Long-time convergence of an adaptive biasing force method: Variance reduction by Helmholtz projection - Archive ouverte HAL
Article Dans Une Revue SMAI Journal of Computational Mathematics Année : 2015

Long-time convergence of an adaptive biasing force method: Variance reduction by Helmholtz projection

Résumé

In this paper, we propose an improvement of the adaptive biasing force (ABF) method, by projecting the estimated mean force onto a gradient. The associated stochastic process satisfies a non linear stochastic differential equation. Using entropy techniques, we prove exponential convergence to the stationary state of this stochastic process. We finally show on some numerical examples that the variance of the approximated mean force is reduced using this technique, which makes the algorithm more efficient than the standard ABF method.
Fichier principal
Vignette du fichier
PABF.pdf (969.97 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01151894 , version 1 (13-05-2015)

Identifiants

Citer

Houssam Alrachid, Tony Lelièvre. Long-time convergence of an adaptive biasing force method: Variance reduction by Helmholtz projection. SMAI Journal of Computational Mathematics, 2015, 1, pp.55 - 82. ⟨10.5802/smai-jcm.4⟩. ⟨hal-01151894⟩
205 Consultations
113 Téléchargements

Altmetric

Partager

More