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Journal Articles Electronic Journal of Probability Year : 2020

Analysis of an Adaptive Biasing Force method based on self-interacting dynamics

Abstract

This article fills a gap in the mathematical analysis of Adaptive Biasing algorithms, which are extensively used in molecular dynamics computations. Given a reaction coordinate, ideally, the bias in the overdamped Langevin dynamics would be given by the gradient of the associated free energy function, which is unknown. We consider an adaptive biased version of the overdamped dynamics, where the bias depends on the past of the trajectory and is designed to approximate the free energy. The main result of this article is the consistency and efficiency of this approach. More precisely we prove the almost sure convergence of the bias as time goes to infinity, and that the limit is close to the ideal bias, as an auxiliary parameter of the algorithm goes to 0. The proof is based on interpreting the process as a self-interacting dynamics, and on the study of a non-trivial fixed point problem for the limiting flow obtained using the ODE method.
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Dates and versions

hal-02310672 , version 1 (10-10-2019)

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Michel Benaïm, Charles-Edouard Bréhier, Pierre Monmarché. Analysis of an Adaptive Biasing Force method based on self-interacting dynamics. Electronic Journal of Probability, 2020, ⟨10.1214/20-EJP490⟩. ⟨hal-02310672⟩
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