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

Julien Guénolé, Wolfram G. Nöhring, Aviral Vaid, Frédéric Houllé, Zhuocheng Xie, Aruna Prakash, Erik Bitzek

2020Computational Materials Science224 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Energy minimizationMinificationRelaxation (psychology)Inertial frame of referenceComputer scienceMolecular dynamicsEnergy (signal processing)Nuclear engineeringStatistical physicsComputational scienceMaterials sciencePhysicsComputational chemistryChemistryEngineeringClassical mechanicsPsychologyQuantum mechanicsSocial psychologyProgramming languageFusion materials and technologiesGas Dynamics and Kinetic TheoryLaser-Plasma Interactions and Diagnostics
Assessment and optimization of the fast inertial relaxation engine (fire) for energy minimization in atomistic simulations and its implementation in lammps | Litcius