Benchmarking thermostat algorithms in molecular dynamics simulations of a binary Lennard-Jones glass-former model

Fuente: arXiv
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Main Authors: Shiraishi, Kumpei, Minamitani, Emi, Kim, Kang
Format: Preprint
Published: 2025
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author Shiraishi, Kumpei
Minamitani, Emi
Kim, Kang
author_facet Shiraishi, Kumpei
Minamitani, Emi
Kim, Kang
contents A systematic comparison was carried out to assess the influence of representative thermostat methods in constant-temperature molecular dynamics simulations. The thermostat schemes considered include the Nosé--Hoover thermostat and its chain generalisation, the Bussi velocity rescaling method, and several implementations of the Langevin dynamics. Using a binary Lennard-Jones liquid as a model glass former, we investigated how the sampling of physical observables, such as particle velocities and potential energy, responds to changes in time step across these thermostats. While the Nosé--Hoover chain and Bussi thermostats provide reliable temperature control, a pronounced time-step dependence was observed in the potential energy. Amongst the Langevin methods, the Grønbech-Jensen--Farago scheme provided the most consistent sampling of both temperature and potential energy. Nonetheless, Langevin dynamics typically incurs approximately twice the computational cost due to the overhead of random number generation, and exhibits a systematic decrease in diffusion coefficients with increasing friction. This study presents a broad comparison of thermostat methods using a binary Lennard-Jones glass-former model, offering practical guidance for the choice of thermostats in classical molecular dynamics simulations. These findings provide useful insights for diverse applications, including glass transition, phase separation, and nucleation.
format Preprint
id arxiv_https___arxiv_org_abs_2509_12837
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Benchmarking thermostat algorithms in molecular dynamics simulations of a binary Lennard-Jones glass-former model
Shiraishi, Kumpei
Minamitani, Emi
Kim, Kang
Computational Physics
Soft Condensed Matter
A systematic comparison was carried out to assess the influence of representative thermostat methods in constant-temperature molecular dynamics simulations. The thermostat schemes considered include the Nosé--Hoover thermostat and its chain generalisation, the Bussi velocity rescaling method, and several implementations of the Langevin dynamics. Using a binary Lennard-Jones liquid as a model glass former, we investigated how the sampling of physical observables, such as particle velocities and potential energy, responds to changes in time step across these thermostats. While the Nosé--Hoover chain and Bussi thermostats provide reliable temperature control, a pronounced time-step dependence was observed in the potential energy. Amongst the Langevin methods, the Grønbech-Jensen--Farago scheme provided the most consistent sampling of both temperature and potential energy. Nonetheless, Langevin dynamics typically incurs approximately twice the computational cost due to the overhead of random number generation, and exhibits a systematic decrease in diffusion coefficients with increasing friction. This study presents a broad comparison of thermostat methods using a binary Lennard-Jones glass-former model, offering practical guidance for the choice of thermostats in classical molecular dynamics simulations. These findings provide useful insights for diverse applications, including glass transition, phase separation, and nucleation.
title Benchmarking thermostat algorithms in molecular dynamics simulations of a binary Lennard-Jones glass-former model
topic Computational Physics
Soft Condensed Matter
url https://arxiv.org/abs/2509.12837