Bayesian calibration of coarse-grained forces: Efficiently addressing transferability

Abstract

Generating and calibrating forces that are transferable across a range of state-points remains a challenging task in coarse-grained (CG) molecular dynamics (MD). In this work, we present a coarse-graining workflow, inspired by ideas from uncertainty quantification and numerical analysis, to address this problem. The key idea behind our approach is to introduce a Bayesian correction algorithm that uses functional derivatives of CG simulations to rapidly and inexpensively recalibrate initial estimates f0 of forces anchored by standard methods such as Force-Matching (FM). Taking density-temperature relationships as a running example, we demonstrate that this algorithm, in concert with various interpolation schemes, can be used to efficiently compute physically reasonable force curves on a fine grid of state-points. Importantly, we show that our work flow is robust to several choices available to the modeler, including the interpolation schemes and tools used to construct f0. In a related vein, we also demonstrate that our approach can speed up coarse-graining by reducing the number of atomistic simulations needed as inputs to standard methods for generating CG forces.

A Review of Multiscale Computational Methods in Polymeric Materials

“…Using calibration methods in order to improve the transferability of derived CG potentials is also an interesting possibility. Recently, inspired by ideas from uncertainty quantification and numerical analysis, Patrone et al [ 383 ] used a Bayesian correction algorithm [ 384 ] to efficiently generate transferable CG forces. Their method uses functional derivatives of CG simulations to rapidly recalibrate initial estimates of forces anchored by standard methods such as force-matching.…”

A Parallel Multiscale Simulation Framework for Complex Polymerization: AB2‐Type Monomer Hyperbranched Polymerization as an Example

“…The reason is that the coarse‐grained force field comes from two predefined training systems, a monomer system and a hexamer system, as shown in Section 2.2. The coarse‐grained force field obtained with the IBI method is not transferable during the change either in temperature or concentration because of the strong state dependence . Moreover, it is also not transferable during the reaction.…”

Uncertainty Quantification for Molecular Dynamics

“…Recently, strategies for addressing some of these issues have begun to emerge, especially in the context of coarse-grained MD. 25,[44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59] In the following we assume that the force-fields are both fixed and suitable as given.…”