title: An efficient sampling algorithm for variational Monte Carlo.
abstract: We propose a new algorithm for sampling the N-body density mid R:Psi(R)mid R:(2)R(3N)mid R:Psimid R:(2) in the variational Monte Carlo framework. This algorithm is based upon a modified Ricci-Ciccotti discretization of the Langevin dynamics in the phase space (R,P) improved by a Metropolis-Hastings accept/reject step. We show through some representative numerical examples (lithium, fluorine, and copper atoms and phenol molecule) that this algorithm is superior to the standard sampling algorithm based on the biased random walk (importance sampling).
authors.affiliation: CERMICS and INRIA Project Micmac, Ecole Nationale des Ponts et Chaussées, 6 et 8 Avenue Blaise Pascal, Cité Descartes-Champs sur Marne, 77455 Marne la Vallée Cedex 2, France. scemam@cermics.enpc.fr
authors.forename: Anthony
authors.initials: A
authors.lastname: Scemama
authors.forename: Tony
authors.initials: T
authors.lastname: Lelièvre
authors.forename: Gabriel
authors.initials: G
authors.lastname: Stoltz
authors.forename: Eric
authors.initials: E
authors.lastname: Cancès
authors.forename: Michel
authors.initials: M
authors.lastname: Caffarel