AtomREM: Non-empirical seeker of the minimum energy escape paths on many-dimensional potential landscapes without coarse graining
arXiv:1907.13316 · doi:10.1016/j.cpc.2020.107260
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); Physica A, 528, 121481 (2019)]. This method is based on the Master equation for the distribution function of the atomic configuration which has a nature to seek the MEP up along the valley of the potential surface. This paper introduces AtomREM (Atomistic Rare Event Manager), which is an MPI parallelized solver program package for executing this method, which yields minimum energy reaction pathways in terms of the microscopic evolution of atomic positions. It is open-source and released under the GNU General Public License (GPL). AtomREM interfaces with the LAMMPS Molecular Dynamics Simulator as a library of versatile potential functions for application to various systems. Examples of the applications to molecular and solid systems are presented.
arXiv comment33 pages (single column), 11 figures
References in corpus (10)
- Escaping free-energy minima
- Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics
- Structure identification methods for atomistic simulations of crystalline materials
- Crystal structure prediction using the Minima Hopping method
- Enhancing entropy and enthalpy fluctuations to drive crystallization in atomistic simulations
- Mechanism of the fcc-hcp Phase Transformation in Solid Ar
- Efficient characterisation of large deviations using population dynamics
- A simple local expression for the prefactor in transition state theory
- Stochastic formalism for thermally driven distribution frontier: A nonempirical approach to the potential escape problem
- Non-empirical weighted Langevin mechanics for the potential escape problem: parallel algorithm and application to the Argon clusters