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| HAL: hal-00721886, version 1 |
| arXiv: 1207.6880 |
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| Convergence and efficiency of the Wang-Landau algorithm |
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| Gersende Fort 1Benjamin Jourdain 2 |
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| (2012-07-30) |
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| 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 dynamic is metastable. We prove that the Wang-Landau algorithm converges with an associated central limit theorem, and we provide an analysis of the efficiency of the algorithm in a metastable situation. |
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| 1: | Laboratoire Traitement et Communication de l'Information [Paris] (LTCI) |
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Télécom ParisTech – CNRS : UMR5141 |
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| 2: | Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique (CERMICS) |
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Ecole des Ponts ParisTech |
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| 3: | Mathématiques et Informatique Appliquées (MIA) |
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Institut national de la recherche agronomique (INRA) : UMR0518 – AgroParisTech |
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| 4: | MICMAC (INRIA Paris - Rocquencourt) |
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Ecole des Ponts ParisTech – INRIA |
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| Domain | : | Mathematics/Probability Statistics/Statistics Theory |
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| Fulltext link |
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| http://fr.arXiv.org/abs/1207.6880 |
| hal-00721886, version 1 | |
| http://hal.inria.fr/hal-00721886 | |
| oai:hal.inria.fr:hal-00721886 | |
| From: Tony Lelievre | |
| Submitted on: Tuesday, 31 July 2012 08:19:43 | |
| Updated on: Wednesday, 9 January 2013 10:18:34 | |
