# Non-empirical weighted Langevin mechanics for the potential escape problem: parallel algorithm and application to the Argon clusters

## TL;DR

This paper introduces a parallelized, non-empirical stochastic algorithm for accurately finding minimum-energy escape paths in potential surfaces, demonstrated on Lennard-Jones argon clusters, enabling detailed rare reaction simulations.

## Contribution

It develops an MPI-parallelized implementation of a non-empirical Langevin-based algorithm for MEP search, with improved efficiency and automatic initialization, applied to argon clusters.

## Key findings

- Successful tracking of reaction paths in argon clusters with 7-38 atoms
- Reduced number of walkers needed for accurate MEP detection
- Demonstrated potential for non-empirical simulation of rare reactions

## Abstract

Recently a non-empirical stochastic walker algorithm has been developed to search for the minimum-energy escape paths (MEP) from the minima of the potential surface [J. Phys. Soc. Jpn. 87, 063801 (2018)]. This algorithm is novel in that it tracks the MEP monotonically and does not use the whole Hessian matrix but only gradient and Laplacian of the potential. In this work, we implement an MPI-parallelized version of this algorithm in a simple way. We also explore efficient ways to reduce the number of walkers required for the accurate tracking of the MEP and generate initial positions automatically. We apply the whole scheme to the Lennard-Jones argon cluster with 7-38 atoms to demonstrate the successful tracking of the reaction paths. This achievement paves the path to non-empirical simulation of rare reactions without coarse-graining or artificial potential.