An Always-Accepting Algorithm for Transition Path Sampling

TL;DR

This paper introduces an always-accepting transition path sampling algorithm that improves efficiency by eliminating rejection steps, enabling better sampling of rare events like hydrate formation under challenging conditions.

Contribution

The paper presents a novel one-way shooting algorithm that always accepts proposed trajectories and corrects for bias, enhancing sampling efficiency in stochastic systems.

Findings

Algorithm successfully samples transition paths without rejection.

Enhanced sampling efficiency enables studying rare events.

Application to hydrate formation demonstrates practical advantages.

Abstract

We present a one-way shooting algorithm for transition path sampling that accepts every proposed trajectory, yet samples the correct transition path ensemble for systems with overdamped stochastic dynamics. The method is based on two key elements: a procedure to propose trajectories that are always reactive, and a reweighting scheme that corrects for the bias introduced by always accepting the proposed paths. This approach significantly improves the efficiency of transition path sampling by eliminating the cost associated with generating trajectories that are then rejected. We demonstrate the performances of the algorithm by investigating the formation of CO$_2$ clathrate hydrates along different reaction mechanisms, showing that the increased efficiency allows proper sampling of the formation of crystalline hydrates at temperatures and pressures that are difficult to access with conventional schemes.