Generalized Path Reweighting and History-Dependent Free Energies
Titus S. van Erp, Daniel T. Zhang, Elias Wils, Sina Safaei, and An Ghysels

TL;DR
This paper introduces a generalized path reweighting framework for advanced sampling methods like TIS and RETIS, enabling accurate computation of thermodynamic and kinetic quantities, including history-dependent free energies, even with suboptimal reaction coordinates.
Contribution
It develops a generalized path reweighting method for fractional samples and biased distributions, and introduces history-dependent free energies that capture kinetic effects.
Findings
Infinity-RETIS improves parallel efficiency via asynchronous exchanges.
The framework accurately computes dynamic and thermodynamic variables.
History-dependent free energies reveal kinetically relevant barriers.
Abstract
Transition interface sampling (TIS) and replica exchange TIS (RETIS) are powerful methods for computing rates of rare events inaccessible to straightforward molecular dynamics (MD) 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 Infinity-RETIS algorithm boosts parallel efficiency through asynchronous replica exchanges in the infinite-swap limit, 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…
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