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Pré-publication, Document de travail

Estimation of statistics of transitions and Hill relation for Langevin dynamics

Abstract : In molecular dynamics, statistics of transitions, such as the mean transition time, are macroscopic observables which provide important dynamical information on the underlying microscopic stochastic process. A direct estimation using simulations of microscopic trajectories over long time scales is typically computationally intractable in metastable situations. To overcome this issue, several numerical methods rely on a potential-theoretic identity, sometimes attributed to Hill in the computational statistical physics litterature, which expresses statistics of transitions in terms of the invariant measure of the sequence of configurations by which the underlying process enters metastable sets. The use of this identity then allows to replace the long time simulation problem with a rare event sampling problem, for which efficient algorithms are available. In this article, we rigorously analyse such a method for molecular systems modelled by the Langevin dynamics. Our main contributions are twofold. First, we prove the Hill relation in the fairly general context of positive Harris recurrent chains, and show that this formula applies to the Langevin dynamics. Second, we provide an explicit expression of the invariant measure involved in the Hill relation, and describe an elementary exact simulation procedure. Overall, this yields a simple and complete numerical method to estimate statistics of transitions.
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Pré-publication, Document de travail
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Contributeur : Julien Reygner Connectez-vous pour contacter le contributeur
Soumis le : jeudi 23 juin 2022 - 16:26:33
Dernière modification le : mardi 2 août 2022 - 03:21:11


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  • HAL Id : hal-03659510, version 2
  • ARXIV : 2206.13264



Tony Lelièvre, Mouad Ramil, Julien Reygner. Estimation of statistics of transitions and Hill relation for Langevin dynamics. 2022. ⟨hal-03659510v2⟩



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