Abstract
A modified Monte Carlo (MC) method for efficient sampling of system outputs is derived by combining transition matrix Monte Carlo (TMMC) and Wang-Landau (WL) flat histogram methods. The proposed combination updates the estimation of the WL method using an intermediate estimate derived from the TMMC dynamics such that the variance of the resultant estimate is minimized. Combining the benefits of both methods, the new algorithm can estimate very low probabilities that are not normally reachable by the conventional MC using a realizable sample size.
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