The G-JF Thermostat for Accurate Configurational Sampling in Soft-Matter Simulations

Abstract

We implement the statistically sound G-JF thermostat for Langevin Dynamics simulations into the ESPREesSo molecular package for large-scale simulations of soft matter systems. The implemented integration method is tested against the integrator currently used by the molecular package in simulations of a fluid bilayer membrane. While the latter exhibits deviations in the sampling statistics that increase with the integration time step dt, the former reproduces near-correct configurational statistics for all dt within the stability range of the simulations. We conclude that, with very modest revisions to existing codes, one can significantly improve the performance of statistical sampling using Langevin thermostats.

Six pages, seven figures. Accepted for publication in Israel Journal of Chemistry

References in corpus (3)

• A simple and effective Verlet-type algorithm for simulating Langevin dynamics
• Application of the G-JF Discrete-Time Thermostat for Fast and Accurate Molecular Simulations
• Constant pressure and temperature discrete-time Langevin molecular dynamics

Cited by in corpus (10)

• Langevin thermostat for robust configurational and kinetic sampling
• Complete Set of Stochastic Verlet-Type Thermostats for Correct Langevin Simulations
• Accurate Configurational and Kinetic Statistics in Discrete-Time Langevin Systems
• Comparison of Modern Langevin Integrators for Simulations of Coarse-Grained Polymer Melts
• Algorithms for Brownian dynamics across discontinuities
• A Langevin dynamics approach for multi-layer mass transfer problems
• The Challenge of Stochastic Størmer-Verlet Thermostats Generating Correct Statistics
• Defining velocities for accurate kinetic statistics in the GJF thermostat
• Bringing discrete-time Langevin splitting methods into agreement with thermodynamics
• The Effects of Intrinsic Dynamical Ghost Modes in Discrete-Time Langevin Simulations