department of Physics,Chongqing University,Chongqing 401331,China)

机构地区：[1]重庆大学物理学院,重庆401331

出　　处：《山西大学学报（自然科学版）》2022年第3期734-743,共10页Journal of Shanxi University(Natural Science Edition)

基　　金：国家自然科学基金(11874094)。

摘　　要：强关联量子多体系统,由于粒子间相互作用较大,导致传统的微扰论失效。因此,绝大多数问题需要依托大规模数值计算进行模拟。其中,量子蒙特卡洛模拟方法以其大尺寸,高精度和模拟丰富的物理量等特点被广泛采用。而具有代表性的随机级数展开方法还兼顾了较好的算法可读性,从而更便于进行程序实现。文章将回顾随机级数展开方法的最基本理论,并介绍一种应用于团簇算法的权重计算方法,之后着重介绍并行退火方法。In the strongly correlated quantum many body systems,the interactions between particles are so strong that the perturbation theory fails.Thus,most of the problems can only be simulated by large-scale numerical methods.As one of widely adopted algorithms,the quantum Monte Carlo simulation method has several features,such as large-scale,high precision and simulating numerous physical observables.As the typical one,the stochastic series expansion method presents strong readability which makes it easy for coding.In this paper,the basic theory of stochastic series expansion method is firstly reviewed.Then,a method of calculating transferring possibilities is introduced.Finally,the parallel tempering method is discussed in detail.

关 键 词：强关联数值方法 量子蒙特卡洛方法 量子多体理论 并行退火 

分 类 号：O469[理学—凝聚态物理]