Bayesian Calibration of Coarse -
نویسندگان
چکیده
Generating and calibrating forces that are transferable across a range of state-points 6 remains a challenging task in coarse-grained (CG) molecular dynamics (MD). In 7 this work, we present a coarse-graining workflow, inspired by ideas from uncertainty 8 quantification and numerical analysis, to address this problem. The key idea behind 9 our approach is to introduce a Bayesian correction algorithm that uses functional 10 derivatives of CG simulations to rapidly and inexpensively recalibrate initial estimates 11 f0 of forces anchored by standard methods such as Force-Matching (FM). Taking 12 density-temperature relationships as a running example, we demonstrate that this 13 algorithm, in concert with various interpolation schemes, can be used to efficiently 14 compute physically reasonable force curves on a fine grid of state-points. Importantly, 15 we show that our workflow is robust to several choices available to the modeler, 16 including the interpolation schemes and tools used to construct f0. In a related vein, 17 we also demonstrate that our approach can speed up coarse-graining by reducing the 18 number of atomistic simulations needed as inputs to standard methods for generating 19 CG forces. 20
منابع مشابه
Calibration and Ranking of Coarse-grained Models in Molecular Simulations Using Bayesian Formalism
CALIBRATION AND RANKING OF COARSE-GRAINED MODELS IN MOLECULAR SIMULATIONS USING BAYESIAN FORMALISM Hadi Meidani,1,∗ Justin B. Hooper,2 Dmitry Bedrov,2 & Robert M. Kirby3 1Department of Civil and Environmental Engineering, 1211 Newmark Civil Engineering Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61822, USA 2Department of Materials Science & Engineering, 206 Civil and Mate...
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