Assessment and optimization of the fast inertial relaxation engine (FIRE) for energy minimization in atomistic simulations and its implementation in LAMMPS
In atomistic simulations, pseudo-dynamics relaxation schemes often exhibit better performance and accuracy in finding local minima than line-search-based descent algorithms like steepest descent or conjugate gradient. Here, an improved version of the fast inertial relaxation engine (FIRE) and its implementation within the open-source code LAMMPS is presented. It is shown that the correct choice of time integration scheme and minimization parameters is crucial for performance.
@article{arxiv.1908.02038,
title = {Assessment and optimization of the fast inertial relaxation engine (FIRE) for energy minimization in atomistic simulations and its implementation in LAMMPS},
author = {Julien Guénolé and Wolfram G. Nöhring and Aviral Vaid and Frédéric Houllé and Zhuocheng Xie and Aruna Prakash and Erik Bitzek},
journal= {arXiv preprint arXiv:1908.02038},
year = {2020}
}