Premium
The force matching approach to multiscale simulations: Merits, shortcomings, and future perspectives
Author(s) -
Masia Marco,
Guàrdia Elvira,
Nicolini Paolo
Publication year - 2014
Publication title -
international journal of quantum chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 105
eISSN - 1097-461X
pISSN - 0020-7608
DOI - 10.1002/qua.24621
Subject(s) - computer science , matching (statistics) , force field (fiction) , scale (ratio) , field (mathematics) , perspective (graphical) , function (biology) , quality (philosophy) , statistical physics , algorithm , mathematics , artificial intelligence , physics , statistics , quantum mechanics , evolutionary biology , pure mathematics , biology
Among the various approaches to multiscale simulations, in recent years, force matching has been known for a quick growth. The method is based on a least‐square fit of reference properties obtained from simulations at a certain scale, to parameterize the force field for coarser‐grained scale simulations. Its advantage with respect to conventional schemes used for parameterizing force fields, lies in that only physically accessible configurations are sampled, and that the number of reference data per configuration is large. In this perspective article, we discuss some recent findings on the tailoring of the objective function, on the choice of the empirical potential, and on the way to improve the quality of the reference calculations. We present pros and cons of the algorithm, and we propose a road map to future developments. © 2014 Wiley Periodicals, Inc.