Adaptive Nonoverlapping Preconditioners for the Helmholtz Equation

TL;DR

This paper introduces novel algebraic nonoverlapping preconditioners for the Helmholtz equation, improving scalability and convergence for high wavenumbers through a substructuring approach within NOSAS methods.

Contribution

It proposes two types of preconditioners addressing real and complex parts of the Helmholtz problem, enhancing robustness and efficiency in large-scale computations.

Findings

Robust convergence for high wavenumbers

Scalability demonstrated through numerical experiments

Effective reduction of computational cost

Abstract

The Helmholtz equation poses significant computational challenges due to its oscillatory solutions, particularly for large wavenumbers. Inspired by the Schur complement system for elliptic problems, this paper presents a novel substructuring approach to mitigate the potential ill-posedness of local Dirichlet problems for the Helmholtz equation. We propose two types of preconditioners within the framework of nonoverlapping spectral additive Schwarz (NOSAS) methods. The first type of preconditioner focuses on the real part of the Helmholtz problem, while the second type addresses both the real and imaginary components, providing a comprehensive strategy to enhance scalability and reduce computational cost. Our approach is purely algebraic, which allows for adaptability to various discretizations and heterogeneous Helmholtz coefficients while maintaining theoretical convergence for thresholds close to zero. Numerical experiments confirm the effectiveness of the proposed preconditioners, demonstrating robust convergence rates and scalability, even for large wavenumbers.