Statistical approaches to forcefield calibration and prediction uncertainty in molecular simulation

Abstract

Calibration of forcefields for molecular simulation should account for the measurement uncertainty of the reference dataset and for the model inadequacy, i.e., the inability of the force-field/simulation pair to reproduce experimental data within their uncertainty range. In all rigour, the resulting uncertainty of calibrated force-field parameters is a source of uncertainty for simulation predictions. Various calibration strategies and calibration models within the Bayesian calibration/prediction framework are explored in the present article. In the case of Lennard-Jones potential for Argon, we show that prediction uncertainty for thermodynamical and transport properties, albeit very small, is larger than statistical simulation uncertainty.