Friday, August 31, 2012

1208.6190 (J. D. Doll et al.)

Rare-Event Sampling: Occupation-Based Performance Measures for Parallel
Tempering and Infinite Swapping Monte Carlo Methods
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J. D. Doll, Nuria Plattner, David L. Freeman, Yufei Liu, Paul Dupuis
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.
View original: http://arxiv.org/abs/1208.6190

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