Modulating Coarse-Grained\nDynamics by Perturbing Free\nEnergy Landscapes

We introduce an approach to describe the long-time dynamics\nof\nmultiatomic molecules by modulating the free energy landscape (FEL)\nto capture dominant features of the energy-barrier crossing dynamics\nof the all-atom (AA) system. Notably, we establish that the self-diffusion\ncoefficient of coarse-grained (CG) systems can be accurately delineated\nby enhancing conservative force fields with high-frequency perturbations.\nUsing theoretical arguments, we show that these perturbations do not\nalter the lower-order distribution functions, thereby preserving the\nstructure of the AA system after coarse-graining. We demonstrate the\nutility of this approach using molecular dynamics simulations of simple\nmolecules in bulk with distinct dynamical characteristics with and\nwithout time scale separations as well as for inhomogeneous systems\nwhere a fluid is confined in a slit-like nanochannel. Additionally,\nwe also apply our approach to more powerful many-body potentials optimized\nby using machine learning (ML).