Monte Carlo techniques for real-time quantum dynamics

被引：10

作者：

Dowling, Mark R. ^{[1
]}

Davis, Matthew J. ^{[1
]}

Drummond, Peter D. ^{[1
]}

Corney, Joel F. ^{[1
]}

机构：

[1] Univ Queensland, Dept Phys, Sch Phys Sci, ARC Ctr Excellence Quantum Atom Opt, Brisbane, Qld 4072, Australia

来源：

JOURNAL OF COMPUTATIONAL PHYSICS | 2007年 / 220卷 / 02期

基金：

澳大利亚研究理事会;

关键词：

quantum dynamics; Monte Carlo; metropolis algorithm; branching algorithm; stochastic gauges; Bose-Einstein condensation;

D O I：

10.1016/j.jcp.2006.05.017

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The stochastic-gauge representation is a method of mapping the equation of motion for the quantum mechanical density operator onto a set of equivalent stochastic differential equations. One of the stochastic variables is termed the "weight", and its magnitude is related to the importance of the stochastic trajectory. We investigate the use of Monte Carlo algorithms to improve the sampling of the weighted trajectories and thus reduce sampling error in a simulation of quantum dynamics. The method can be applied to calculations in real time, as well as imaginary time for which Monte Carlo algorithms are more-commonly used. The Monte-Carlo algorithms are applicable when the weight is guaranteed to be real, and we demonstrate how to ensure this is the case. Examples are given for the anharmonic oscillator, where large improvements over stochastic sampling are observed. (c) 2006 Elsevier Inc. All rights reserved.

引用

页码：549 / 567

页数：19

共 38 条

[21]

Gardiner C., 1985, Handbook of stochastic methods, V3

[22]

Gardiner CW., 1999, Quantum noise

[23] Positive P representation: Application and validity [J].