Probability-Changing Cluster Algorithm for Potts Models

Abstract

We propose a new effective cluster algorithm of tuning the critical point automatically, which is an extended version of Swendsen-Wang algorithm. We change the probability of connecting spins of the same type, $p=1-e^{-J/k_{B}T}$, in the process of the Monte Carlo spin update. Since we approach the canonical ensemble asymptotically, we can use the finite-size scaling analysis for physical quantities near the critical point. Simulating the two-dimensional Potts models to demonstrate the validity of the algorithm, we have obtained the critical temperatures and critical exponents which are consistent with the exact values; the comparison has been made with the invaded cluster algorithm.

4 pages including 5 eps figures, RevTeX, to appear in Phys. Rev. Lett

References in corpus (1)

• Cluster Analysis and Finite-Size Scaling for Ising Spin Systems

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