Assessment and optimization of the fast inertial relaxation engine (FIRE) for energy minimization in atomistic simulations and its implementation in LAMMPS

J Guenole and WG Nohring and A Vaid and F Houlle and ZC Xie and A Prakash and E Bitzek, COMPUTATIONAL MATERIALS SCIENCE, 175, 109584 (2020).

DOI: 10.1016/j.commatsci.2020.109584

In atomistic simulations, pseudo-dynamical 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 atomistic simulation code LAMMPS is presented. It is shown that the correct choice of time integration scheme and minimization parameters is crucial for the performance of FIRE.

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