Some Random Batch Particle Methods for the Poisson-Nernst-Planck and Poisson-Boltzmann Equations

Some Random Batch Particle Methods for the Poisson-Nernst-Planck and Poisson-Boltzmann Equations

Year:    2022

Author:    Lei Li, Jian-Guo Liu, Yijia Tang

Communications in Computational Physics, Vol. 32 (2022), Iss. 1 : pp. 41–82

Abstract

We consider in this paper random batch interacting particle methods for solving the Poisson-Nernst-Planck (PNP) equations, and thus the Poisson-Boltzmann (PB) equation as the equilibrium, in the external unbounded domain. To justify the simulation in a truncated domain, an error estimate of the truncation is proved in the symmetric cases for the PB equation. Then, the random batch interacting particle methods are introduced which are $\mathcal{O}(N)$ per time step. The particle methods can not only be considered as a numerical method for solving the PNP and PB equations, but also can be used as a direct simulation approach for the dynamics of the charged particles in solution. The particle methods are preferable due to their simplicity and adaptivity to complicated geometry, and may be interesting in describing the dynamics of the physical process. Moreover, it is feasible to incorporate more physical effects and interactions in the particle methods and to describe phenomena beyond the scope of the mean-field equations.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/cicp.OA-2021-0159

Communications in Computational Physics, Vol. 32 (2022), Iss. 1 : pp. 41–82

Published online:    2022-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    42

Keywords:    Interacting particle systems Coulomb interaction reflecting stochastic differential equation charge reversal phenomenon singular-regular decomposition.

Author Details

Lei Li

Jian-Guo Liu

Yijia Tang