Rare-Event Sampling: Occupation-Based Performance Measures for Parallel Tempering and Infinite Swapping Monte Carlo Methods

Authors

J. D. Doll
Nuria Plattner
David L. Freeman, University of Rhode IslandFollow
Yufei Lu
Paul Dupuis

Document Type

Article

Date of Original Version

11-27-2012

Department

Chemistry

Abstract

In the present paper we identify a rigorous property of a number of tempering-based Monte Carlo sampling methods, including parallel tempering as well as partial and infinite swapping. Based on this property we develop a variety of performance measures for such rare-event sampling methods that are broadly applicable, informative, and straightforward to implement. We illustrate the use of these performance measures with a series of applications involving the equilibrium properties of simple Lennard-Jones clusters, applications for which the performance levels of partial and infinite swapping approaches are found to be higher than those of conventional parallel tempering.

Citation/Publisher Attribution

Doll, J. D., Plattner, N., Freeman, D. L., Liui, Y., & Dupuis, P. (2012). Rare-Event Sampling: Occupation-Based Performance Measures for Parallel Tempering and Infinite Swapping Monte Carlo Methods. Journal of Chemical Physics, 137(20), #204112. doi: 10.1063/1.4765060

Available at: http://dx.doi.org/10.1063/1.4765060

Publisher Statement

© 2012 American Institute of Physics.