期刊
JOURNAL OF CHEMICAL PHYSICS
卷 134, 期 9, 页码 -出版社
AMER INST PHYSICS
DOI: 10.1063/1.3557038
关键词
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资金
- Camille & Henry Dreyfus Foundation
- National Science Foundation [CBET-0845074]
- Directorate For Engineering [845074] Funding Source: National Science Foundation
- Div Of Chem, Bioeng, Env, & Transp Sys [845074] Funding Source: National Science Foundation
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. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3557038]
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