A Numerical Code for Automated Calculation of Coarse-Grained Potentials using the Iterative Boltzmann Inversion (IBI) Method

Iterative Boltzmann Inversion (IBI) is a systematic coarse-graining (CG) method in which tabular CG potentials are derived that reproduce target distributions generated from atomistic reference simulations. In IBI, an initial guess for the CG bonded and pair potential is iteratively refined by means of a correction proportional to the difference between the all-atom (AA) targets and coarse-grained potentials of the mean force. We report here on a software code which automates the development of coarse-grained potentials using IBI. Two major problems make automation difficult: 1) noisy distributions derived from sampling; 2) low sampling regions which introduces discontinuities in the sampling. Both of these make differentiation to calculate energy and forces difficult and error prone. Our approach addresses these problems by use of an approach which combines data smoothing, fitting to functional expansions (bonded potentials), and flexible extrapolation schemes to handle low sampling regions without discontinuity or data distortion. We also introduce a library to automate the conversion of AA to CG representations and have designed an input-output framework which aims at providing reproducibility. Some use cases for polymers will be discussed aimed at providing guidance on usage.