Assessing numerical methods for molecular and particle simulation
Xiaocheng Shang, Martin Kr\"oger, Benedict Leimkuhler

TL;DR
This paper evaluates various numerical methods for molecular dynamics, highlighting the advantages of the newly proposed PAdL method in terms of efficiency, stability, and accuracy in soft matter simulations.
Contribution
It introduces the PAdL method, a new momentum-conserving algorithm that improves efficiency and accuracy in nonequilibrium soft matter simulations.
Findings
PAdL conserves momentum and matches relaxation rates.
PAdL outperforms DPD and Langevin in shear viscosity accuracy.
PAdL offers significant computational efficiency improvements.
Abstract
We discuss the design of state-of-the-art numerical methods for molecular dynamics, focusing on the demands of soft matter simulation, where the purposes include sampling and dynamics calculations both in and out of equilibrium. We discuss the characteristics of different algorithms, including their essential conservation properties, the convergence of averages, and the accuracy of numerical discretizations. Formulations of the equations of motion which are suited to both equilibrium and nonequilibrium simulation include Langevin dynamics, dissipative particle dynamics (DPD), and the more recently proposed "pairwise adaptive Langevin" (PAdL) method, which, like DPD but unlike Langevin dynamics, conserves momentum and better matches the relaxation rate of orientational degrees of freedom. PAdL is easy to code and suitable for a variety of problems in nonequilibrium soft matter modeling,…
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