Harmonic surface mapping algorithm for fast electrostatic sums

TL;DR

The paper introduces a harmonic surface mapping algorithm (HSMA) that efficiently computes electrostatic sums involving infinite image charges, achieving linear scaling and high accuracy for large-scale systems.

Contribution

A novel harmonic surface mapping algorithm that simplifies electrostatic calculations with infinite image charges, enabling fast and accurate results independent of source number.

Findings

Achieves linear scaling with system size.

Accurately computes Madelung constants and electrostatic energies.

Demonstrates high speed and precision in large-scale simulations.

Abstract

We propose a harmonic surface mapping algorithm (HSMA) for electrostatic pairwise sums of an infinite number of image charges. The images are induced by point sources within a box due to a specific boundary condition which can be non-periodic. The HSMA first introduces an auxiliary surface such that the contribution of images outside the surface can be approximated by the least-squares method using spherical harmonics as basis functions. The so-called harmonic surface mapping is the procedure to transform the approximate solution into a surface charge and a surface dipole over the auxiliary surface, which becomes point images by using numerical integration. The mapping procedure is independent of the number of the sources and is considered to have a low complexity. The electrostatic interactions are then among those charges within the surface and at the integration points, which are all the form of Coulomb potential and can be accelerated straightforwardly by the fast multipole method to achieve linear scaling. Numerical calculations of the Madelung constant of a crystalline lattice, electrostatic energy of ions in a metallic cavity, and the time performance for large-scale systems show that the HSMA is accurate and fast, and thus is attractive for many applications.