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A modification of the generalized shift-splitting (GSS) method is presented for solving singular saddle point problems. In this kind of modification, the diagonal shift matrix is replaced by a block diagonal matrix which is symmetric…

Numerical Analysis · Mathematics 2017-04-26 Davod Khojasteh Salkuyeh , Maryam Rahimian

In this paper, we consider effective discretization strategies and iterative solvers for nonlinear PDE-constrained optimization models for pattern evolution within biological processes. Upon a Sequential Quadratic Programming linearization…

Numerical Analysis · Mathematics 2024-08-28 Karolína Benková , John W. Pearson , Mariya Ptashnyk

Motivated by the need for efficient and accurate simulation of the dynamics of the polar ice sheets, we design high-order finite element discretizations and scalable solvers for the solution of nonlinear incompressible Stokes equations. We…

Numerical Analysis · Computer Science 2015-11-05 Tobin Isaac , Georg Stadler , Omar Ghattas

The iterative diagonalization of a sequence of large ill-conditioned generalized eigenvalue problems is a computational bottleneck in quantum mechanical methods employing a nonorthogonal basis for {\em ab initio} electronic structure…

Materials Science · Physics 2013-08-13 Yunfeng Cai , Zhaojun Bai , John E. Pask , N. Sukumar

In this paper we introduce a parameter dependent class of Krylov-based methods, namely CD, for the solution of symmetric linear systems. We give evidence that in our proposal we generate sequences of conjugate directions, extending some…

Numerical Analysis · Mathematics 2014-08-27 Giovanni Fasano

Domain decomposition (DD) methods are widely used as preconditioner techniques. Their effectiveness relies on the choice of a locally constructed coarse space. Thus far, this construction was mostly achieved using non-assembled matrices…

Numerical Analysis · Mathematics 2021-09-14 Hussam Al Daas , Pierre Jolivet

Large, sparse linear systems are pervasive in modern science and engineering, and Krylov subspace solvers are an established means of solving them. Yet convergence can be slow for ill-conditioned matrices, so practical deployments usually…

A new domain decomposition preconditioner is introduced for efficiently solving linear systems Ax = b with a symmetric positive definite matrix A. The particularity of the new preconditioner is that it is not necessary to have access to the…

Numerical Analysis · Mathematics 2021-06-23 Nicole Spillane

The PMCHWT integral equation enables the modelling of scattering of time-harmonic fields by penetrable, piecewise homogeneous, systems. They have been generalised to include the modelling of composite systems that may contain junctions,…

Computational Engineering, Finance, and Science · Computer Science 2025-06-23 Kristof Cools

We study the problem of preconditioning in sequential prediction. From the theoretical lens of linear dynamical systems, we show that convolving the target sequence corresponds to applying a polynomial to the hidden transition matrix.…

Machine Learning · Computer Science 2026-01-29 Annie Marsden , Elad Hazan

Despite hundreds of papers on preconditioned linear systems of equations, there remains a significant lack of comprehensive performance benchmarks comparing various preconditioners for solving symmetric positive definite (SPD) systems. In…

Numerical Analysis · Mathematics 2025-05-28 Marc A. Tunnell , David F. Gleich

There has been a growing interest in parallel strategies for solving trajectory optimization problems. One key step in many algorithmic approaches to trajectory optimization is the solution of moderately-large and sparse linear systems.…

Optimization and Control · Mathematics 2024-03-05 Xueyi Bu , Brian Plancher

Recently, Garcke et al.[Garcke, Hinze, Kahle, A stable and linear time discretization for a thermodynamically consistent model for two-phase incompressible flow, Applied Numerical Mathematics 99, pp. 151-171, 2016] developed a consistent…

Numerical Analysis · Mathematics 2017-02-16 Jessica Bosch , Christian Kahle , Martin Stoll

We consider the iterative solution of symmetric saddle-point matrices with a singular leading block. We develop a new ideal positive definite block diagonal preconditioner that yields a preconditioned operator with four distinct…

Numerical Analysis · Mathematics 2022-06-29 Susanne Bradley , Chen Greif

For some typical and widely used non-convex half-quadratic regularization models and the Ambrosio-Tortorelli approximate Mumford-Shah model, based on the Kurdyka-\L ojasiewicz analysis and the recent nonconvex proximal algorithms, we…

Optimization and Control · Mathematics 2021-07-30 Shengxiang Deng , Ismail Ben Ayed , Hongpeng Sun

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 two-level nested preconditioned iterative scheme for solving sparse linear systems of equations in which the coefficient matrix is symmetric and indefinite with relatively small number of negative eigenvalues. The proposed…

Numerical Analysis · Computer Science 2019-01-29 Murat Manguoglu , Volker Mehrmann

It is known that the solution of a conservative steady-state two-sided fractional diffusion problem can exhibit singularities near the boundaries. As consequence of this, and due to the conservative nature of the problem, we adopt a finite…

Numerical Analysis · Mathematics 2022-09-20 Marco Donatelli , Rolf Krause , Mariarosa Mazza , Ken Trotti

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

We describe a randomized variant of the block conjugate gradient method for solving a single positive-definite linear system of equations. Our method provably outperforms preconditioned conjugate gradient with a broad-class of…

Numerical Analysis · Mathematics 2026-02-09 Tyler Chen , Caroline Huber , Ethan Lin , Hajar Zaid