Applications of the Probability-Changing Cluster Algorithm and Related Problems

We describe the idea of the newly proposed efficient algorithpi of tuning the critical point automatically. This probability-changing cluster (PCC) algorithm is an extended version of the Swendsen-Wang algorithm. As an application of the PCC algorithm, we study the two-dimensional site-diluted Ising model, paying attention to the self-averaging property. We also use another newly proposed algorithm, the Wang-Landau algorithm, for the study of the three-dimensional antiferromagnetic q-state Potts models.

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