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Optimized Monte Carlo sampling in forward–backward semiclassical dynamics
Author(s) -
Kegerreis Jeb,
Makri Nancy
Publication year - 2007
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.20608
Subject(s) - semiclassical physics , statistical physics , monte carlo method , quantum monte carlo , quantization (signal processing) , importance sampling , variance reduction , monte carlo molecular modeling , molecular dynamics , quantum , operator (biology) , hybrid monte carlo , physics , mathematics , computer science , quantum mechanics , algorithm , markov chain monte carlo , chemistry , biochemistry , statistics , repressor , transcription factor , gene
Forward–backward semiclassical dynamics (FBSD) provides a rigorous and powerful methodology for calculating time correlation functions in condensed phase systems characterized by substantial quantum mechanical effects associated with zero‐point motion, quantum dispersion, or identical particle exchange symmetries. The efficiency of these simulations arises from the use of classical trajectories to capture all dynamical information. However, full quantization of the density operator makes these calculations rather expensive compared to fully classical molecular dynamics simulations. This article discusses the convergence properties of various correlation functions and introduces an optimal Monte Carlo sampling scheme that leads to a significant reduction of statistical error. A simple and efficient procedure for normalizing the FBSD results is also discussed. Illustrative examples on model systems are presented. © 2007 Wiley Periodicals, Inc. J Comput Chem 28: 818–824, 2007