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Journal Articles Mathematics of Computation Year : 2015

Convergence of the Wang-Landau algorithm


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-01238595 , version 1 (05-12-2015)



Gersende Fort, Benjamin Jourdain, Estelle Kuhn, Tony Lelièvre, Gabriel Stoltz. Convergence of the Wang-Landau algorithm. Mathematics of Computation, 2015, 84 (295), pp.2297-2327. ⟨10.1090/S0025-5718-2015-02952-4⟩. ⟨hal-01238595⟩
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