An O(N^2) Approximation for Hydrodynamic Interactions in Brownian Dynamics Simulations

TL;DR

This paper introduces an O(N^2) algorithm for approximating hydrodynamic interactions in Brownian Dynamics, significantly reducing computational complexity while maintaining high accuracy, enabling large-scale simulations.

Contribution

The authors develop a truncated expansion method that approximates hydrodynamic interactions with 95% accuracy and reduces runtime from O(N^3) to O(N^2), applicable to arbitrary configurations.

Findings

Achieves about 95% of hydrodynamic correlations

Reduces runtime scaling to O(N^2)

Applicable to arbitrary particle configurations

Abstract

In the Ermak-McCammon algorithm for Brownian Dynamics, the hydrodynamic interactions (HI) between N spherical particles are described by a 3N x 3N diffusion tensor. This tensor has to be factorized at each timestep with a runtime of O(N^3), making the calculation of the correlated random displacements the bottleneck for many-particle simulations. Here we present a faster algorithm for this step, which is based on a truncated expansion of the hydrodynamic multi-particle correlations as two-body contributions. The comparison to the exact algorithm and to the Chebyshev approximation of Fixman verifies that for bead-spring polymers this approximation yields about 95% of the hydrodynamic correlations at an improved runtime scaling of O(N^2) and a reduced memory footprint. The approximation is independent of the actual form of the hydrodynamic tensor and can be applied to arbitrary particle configurations. This now allows to include HI into large many-particle Brownian dynamics simulations, where until now the runtime scaling of the correlated random motion was prohibitive.