Meanwhile, in top-down force field development, developers aim to reproduce macroscopic properties including density, radial distribution function (RDF), evaporation enthalpy, free energy difference etc. To compute these properties, one needs to perform long MD simulations, the differentiation of which is nontrivial to do. Previous studies often differentiate through the entire MD trajectory, which is extremely expensive in both computational time and memory cost. Meanwhile, Thaler and Zavadlav showed that for ensemble averages, such end-to-end differentiation can be avoided by a trajectory reweighting scheme. In DMFF, we put the reweighting algorithm into a more general context of the MBAR 30 method, and introduce differentiable estimators for both averaged properties and free energies. While the differentiable evaluation of dynamic quantities remains a challenge, the reweighting MBAR estimator makes the fittings of thermodynamic properties relatively easy. We now briefly introduce the basic formulation of the reweighting MBAR estimator in DMFF.