Multi-resolution Localized Orthogonal Decomposition for Helmholtz problems

TL;DR

This paper presents a multi-resolution Localized Orthogonal Decomposition method for Helmholtz problems that combines wavelet concepts to improve stability and efficiency in complex acoustic scattering simulations.

Contribution

It introduces a novel multi-resolution LOD approach merging wavelet techniques, applicable to complex Helmholtz problems, with proven stability and error bounds.

Findings

Hierarchical bases block-diagonalize the Helmholtz operator

Localization strategy preserves sparsity and improves stability

Numerical experiments confirm theoretical predictions and applicability to heterogeneous media

Abstract

We introduce a novel multi-resolution Localized Orthogonal Decomposition (LOD) for time-harmonic acoustic scattering problems that can be modeled by the Helmholtz equation. The method merges the concepts of LOD and operator-adapted wavelets (gamblets) and proves its applicability for a class of complex-valued, non-hermitian and indefinite problems. It computes hierarchical bases that block-diagonalize the Helmholtz operator and thereby decouples the discretization scales. Sparsity is preserved by a novel localization strategy that improves stability properties even in the elliptic case. We present a rigorous stability and a-priori error analysis of the proposed method for homogeneous media. In addition, we investigate the fast solvability of the blocks by a standard iterative method. A sequence of numerical experiments illustrates the sharpness of the theoretical findings and demonstrates the applicability to scattering problems in heterogeneous media.