QR-Recursive Compression of Volume Integral Equations for Electromagnetic Scattering by Large Metasurfaces

TL;DR

This paper introduces a QR decomposition-based compression method combined with volume integral equations to efficiently simulate electromagnetic scattering from large, complex metasurfaces with thousands of scatterers, enabling faster and more accurate computations.

Contribution

A novel QR decomposition-based compression scheme tailored for volume integral equations, improving the efficiency and accuracy of electromagnetic scattering simulations for large metasurfaces.

Findings

Effective modeling of metasurfaces with thousands of particles

Significant reduction in computational time

High accuracy in electromagnetic scattering predictions

Abstract

In this paper, a novel QR decomposition-based compression scheme is combined with a volume integral equations method for the fast and efficient numerical computation of the scattering of electromagnetic fields from large scale metasurfaces, via an iterative approach. The underlying problem is of a multiscale nature. Indeed, these metasurfaces are made of a large collection of interacting sub-wavelength scatterers, thus making the numerical computation of the solution very challenging. More specifically, the paper proposes a tailored version of a QR decomposition-based compression for a volume integral equation, together with a proper preconditioner that exploits the geometrical structure of the array, in order to achieve a fast and accurate iterative solver, in view of realistic applications. Numerical examples prove the effectiveness of the method in efficiently modeling metasurfaces made by thousands of particles.