Collective mode Brownian dynamics: A method for fast relaxation of statistical ensembles
Name
094104_1_online.pdf
Description
Published version
Size
4.8 MB
Format
Adobe PDF
Checksum (MD5)
7f3ddadcd7a1aa02fcc5c0b544c9b92c
Author(s)
Silmore, Kevin S
Swan, James W
Date Issued
March 2, 2020
Journal
The Journal of Chemical Physics
Publisher
AIP Publishing
Citation
Kevin S. Silmore, James W. Swan; Collective mode Brownian dynamics: A method for fast relaxation of statistical ensembles. J. Chem. Phys. 7 March 2020; 152 (9): 094104.
Version
Final published version
Abstract
Sampling equilibrium configurations of correlated systems of particles with long relaxation times (e.g., polymeric solutions) using conventional molecular dynamics and Monte Carlo methods can be challenging. This is especially true for systems with complicated, extended bond network topologies and other interactions that make the use and design of specialized relaxation protocols infeasible. We introduce a method based on Brownian dynamics simulations that can reduce the computational time it takes to reach equilibrium and draw decorrelated samples. Importantly, the method is completely agnostic to the particle configuration and the specifics of interparticle forces. In particular, we develop a mobility matrix that excites non-local, collective motion of N particles and can be computed efficiently in O(N) time. Particle motion in this scheme is computed by integrating the overdamped Langevin equation with an Euler–Maruyama scheme, in which Brownian displacements are drawn efficiently using a low-rank representation of the mobility matrix in position and wave space. We demonstrate the efficacy of the method with various examples from the realm of soft condensed matter and release a massively parallel implementation of the code as a plugin for the open-source package HOOMD-blue [J. A. Anderson et al., J. Comput. Phys. 227, 5342 (2008) and J. Glaser et al., Comput. Phys. Commun. 192, 97 (2015)] which runs on graphics processing units.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1063/1.5129648
