Bridging coarse-grained models by jump-in-sample simulations

We present an efficient method to construct coarse-grained (CG) models from models of finer resolution. The method estimates the free energies in a generated sample of the CG conformational space and then fits the entire effective potential surface in the high-dimensional CG conformational space. A jump-in-sample algorithm that uses a random jumping walk in the CG sample is used to iteratively estimate the free energies. We test the method in a tetrahedral molecular fluid where we construct the intermolecular effective potential and evaluate the CG molecular model. Our algorithm for calculating the free energy involves an improved Wang-Landau (WL) algorithm, which not only works more efficiently than the standard WL algorithm, but also can work in high-dimensional spaces.