A Stochastic Monte Carlo Algorithm
نویسنده
چکیده
We propose a Monte Carlo algorithm to promote Kennedy and Kuti’s linear accept/reject algorithm which accommodates unbiased stochastic estimates of the probability to an exact one. The probability upper bound violations are avoided by adopting the Metropolis accept/reject steps for both the dynamical and noise configurations and the lower bound violations can be absorbed into the observables. We test it on the five state model and obtain desirable results. PACS numbers: 11.15.Ha, 02.70.Lq, 02.50.Ey On leave from Department of Physics, National Chung Hsing University, Taichung 40227, Taiwan, ROC Present address: Spatial Technologies, Boulder, CO
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تاریخ انتشار 1999