Probability-Changing Cluster Algorithm: Study of Three-Dimensional Ising Model and Percolation Problem

Details Probability-Changing Cluster Algorithm: Study of Three-Dimensional Ising Model and Percolation Problem Probability-Changing Cluster Algorithm: Study of Three-Dimensional Ising Model and Percolation Problem

2002-03-22

arxiv.org/abs/cond-mat/0203454v1

J. Phys. Soc. Jpn. 71, 1570-1575 (2002)

Physics

Condensed Matter

Statistical Mechanics

6 pages including 8 eps figures, to appear in J. Phys. Soc. Jpn

Scientific paper

10.1143/JPSJ.71.1570

We present a detailed description of the idea and procedure for the newly proposed Monte Carlo algorithm of tuning the critical point automatically, which is called the probability-changing cluster (PCC) algorithm [Y. Tomita and Y. Okabe, Phys. Rev. Lett. {\bf 86} (2001) 572]. Using the PCC algorithm, we investigate the three-dimensional Ising model and the bond percolation problem. We employ a refined finite-size scaling analysis to make estimates of critical point and exponents. With much less efforts, we obtain the results which are consistent with the previous calculations. We argue several directions for the application of the PCC algorithm.

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