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Journal Articles Applied Mathematics Research eXpress Year : 2014

Efficiency of the Wang-Landau Algorithm: A Simple Test Case

Abstract

We analyze the convergence properties of the Wang-Landau algorithm. This sampling method belongs to the general class of adaptive importance sampling strategies which use the free energy along a chosen reaction coordinate as a bias. Such algorithms are very helpful to enhance the sampling properties of Markov Chain Monte Carlo algorithms, when the dynamics is metastable. We prove the convergence of the Wang-Landau algorithm and an associated central limit theorem.

Dates and versions

hal-00721886 , version 1 (31-07-2012)

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Gersende Fort, Benjamin Jourdain, Estelle Kuhn, Tony Lelièvre, Gabriel Stoltz. Efficiency of the Wang-Landau Algorithm: A Simple Test Case. Applied Mathematics Research eXpress, 2014, 2014 (2), pp.275-311. ⟨10.1093/amrx/abu003⟩. ⟨hal-00721886⟩
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