Simulated Tempering: A New Monte Carlo Scheme

Abstract

We propose a new global optimization method ({\em Simulated Tempering}) for simulating effectively a system with a rough free energy landscape (i.e. many coexisting states) at finite non-zero temperature. This method is related to simulated annealing, but here the temperature becomes a dynamic variable, and the system is always kept at equilibrium. We analyze the method on the Random Field Ising Model, and we find a dramatic improvement over conventional Metropolis and cluster methods. We analyze and discuss the conditions under which the method has optimal performances.

12 pages, very simple LaTeX file, figures are not included, sorry

References in corpus (2)

• Multicanonical Ensemble: A New Approach to Simulate First-order Phase Transitions
• A New Approach to Spin Glass Simulations

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