Monte Carlo transition dynamics and variance reduction

被引：81

作者：

Fitzgerald, M ^{[1
]}

Picard, RR ^{[1
]}

Silver, RN ^{[1
]}

机构：

[1] Univ Calif Los Alamos Natl Lab, Los Alamos, NM 87545 USA

来源：

JOURNAL OF STATISTICAL PHYSICS | 2000年 / 98卷 / 1-2期

关键词：

statistical mechanics; variance reduction; Monte Carlo algorithms; Metropolis algorithm; statistical estimators; Ising model; histogram methods; transition probabilities;

D O I：

10.1023/A:1018635108073

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

For Metropolis Monte Carlo simulations in statistical physics, efficient, easy-to-implement, and unbiased statistical estimators of thermodynamic properties are based on the transition dynamics. Using an Ising model example, we demonstrate (problem-specific) variance reductions compared to conventional histogram estimators. A proof of variance reduction in a microstate limit is presented.

引用

页码：321 / 345

页数：25

共 15 条

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