期刊
JOURNAL OF STATISTICAL PHYSICS
卷 98, 期 1-2, 页码 321-345出版社
KLUWER ACADEMIC/PLENUM PUBL
DOI: 10.1023/A:1018635108073
关键词
statistical mechanics; variance reduction; Monte Carlo algorithms; Metropolis algorithm; statistical estimators; Ising model; histogram methods; transition probabilities
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.
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