Relative entropy code#
Relative entropy free#

Generally, CG systems are limited in their representability and transferability, i.e., they cannot simultaneously reproduce all of the properties of interest and they may not be applicable for thermodynamic states far away from the one at which the system was parametrized. For instance, when replacing a water molecule by a single sphere, one loses information about the molecule’s orientation. Īlthough coarse-grained simulations allow one to reach longer time- and length-scales, they also, by definition, lose some information from the underlying reference system. Such coarse-graining leads to a significant speed-up in the molecular dynamics (MD) simulations due to i) a reduced number of degrees of freedom and hence, the number of interactions to compute, ii) smoother interaction potentials among CG particles that enable larger time steps, and most importantly, iii) a speedup in the intrinsic dynamics of the system which leads to faster diffusion and thus, shorter equilibration times.

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In a coarse-grained representation, several atoms are grouped into a single CG unit and the effective interactions between them are determined. Here, we focus on the bottom-up approaches of coarse-graining (CG), which create a systematic link between two particle based descriptions of a given system by building a lower resolution model based on a reference higher resolution model.

In recent years, coarse-grained simulations have become an important tool for investigating systems on larger time- and length-scales. This does not alter the authors’ adherence to all of the PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products to declare. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: Nestlé Research Center partly funded this study. LANL is operated by Los Alamos National Security, LLC, for the National Nuclear Security Administration of the U.S. MNJ acknowledges DFG Emmy Noether program for financial support. Koschke acknowledges funding by the Nestlé Research Center. CJ thanks LANL for a Director’s fellowship and the MPG for hospitality in 2013 at MPI-P. This research was supported in part by the National Science Foundation under grant number NSF PHY11-25915. CJ was financially supported by SFB 625 in the framework of the multiscale modeling initiative of the Max-Planck Society (M3). įunding: SYM and NRA acknowledge financial support by the NSF under grant Nos. The input files to the simulations shown in the paper have been published here.

Relative entropy code#

The work is made available under the Creative Commons CC0 public domain dedicationĭata Availability: The code with which the simulation has been performed can be found here.

Relative entropy free#

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. Received: NovemAccepted: JPublished: July 20, 2015 Hong Kong University of Science and Technology, HONG KONG Citation: Mashayak SY, Jochum MN, Koschke K, Aluru NR, Rühle V, Junghans C (2015) Relative Entropy and Optimization-Driven Coarse-Graining Methods in VOTCA.