Understanding and Improving the Wang-Landau Algorithm
Abstract
We present a mathematical analysis of the Wang-Landau algorithm, prove its convergence, identify sources of errors and strategies for optimization. In particular, we found the histogram increases uniformly with small fluctuation after a stage of initial accumulation, and the statistical error is found to scale as f with the modification factor f. This has implications for strategies for obtaining fast convergence.
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