Application of new Monte Carlo algorithms to random spin systems

Yutaka Okabe, Yusuke Tomita, Chiaki Yamaguchi

研究成果: Article査読

25 被引用数 (Scopus)

抄録

We explain the idea of the probability-changing cluster (PCC) algorithm, which is an extended version of the Swendsen-Wang algorithm. With this algorithm, we can tune the critical point automatically. We show the effectiveness of the PCC algorithm for the case of the three-dimensional (3D) Ising model. We also apply this new algorithm to the study of the 3D diluted Ising model. Since we tune the critical point of each random sample automatically with the PCC algorithm, we can investigate the sample-dependent critical temperature and the sample average of physical quantities at each critical temperature, systematically. We have also applied another newly proposed algorithm, the Wang-Landau algorithm, to the study of the spin glass problem.

本文言語English
ページ(範囲)63-68
ページ数6
ジャーナルComputer Physics Communications
146
1
DOI
出版ステータスPublished - 2002 6 15
外部発表はい

ASJC Scopus subject areas

  • ハードウェアとアーキテクチャ
  • 物理学および天文学(全般)

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