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In this work we extend the shifted Laplacian approach to the elastic Helmholtz equation. The shifted Laplacian multigrid method is a common preconditioning approach for the discretized acoustic Helmholtz equation. In some cases, like…

Computational Engineering, Finance, and Science · Computer Science 2023-11-21 Eran Treister , Rachel Yovel

Shifted Laplacian multigrid preconditioner has become a tool du jour for solving highly indefinite Helmholtz equations. The idea is to add a complex damping to the original Helmholtz operator and then apply a multigrid processing to the…

Numerical Analysis · Mathematics 2013-12-11 Ira Livshits

The solution of saddle-point problems, such as the Stokes equations, is a challenging task, especially in large-scale problems. Multigrid methods are one of the most efficient solvers for such systems of equations and can achieve…

Numerical Analysis · Mathematics 2022-04-13 S. Saberi , G. Meschke , A. Vogel

We present a convergent and scalable multigrid solver for high-frequency Helmholtz equations. Standard multigrid methods do not converge for high-frequency Helmholtz problems, and a common cure is adding a complex shift and using the…

Numerical Analysis · Mathematics 2026-04-22 Rachel Yovel , Eran Treister

We propose and analyze a Vanka-type multigrid solver for solving a sequence of complex-shifted Laplacian systems arising in diagonalization-based parallel-in-time algorithms for evolutionary equations. Under suitable assumption, local…

Numerical Analysis · Mathematics 2022-03-22 Yunhui He , Jun Liu

We present an efficient matrix-free geometric multigrid method for the elastic Helmholtz equation, and a suitable discretization. Many discretization methods had been considered in the literature for the Helmholtz equations, as well as many…

Numerical Analysis · Mathematics 2023-12-05 Rachel Yovel , Eran Treister

We present a deep learning-based iterative approach to solve the discrete heterogeneous Helmholtz equation for high wavenumbers. Combining classical iterative multigrid solvers and convolutional neural networks (CNNs) via preconditioning,…

Machine Learning · Computer Science 2024-06-07 Bar Lerer , Ido Ben-Yair , Eran Treister

In this paper, we present a data-driven approach to iteratively solve the discrete heterogeneous Helmholtz equation at high wavenumbers. In our approach, we combine classical iterative solvers with convolutional neural networks (CNNs) to…

Numerical Analysis · Mathematics 2022-03-22 Yael Azulay , Eran Treister

Getting standard multigrid to work efficiently for the high-frequency Helmholtz equation has been an open problem in applied mathematics for years. Much effort has been dedicated to finding solution methods which can use multigrid…

Numerical Analysis · Mathematics 2023-08-28 Vandana Dwarka , Cornelis Vuik

We present a novel block-preconditioner for the elastic Helmholtz equation, based on a reduction to acoustic Helmholtz equations. Both versions of the Helmholtz equations are challenging numerically. The elastic Helmholtz equation is…

Numerical Analysis · Mathematics 2025-12-09 Rachel Yovel , Eran Treister

The magnetohydrodynamics (MHD) equations model a wide range of plasma physics applications and are characterized by a nonlinear system of partial differential equations that strongly couples a charged fluid with the evolution of…

Numerical Analysis · Mathematics 2020-06-30 J. H. Adler , T. Benson , E. C. Cyr , P. E. Farrell , S. MacLachlan , R. Tuminaro

Multigrid preconditioners and solvers for the indefinite Helmholtz equation suffer from non-stability of the stationary smoothers due to the indefinite spectrum of the operator. In this paper we explore GMRES as a replacement for the…

Numerical Analysis · Computer Science 2015-03-17 Bram Reps , Wim Vanroose , Hisham bin Zubair

Due to the indefiniteness and poor spectral properties, the discretized linear algebraic system of the vector Laplacian by mixed finite element methods is hard to solve. A block diagonal preconditioner has been developed and shown to be an…

Numerical Analysis · Mathematics 2016-01-19 Long Chen , Yongke Wu , Lin Zhong , Jie Zhou

In this paper we solve the Helmholtz equation with multigrid preconditioned Krylov subspace methods. The class of Shifted Laplacian preconditioners are known to significantly speed-up Krylov convergence. However, these preconditioners have…

Analysis of PDEs · Mathematics 2013-09-06 Siegfried Cools , Wim Vanroose

We propose a block-structured multigrid relaxation scheme for solving the Stokes-Darcy Brinkman equations discretized by the marker and cell scheme. An element-based additive Vanka smoother is used to solve the corresponding shifted…

Numerical Analysis · Mathematics 2022-04-05 Yunhui He

In this paper we construct and analyse a level-dependent coarsegrid correction scheme for indefinite Helmholtz problems. This adapted multigrid method is capable of solving the Helmholtz equation on the finest grid using a series of…

Numerical Analysis · Mathematics 2013-09-09 Siegfried Cools , Bram Reps , Wim Vanroose

Numerical simulation of incompressible fluid flows has been an active topic of research in Scientific Computing for many years, with many contributions to both discretizations and linear and nonlinear solvers. In this work, we propose an…

Numerical Analysis · Mathematics 2025-12-16 Amin Rafiei , Scott MacLachlan

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.…

Computational Engineering, Finance, and Science · Computer Science 2021-04-06 Daniel Drzisga , Tobias Köppl , Barbara Wohlmuth

A V-cycle multigrid method for the Hellan-Herrmann-Johnson (HHJ) discretization of the Kirchhoff plate bending problems is developed in this paper. It is shown that the contraction number of the V-cycle multigrid HHJ mixed method is bounded…

Numerical Analysis · Mathematics 2017-12-27 Long Chen , Jun Hu , Xuehai Huang

Multigrid methods are popular solution algorithms for many discretized PDEs, either as standalone iterative solvers or as preconditioners, due to their high efficiency. However, the choice and optimization of multigrid components such as…

Numerical Analysis · Mathematics 2020-01-22 Patrick E. Farrell , Yunhui He , Scott P. MacLachlan
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