Non-empirical weighted Langevin mechanics for the potential escape problem: Parallel algorithm and application to the Argon clusters - Nagornov, Yuri S.; Akashi, Ryosuke (Physica A, 2019)
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 (Akashi and Nagornov, 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 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. •A novel algorithm has been designed and investigated for the reaction path seeking.•The method based on the weighted Langevin mechanics with excellent parallel implementation.•The stochastic walker algorithm utilized the biasing potential to reach a saddle point.•The applications to argon clusters with 7–38 atoms are demonstrated.