Long-time convergence of an adaptive biasing force method: Variance reduction by Helmholtz projection
The SMAI journal of computational mathematics, Volume 1 (2015) , pp. 55-82.

In this paper, we propose an improvement of the adaptive biasing force (ABF) method, by projecting the estimated mean force onto a gradient. We 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. The associated stochastic process satisfies a nonlinear stochastic differential equation. Using entropy techniques, we prove exponential convergence to the stationary state of this stochastic process.

Published online:
DOI: https://doi.org/10.5802/smai-jcm.4
Keywords: Adaptive biasing force; Helmholtz projection; Free energy; Variance reduction.
@article{SMAI-JCM_2015__1__55_0,
author = {Houssam Alrachid and Tony Leli\evre},
title = {Long-time convergence of an adaptive biasing force method: Variance reduction by Helmholtz projection},
journal = {The SMAI journal of computational mathematics},
pages = {55--82},
publisher = {Soci\'et\'e de Math\'ematiques Appliqu\'ees et Industrielles},
volume = {1},
year = {2015},
doi = {10.5802/smai-jcm.4},
mrnumber = {3620370},
zbl = {1416.65015},
language = {en},
url = {https://smai-jcm.centre-mersenne.org/articles/10.5802/smai-jcm.4/}
}
Houssam Alrachid; Tony Lelièvre. Long-time convergence of an adaptive biasing force method: Variance reduction by Helmholtz projection. The SMAI journal of computational mathematics, Volume 1 (2015) , pp. 55-82. doi : 10.5802/smai-jcm.4. https://smai-jcm.centre-mersenne.org/articles/10.5802/smai-jcm.4/`

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