Document Detail

Coarse-graining errors and numerical optimization using a relative entropy framework.
MedLine Citation:
PMID:  21384955     Owner:  NLM     Status:  In-Data-Review    
The ability to generate accurate coarse-grained models from reference fully atomic (or otherwise "first-principles") ones has become an important component in modeling the behavior of complex molecular systems with large length and time scales. We recently proposed a novel coarse-graining approach based upon variational minimization of a configuration-space functional called the relative entropy, S(rel), that measures the information lost upon coarse-graining. Here, we develop a broad theoretical framework for this methodology and numerical strategies for its use in practical coarse-graining settings. In particular, we show that the relative entropy offers tight control over the errors due to coarse-graining in arbitrary microscopic properties, and suggests a systematic approach to reducing them. We also describe fundamental connections between this optimization methodology and other coarse-graining strategies like inverse Monte Carlo, force matching, energy matching, and variational mean-field theory. We suggest several new numerical approaches to its minimization that provide new coarse-graining strategies. Finally, we demonstrate the application of these theoretical considerations and algorithms to a simple, instructive system and characterize convergence and errors within the relative entropy framework.
Aviel Chaimovich; M Scott Shell
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  The Journal of chemical physics     Volume:  134     ISSN:  1089-7690     ISO Abbreviation:  J Chem Phys     Publication Date:  2011 Mar 
Date Detail:
Created Date:  2011-03-09     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0375360     Medline TA:  J Chem Phys     Country:  United States    
Other Details:
Languages:  eng     Pagination:  094112     Citation Subset:  IM    
Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California 93106-5080, USA.
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