Understanding and improving the Wang-Landau algorithm.

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