skip to main content

DOE PAGESDOE PAGES

Title: Rigorous force field optimization principles based on statistical distance minimization

We use the concept of statistical distance to define a measure of distinguishability between a pair of statistical mechanical systems, i.e., a model and its target, and show that its minimization leads to general convergence of the model’s static measurable properties to those of the target. Here we exploit this feature to define a rigorous basis for the development of accurate and robust effective molecular force fields that are inherently compatible with coarse-grained experimental data. The new model optimization principles and their efficient implementation are illustrated through selected examples, whose outcome demonstrates the higher robustness and predictive accuracy of the approach compared to other currently used methods, such as force matching and relative entropy minimization. We also discuss relations between the newly developed principles and established thermodynamic concepts, which include the Gibbs-Bogoliubov inequality and the thermodynamic length.
Authors:
 [1] ;  [2]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Chemical Sciences Division; Univ. of Tennessee, Knoxville, TN (United States). Joint Inst. for Computational Sciences
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Chemical Sciences Division
Publication Date:
Grant/Contract Number:
AC05-00OR22725
Type:
Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Volume: 143; Journal Issue: 14; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics (AIP)
Research Org:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS Statistical mechanics models; Entropy; Probability theory; Particle distribution functions; Thermodynamic properties
OSTI Identifier:
1366366
Alternate Identifier(s):
OSTI ID: 1366366