DMFF: An Open-Source Automatic Differentiable Platform for Molecular Force Field Development and Molecular Dynamics Simulation

In
the simulation of molecular systems, the underlying force field
(FF) model plays an extremely important role in determining the reliability
of the simulation. However, the quality of the state-of-the-art molecular
force fields is still unsatisfactory in many cases, and the FF parameterization
process largely relies on human experience, which is not scalable.
To address this issue, we introduce DMFF, an open-source molecular
FF development platform based on an automatic differentiation technique.
DMFF serves as a powerful tool for both top-down and bottom-up FF
development. Using DMFF, both energies/forces and thermodynamic quantities
such as ensemble averages and free energies can be evaluated in a
differentiable way, realizing an automatic, yet highly flexible FF
optimization workflow. DMFF also eases the evaluation of forces and
virial tensors for complicated advanced FFs, helping the fast validation
of new models in molecular dynamics simulation. DMFF has been released
as an open-source package under the LGPL-3.0 license and is available
at https://github.com/deepmodeling/DMFF.