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This paper introduces a robust preconditioner for general sparse symmetric matrices, that is based on low-rank approximations of the Schur complement in a Domain Decomposition (DD) framework. In this "Schur Low Rank" (SLR) preconditioning…

Numerical Analysis · Computer Science 2015-05-19 Ruipeng Li , Yuanzhe Xi , Yousef Saad

The importance of Schur complement based preconditioners are well-established for classical saddle point problems in $\mathbb{R}^N \times \mathbb{R}^M$. In this paper we extend these results to multiple saddle point problems in Hilbert…

Numerical Analysis · Mathematics 2020-12-25 Jarle Sogn , Walter Zulehner

High-order implicit shock tracking (fitting) is a class of high-order numerical methods that use numerical optimization to simultaneously compute a high-order approximation to a conservation law solution and align elements of the…

Numerical Analysis · Mathematics 2024-06-28 Jakob Vandergrift , Matthew J. Zahr

Multistep matrix splitting iterations serve as preconditioning for Krylov subspace methods for solving singular linear systems. The preconditioner is applied to the generalized minimal residual (GMRES) method and the flexible GMRES (FGMRES)…

Numerical Analysis · Mathematics 2021-11-09 Keiichi Morikuni

For several classes of mathematical models that yield linear systems, the splitting of the matrix into its Hermitian and skew Hermitian parts is naturally related to properties of the underlying model. This is particularly so for…

Numerical Analysis · Mathematics 2023-01-02 Malak Diab , Andreas Frommer , Karsten Kahl

We develop a novel iterative solution method for the incompressible Navier-Stokes equations with boundary conditions coupled with reduced models. The iterative algorithm is designed based on the variational multiscale formulation and the…

Numerical Analysis · Mathematics 2020-06-24 Ju Liu , Weiguang Yang , Melody Dong , Alison L. Marsden

We introduce a new preconditioner for a recently developed pressure-robust hybridized discontinuous Galerkin (HDG) finite element discretization of the Stokes equations. A feature of HDG methods is the straightforward elimination of…

Numerical Analysis · Mathematics 2023-07-07 Sander Rhebergen , Garth N. Wells

Randomized methods are becoming increasingly popular in numerical linear algebra. However, few attempts have been made to use them in developing preconditioners. Our interest lies in solving large-scale sparse symmetric positive definite…

Numerical Analysis · Mathematics 2021-11-16 Hussam Al Daas , Tyrone Rees , Jennifer Scott

This work investigates inexact block Schur complement preconditioning for linear poroelasticity problems discretized using a hybrid approach: Bernardi-Raugel elements for solid displacement and lowest-order weak Galerkin elements for fluid…

Numerical Analysis · Mathematics 2025-12-25 Weizhang Huang , Zhuoran Wang

Poroelasticity problems play an important role in various engineering, geophysical, and biological applications. Their full discretization results in a large-scale saddle-point system at each time step that is becoming singular for locking…

Numerical Analysis · Mathematics 2025-06-27 Weizhang Huang , Zhuoran Wang

This work is concerned with the convergence of the iterative solution for the Stokes flow, discretized with the weak Galerkin finite element method and preconditioned using inexact block Schur complement preconditioning. The resulting…

Numerical Analysis · Mathematics 2024-09-26 Weizhang Huang , Zhuoran Wang

Interior point methods are widely used for different types of mathematical optimization problems. Many implementations of interior point methods in use today rely on direct linear solvers to solve systems of equations in each iteration. The…

Optimization and Control · Mathematics 2024-02-27 Felix Liu , Albin Fredriksson , Stefano Markidis

A block diagonal preconditioner with the minimal residual method and a block triangular preconditioner with the generalized minimal residual method are developed for Hu-Zhang mixed finite element methods of linear elasticity. They are based…

Numerical Analysis · Mathematics 2016-05-24 Long Chen , Jun Hu , Xuehai Huang

This work considers the iterative solution of large-scale problems subject to non-symmetric matrices or operators arising in discretizations of (port-)Hamiltonian partial differential equations. We consider problems governed by an operator…

Numerical Analysis · Mathematics 2025-10-21 Volker Mehrmann , Manuel Schaller , Martin Stoll

In this paper we propose and analyze a preconditioner for a system arising from a finite element approximation of second order elliptic problems describing processes in highly het- erogeneous media. Our approach uses the technique of…

Numerical Analysis · Mathematics 2016-01-14 Johannes Kraus , Raytcho Lazarov , Maria Lymbery , Svetozar Margenov , Ludmil Zikatanov

This paper presents a novel space-time topology optimisation framework for time-dependent thermal conduction problems, aiming to significantly reduce the time-to-solution. By treating time as an additional spatial dimension, we discretise…

Computational Engineering, Finance, and Science · Computer Science 2025-08-14 Joe Alexandersen , Magnus Appel

We propose a novel universal construction of two-level overlapping Schwarz preconditioners for $2m$th-order elliptic boundary value problems, where $m$ is a positive integer. The word "universal" here signifies that the coarse space…

Numerical Analysis · Mathematics 2025-11-11 Jongho Park

In this thesis we study the preconditioning of square, non-symmetric and real Toeplitz systems. We prove theoretical results, which constitute sufficient conditions for the efficiency of the proposed preconditioners and the fast convergence…

Numerical Analysis · Mathematics 2023-03-07 Grigorios Tachyridis

In recent years two Krylov subspace methods have been proposed for solving skew symmetric linear systems, one based on the minimum residual condition, the other on the Galerkin condition. We give new, algorithm-independent proofs that in…

Numerical Analysis · Mathematics 2015-12-02 Stanley C. Eisenstat

Stochastic Galerkin finite element method (SGFEM) provides an efficient alternative to traditional sampling methods for the numerical solution of linear elliptic partial differential equations with parametric or random inputs. However,…

Numerical Analysis · Mathematics 2021-02-16 Alex Bespalov , Daniel Loghin , Rawin Youngnoi