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Existence, uniqueness and convergence of a particle approximation for the AdaptiveBiasing Force process

Published online by Cambridge University Press:  26 August 2010

Benjamin Jourdain ,
Tony Lelièvre  and
Raphaël Roux
Benjamin Jourdain
Affiliation:
Université Paris-Est, CERMICS, 6 et 8 avenue Blaise Pascal, 77455 Marne-La-Vallée Cedex 2, France.
Tony Lelièvre
Affiliation:
Université Paris-Est, CERMICS, Project-Team MICMAC ENPC-INRIA, 6 et 8 avenue Blaise Pascal, 77455 Marne-La-Vallée Cedex 2, France. lelievre@cermics.enpc.fr
Raphaël Roux
Affiliation:
Université Paris-Est, CERMICS, Project-Team MICMAC ENPC-INRIA, 6 et 8 avenue Blaise Pascal, 77455 Marne-La-Vallée Cedex 2, France. lelievre@cermics.enpc.fr
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Abstract

We study a free energy computation procedure, introduced in [Darve and Pohorille, J. Chem. Phys.115 (2001) 9169–9183; Hénin and Chipot, J. Chem. Phys.121 (2004) 2904–2914], which relies on the long-time behavior of a nonlinear stochastic differential equation. This nonlinearity comes from a conditional expectation computed with respect to one coordinate of the solution. The long-time convergence of the solutions to this equation has been proved in [Lelièvre et al., Nonlinearity21 (2008) 1155–1181], under some existence and regularity assumptions. In this paper, we prove existence and uniqueness under suitable conditions for the nonlinear equation, and we study a particle approximation technique based on a Nadaraya-Watson estimator of the conditional expectation. The particle system converges to the solution of the nonlinear equation if the number of particles goes to infinity and then the kernel used in the Nadaraya-Watson approximation tends to a Dirac mass. We derive a rate for this convergence, and illustrate it by numerical examples on a toy model.

Keywords

Conditional McKean nonlinearityinteracting particle systemsAdaptive Biasing Force method
Type
Research Article
Information
ESAIM: Mathematical Modelling and Numerical Analysis , Volume 44 , Issue 5: Special Issue on Probabilistic methods and their applications , September 2010 , pp. 831 - 865
Copyright
© EDP Sciences, SMAI, 2010

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