Generalized path reweighting and history-dependent free energies

Transition interface sampling (TIS) and replica exchange TIS (RETIS) are powerful methods for computing rates of rare events inaccessible to straightforward molecular dynamics simulations. Path reweighting extends their output, enabling the evaluation of diverse thermodynamic and kinetic quantities, including reaction prediction metrics, activation barriers, committor functions, and free energies. The recently developed ∞RETIS algorithm boosts parallel efficiency through asynchronous replica exchanges in the infinite-swap limit, thereby eliminating the wall-time bottlenecks of conventional RETIS. This approach introduces fractional samples and biased sampling distributions, requiring a generalized path reweighting framework, for which we derive expressions demonstrating how exact dynamic and thermodynamic variables can be computed. We then focus on a special class of free energy surfaces defined by history-dependent conditions, whose values are influenced by kinetic factors such as particle mass and friction, unlike standard unconditional free energy surfaces. Even with suboptimal reaction coordinates, these conditional free energies can reveal kinetically relevant barriers that may be misrepresented by standard unconditional free energies, thereby providing a rigorous and versatile tool for characterizing complex molecular transitions.