NEW MONTE-CARLO ALGORITHM - ENTROPIC SAMPLING

被引：471

作者：

LEE, J

机构：

[1] Supercomputer Computations Research Institute B-186, Florida State University, Tallahassee

来源：

PHYSICAL REVIEW LETTERS | 1993年 / 71卷 / 02期

关键词：

D O I：

10.1103/PhysRevLett.71.211

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

We present a new Monte Carlo sampling algorithm, with which one can obtain any desired distribution of the sampling in one Monte Carlo simulation. The free energy and the entropy of a system can thus be obtained from a simple exercise of this algorithm. The main idea is to sample directly the entropy of a system at infinite temperature. Importance sampling is shown to be a particular case of the new algorithm. The algorithm is tested against the exact partition function of the L = 4 simple cubic Ising model. A comparison with the multicanonical ensemble for the L = 12, q = 10 Potts model shows that the new algorithm is more general and more efficient.

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页码：211 / 214

页数：4

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