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Theoretical and numerical comparison of some sampling methods for molecular dynamics

Published online by Cambridge University Press:  16 June 2007

Eric Cancès ,
Frédéric Legoll  and
Gabriel Stoltz
Eric Cancès
Affiliation:
CERMICS, École Nationale des Ponts et Chaussées, 6-8 avenue Blaise Pascal, 77455 Marne-la-Vallée Cedex 2, France. [email protected]; [email protected]; [email protected] INRIA, Domaine de Voluceau-Rocquencourt, B.P. 105, 78153 Le Chesnay Cedex, France.
Frédéric Legoll
Affiliation:
CERMICS, École Nationale des Ponts et Chaussées, 6-8 avenue Blaise Pascal, 77455 Marne-la-Vallée Cedex 2, France. [email protected]; [email protected]; [email protected] Institute for Mathematics and its Applications, University of Minnesota, 400 Lind Hall, 207 Church Street SE, Minneapolis MN 55455, USA.
Gabriel Stoltz
Affiliation:
CERMICS, École Nationale des Ponts et Chaussées, 6-8 avenue Blaise Pascal, 77455 Marne-la-Vallée Cedex 2, France. [email protected]; [email protected]; [email protected] CEA/DAM Ile-de-France, BP 12, 91680 Bruyères-le-Châtel, France.
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Abstract

The purpose of the present article is to compare different phase-spacesampling methods, such as purely stochastic methods (Rejection method, Metropolized independence sampler, Importance Sampling),stochastically perturbed Molecular Dynamics methods (Hybrid Monte Carlo, Langevin Dynamics, Biased Random Walk), and purelydeterministic methods (Nosé-Hoover chains, Nosé-Poincaré and RecursiveMultiple Thermostats (RMT) methods). After recalling some theoretical convergence properties forthe various methods, we provide some new convergence resultsfor the Hybrid Monte Carlo scheme, requiring weaker (and easier tocheck) conditions than previously known conditions. We then turn to the numericalefficiency of the sampling schemes for a benchmark model of linearalkane molecules. In particular, the numerical distributions that are generated are compared in a systematic way, on the basisof some quantitative convergence indicators.

Keywords

Sampling methodscanonical ensembleMolecular Dynamics.
Type
Research Article
Information
ESAIM: Mathematical Modelling and Numerical Analysis , Volume 41 , Issue 2: Special issue on Molecular Modelling , March 2007 , pp. 351 - 389
Copyright
© EDP Sciences, SMAI, 2007

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