Convergence estimation of flat-histogram algorithms based on simulation results.

The present work considers the question of convergence of Wang–Landau, multi-canonical and stochastic approximation Monte Carlo algorithms, which was previously investigated on very different levels. In the case of the multi-canonical algorithms, a convergence behavior similar to either the original Wang–Landau or the stochastic approximation Monte Carlo algorithms is shown, depending on details of the algorithm. I suggest a method for error estimation based only on the results of simulations, not involving an information about the exact density of states, which is unknown for most practically interesting problems. [ABSTRACT FROM AUTHOR]