Markov chain Monte Carlo | Statistical algorithms

Wang and Landau algorithm

The Wang and Landau algorithm, proposed by Fugao Wang and David P. Landau, is a Monte Carlo method designed to estimate the density of states of a system. The method performs a non-Markovian random walk to build the density of states by quickly visiting all the available energy spectrum. The Wang and Landau algorithm is an important method to obtain the density of states required to perform a multicanonical simulation. The Wang–Landau algorithm can be applied to any system which is characterized by a cost (or energy) function. For instance,it has been applied to the solution of numerical integrals and the folding of proteins.The Wang–Landau sampling is related to the metadynamics algorithm. (Wikipedia).

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Estimator | Random walk | Metropolis–Hastings algorithm | Monte Carlo method | Density of states | Multicanonical ensemble | Stochastic process | Harmonic oscillator