Langevin thermostat for robust configurational and kinetic sampling

Oded Farago

Physica A: Statistical Mechanics and its Applications, 2019, vol. 534, issue C

Abstract: We reformulate the algorithm of Grønbech-Jensen and Farago (GJF) for Langevin dynamics simulations at constant temperature. The GJF algorithm has become increasingly popular in molecular dynamics simulations because it provides robust (i.e., insensitive to variations in the time step) and accurate configurational sampling of the phase space with larger time steps than other Langevin thermostats. In the original derivation (Grønbech-Jensen and Farago, 2013), the algorithm was formulated as a velocity-Verlet type integrator with an in-site velocity variable. Here, we reformulate it as a leap frog scheme with a half-step velocity variable. In contrast to the original form, the reforumlated one also provides robust and accurate estimations of kinetic measures such as the average kinetic energy. We analytically prove that the newly presented algorithm gives the exact configurational and kinetic temperatures of a harmonic oscillator for any time step smaller than the Verlet stability limit, and use computer simulations to demonstrate the configurational and kinetic robustness of the algorithm in strongly non-linear systems. This property of the new formulation of the GJF thermostat makes it very attractive for implementation in computer simulations.

Keywords: Molecular dynamics; Langevin thermostat; Discrete-time integration; Verlet algorithm (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119312828

DOI: 10.1016/j.physa.2019.122210

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