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In this paper we study fast iterative solvers for the large sparse linear systems resulting from the stochastic Galerkin discretization of stochastic partial differential equations. A block triangular preconditioner is introduced and…

Numerical Analysis · Mathematics 2013-04-08 Bin Zheng , Guang Lin , Jinchao Xu

The block structure of double saddle-point problems has prompted extensive research into efficient preconditioners. This paper introduces a novel class of three-by-three block preconditioners tailored for such systems from the…

Numerical Analysis · Mathematics 2025-12-09 Achraf Badahmane

Numerical solution of discrete PDEs corresponding to saddle point problems is highly relevant to physical systems such as Stokes flow. However, scaling up numerical solvers for such systems is often met with challenges in efficiency and…

Numerical Analysis · Mathematics 2024-08-23 Yutian Tao , Eftychios Sifakis

We develop a robust and efficient iterative method for hyper-elastodynamics based on a novel continuum formulation recently developed. The numerical scheme is constructed based on the variational multiscale formulation and the…

Numerical Analysis · Mathematics 2019-02-20 Ju Liu , Alison L. Marsden

This work is on a user-friendly reduced basis method for solving a family of parametric PDEs by preconditioned Krylov subspace methods including the conjugate gradient method, generalized minimum residual method, and bi-conjugate gradient…

Numerical Analysis · Mathematics 2026-02-24 Yuwen Li , Ludmil T. Zikatanov , Cheng Zuo

In this article, we derive a new, fast, and robust preconditioned iterative solution strategy for the all-at-once solution of optimal control problems with time-dependent PDEs as constraints, including the heat equation and the non-steady…

Numerical Analysis · Mathematics 2020-07-17 Santolo Leveque , John W. Pearson

This paper introduces inexact versions of several block-splitting preconditioners for solving the three-by-three block linear systems arising from a special class of indefinite least squares problems. We first establish the convergence…

Numerical Analysis · Mathematics 2026-05-26 Mohaddese Kaveh Shaldehi , Davod Khojasteh Salkuyeh

Stochastic Galerkin finite element discretizations of partial differential equations with coefficients characterized by arbitrary distributions lead, in general, to fully block dense linear systems. We propose two novel strategies for…

Numerical Analysis · Mathematics 2014-07-31 Bedřich Sousedík , Roger G. Ghanem

We study the solution of block-structured linear algebra systems arising in optimization by using iterative solution techniques. These systems are the core computational bottleneck of many problems of interest such as parameter estimation,…

Optimization and Control · Mathematics 2019-09-10 Jose S. Rodriguez , Carl D. Laird , Victor M. Zavala

An inherent regularization strategy and block Schur complement preconditioning are studied for linear poroelasticity problems discretized using the lowest-order weak Galerkin FEM in space and the implicit Euler scheme in time. At each time…

Numerical Analysis · Mathematics 2025-07-31 Weizhang Huang , Zhuoran Wang

We propose a geometry-aware strategy for training neural preconditioners tailored to parametrized linear systems arising from the discretization of mixed-dimensional partial differential equations (PDEs). These systems are typically…

Numerical Analysis · Mathematics 2025-07-22 Nunzio Dimola , Alessandro Coclite , Paolo Zunino

We present a modified version of the PRESB preconditioner for two-by-two block system of linear equations with the coefficient matrix $$\textbf{A}=\left(\begin{array}{cc} F & -G^* G & F \end{array}\right),$$ where $F\in\mathbb{C}^{n\times…

Numerical Analysis · Mathematics 2024-05-15 Owe Axelsson , Dovod Khojasteh Slakuyeh

A Crank-Nicolson finite volume approximation for three-dimensional conservative space-fractional diffusion equation results in large and dense three-level Toeplitz discrete linear systems. Preconditioned Krylov subspace methods with sine…

Numerical Analysis · Mathematics 2026-03-19 Wei Qu , Siu-Long Lei , Sean Y. Hon , Yuan-Yuan Huang

A combination of block-Jacobi and deflation preconditioning is used to solve a high-order discontinuous collocation-based discretization of the Schur complement of the Poisson-Neumann system as arises in the operator splitting of the…

Numerical Analysis · Mathematics 2016-03-23 Sumedh M. Joshi , Greg N. Thomsen , Peter J. Diamessis

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

Coupled systems of free flow and porous media arise in a variety of technical and environmental applications. For laminar flow regimes, such systems are described by the Stokes equations in the free-flow region and Darcy's law in the porous…

Numerical Analysis · Mathematics 2024-10-14 Paula Strohbeck , Iryna Rybak

A linearly implicit conservative difference scheme is applied to discretize the attractive coupled nonlinear Schr\"odinger equations with fractional Laplacian. Complex symmetric linear systems can be obtained, and the system matrices are…

Numerical Analysis · Mathematics 2023-10-19 Yan Cheng , Xi Yang

The paper considers grad-div stabilized equal-order finite elements (FE) methods for the linearized Navier-Stokes equations. A block triangular preconditioner for the resulting system of algebraic equations is proposed which is closely…

Numerical Analysis · Mathematics 2024-11-12 Yunhui He , Maxim Olshanskii

We present a preconditioner for saddle point problems. The proposed preconditioner is extracted from a stationary iterative method which is convergent under a mild condition. Some properties of the preconditioner as well as the eigenvalues…

Numerical Analysis · Mathematics 2016-06-23 Davod Khojasteh Salkuyeh , Mohsen Masoudi

This paper studies the solution of nonsymmetric linear systems by preconditioned Krylov methods based on the normal equations, LSQR in particular. On some examples, preconditioned LSQR is seen to produce errors many orders of magnitude…

Numerical Analysis · Mathematics 2025-03-06 Ethan N. Epperly , Anne Greenbaum , Yuji Nakatsukasa