Physics > Computational Physics
[Submitted on 6 Aug 2019
(v1)
, last revised 30 Jan 2020 (this version, v4)]
Title: Assessment and optimization of the fast inertial relaxation engine (FIRE) for energy minimization in atomistic simulations and its implementation in LAMMPS
Title: 基于原子模拟中的能量最小化，对快速惯性松弛引擎（FIRE）的评估与优化及其在LAMMPS中的实现
Abstract: 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.
Submission history
From: Julien Guénolé PhD [view email][v1] Tue, 6 Aug 2019 09:27:29 UTC (6,293 KB)
[v2] Thu, 19 Sep 2019 15:22:29 UTC (6,246 KB)
[v3] Tue, 5 Nov 2019 13:12:44 UTC (6,245 KB)
[v4] Thu, 30 Jan 2020 12:50:05 UTC (6,248 KB)
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