Semi matrix-free twogrid shifted Laplacian preconditioner for the Helmholtz equation with near optimal shifts

TL;DR

This paper develops a data-driven method to select near optimal complex shifts for a multigrid preconditioner to efficiently solve the Helmholtz equation, using a semi matrix-free two-grid approach and nonlinear regression.

Contribution

It introduces a map for near optimal shift parameters based on wavenumber and mesh size, improving Helmholtz solver efficiency.

Findings

The method reduces iteration counts in FGMRES for Helmholtz problems.

The shift map adapts to heterogeneous wavenumbers in 2D and 3D.

The semi matrix-free two-grid preconditioner performs well on benchmark problems.

Abstract

Due to its significance in terms of wave phenomena a considerable effort has been put into the design of preconditioners for the Helmholtz equation. One option to derive a preconditioner is to apply a multigrid method on a shifted operator. In such an approach, the wavenumber is shifted by some imaginary value. This step is motivated by the observation that the shifted problem can be more efficiently handled by iterative solvers when compared to the standard Helmholtz equation. However, up to now, it is not obvious what the best strategy for the choice of the shift parameter is. It is well known that a good shift parameter depends sensitively on the wavenumber and the discretization parameters such as the order and the mesh size. Therefore, we study the choice of a near optimal complex shift such that an FGMRES solver converges with fewer iterations. Our goal is to provide a map which returns the near optimal shift for the preconditioner depending on the wavenumber and the mesh size. In order to compute this map, a data driven approach is considered: We first generate many samples, and in a second step, we perform a nonlinear regression on this data. With this representative map, the near optimal shift can be obtained by a simple evaluation. Our preconditioner is based on a twogrid V-cycle applied to the shifted problem, allowing us to implement a semi matrix-free method. The performance of our preconditioned FGMRES solver is illustrated by several benchmark problems with heterogeneous wavenumbers in two and three space dimensions.