Fast and accurate evaluation of Biot-Savart integrals over spatial curves in periodic domains

TL;DR

This paper introduces a fast, accurate method for evaluating Biot-Savart integrals over spatial curves in periodic domains, leveraging Ewald summation and FFT techniques to improve efficiency in vortex filament simulations.

Contribution

It adapts Ewald summation methods from molecular dynamics to vortex filament simulations, enabling $O(N \, \log N)$ complexity and improved accuracy for large-scale fluid flow modeling.

Findings

Achieves $O(N \log N)$ computational complexity.

Provides analytical accuracy estimates for the method.

Demonstrates conservation properties and accuracy through numerical experiments.

Abstract

The Biot-Savart law is relevant in physical contexts including electromagnetism and fluid dynamics. In the latter case, when the rotation of a fluid is confined to a set of very thin vortex filaments, this law describes the velocity field induced by the spatial arrangement of these objects. The Biot-Savart law is at the core of vortex methods used in the simulation of classical and quantum fluid flows. Naive methods are inefficient when dealing with large numbers of vortex elements, which makes them inadequate for simulating turbulent vortex flows. Here we exploit a direct analogy between the Biot-Savart law and electrostatics to adapt Ewald summation methods, routinely used in molecular dynamics simulations, to vortex filament simulations in three-dimensional periodic domains. In this context, the basic idea is to split the induced velocity onto (i) a coarse-grained velocity generated by a Gaussian-filtered vorticity field, and (ii) a short-range correction accounting for near-singular behaviour near the vortices. The former component can be accurately and efficiently evaluated using the nonuniform fast Fourier transform algorithm. Analytical accuracy estimates are provided as a function of the parameters entering the method. We also discuss how to properly account for the finite vortex core size in kinetic energy estimations. Using numerical experiments, we verify the accuracy and the conservation properties of the proposed approach. Moreover, we demonstrate the $O(N \log N)$ complexity of the method over a wide range of problem sizes $N$, considerably better than the $O(N^2)$ cost of a naive approach.