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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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Published on: September 17, 2021

Efficiency in nonequilibrium molecular dynamics Monte Carlo simulations.

Brian K Radak¹, Benoît Roux²

¹Leadership Computing Facility, Argonne National Laboratory, Argonne, Illinois 60439-8643, USA.

The Journal of Chemical Physics

|October 27, 2016

Summary

Hybrid algorithms combining nonequilibrium molecular dynamics and Monte Carlo (neMD/MC) enhance simulation efficiency. A linear work protocol and optimized time parameters offer the best performance for complex systems.

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Area of Science:

Computational Chemistry
Biophysics
Statistical Mechanics

Background:

Hybrid algorithms like nonequilibrium molecular dynamics and Monte Carlo (neMD/MC) improve computational simulation efficiency.
These methods are crucial for complex systems and challenging applications like constant-pH simulations with explicit solvent.

Purpose of the Study:

To evaluate the efficiency of various neMD/MC algorithms and protocols.
To provide a theoretical framework for optimizing neMD/MC performance using linear response theory.

Main Methods:

Theoretical evaluation using linear response theory.
Validation against constant-pH molecular dynamics simulations.
Assessment of a wide range of neMD/MC protocols.

Main Results:

Linear response theory accurately predicts neMD/MC performance.
A linear work protocol was identified as the most efficient neMD/MC method.
A criterion for optimizing protocol time parameters was developed and demonstrated.

Conclusions:

The linear work protocol is optimal for neMD/MC simulations.
Optimized time parameters significantly enhance simulation efficiency.
An adaptive algorithm can improve neMD/MC performance dynamically.