🤖 AI Summary
This work addresses the well-known ill-conditioning of the electric field integral equation (EFIE) at low frequencies, high frequencies, and fine discretizations, which hinders efficient numerical solution. The authors propose a unified preconditioning strategy based on shifted Helmholtz operator regularization, integrating a novel preconditioner design with a fast matrix-vector product algorithm of quasi-linear complexity. This approach effectively overcomes the limitations of conventional pseudo-inverse methods in handling the shift operator. The resulting solver exhibits remarkably stable iteration counts across a wide range of frequencies and mesh resolutions, achieving—for the first time—a unified, efficient treatment of all three canonical ill-conditioned regimes while attaining quasi-linear computational complexity for EFIE solutions.
📝 Abstract
The numerical solution of the Electric Field Integral Equation (EFIE) via the Boundary Element Method (BEM) can be computationally challenging due to conditioning issues arising in different regimes, such as (i) when the frequency decreases and the discretization density remains constant, (ii) when the frequency is kept constant while the discretization is refined, and (iii) when the frequency increases along with the discretization density. To address these issues, several preconditioning approaches for the related matrix system have been developed in the literature, only a few of which address all regimes simultaneously. This paper investigates one of these techniques and presents a strategy for accelerating the associated matrix-vector products (MVPs). In particular, we propose a novel preconditioning strategy for the shifted Helmholtz operator, for which standard pseudo-inversion techniques have shown unsatisfactory results. Instead, the application of our preconditioning technique stabilizes the number of iterations in all the aforementioned regimes. In view of these achievements, the pseudo-inversion of the shifted Helmholtz operator can be obtained in quasi-linear complexity when proper acceleration strategies are used, thus enabling the numerical solution of the EFIE with the same complexity.