Single-Cluster Monte Carlo Dynamics for the Ising Model

نویسنده

  • P. Tamayo
چکیده

We present an extensive study of a new Monte Carlo acceleration algorithm introduced by Wolff for the Ising model. It differs from the Swendsen-Wang algorithm by growing and flipping single clusters at a random seed. In general, it is more efficient than Swendsen-Wang dynamics for d > 2, giving zero critical slowing down in the upper critical dimension. Monte Carlo simulations give dynamical critical exponents zw=0.33+0.05 and 0.44_+0.10 in d = 2 and 3, respectively, and numbers consistent with z w = 0 in d = 4 and mean-field theory. We present scaling arguments which indicate that the Wolff mechanism for decorrelation differs substantially from Swendsen Wang despite the apparent similarities of the two methods.

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تاریخ انتشار 1990