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This work aims to accelerate the convergence of proximal gradient methods used to solve regularized linear inverse problems. This is achieved by designing a polynomial-based preconditioner that targets the eigenvalue spectrum of the normal…

We present a novel linear solver that works well for large systems obtained from discretizing PDEs. It is robust and, for the examples we studied, the computational effort scales linearly with the number of equations. The algorithm is based…

Numerical Analysis · Mathematics 2025-10-20 Klaus Lackner , Ralph Menikoff

We develop a simple algorithmic framework to solve large-scale symmetric positive definite linear systems. At its core, the framework relies on two components: (1) a norm-convergent iterative method (i.e. smoother) and (2) a preconditioner.…

Numerical Analysis · Mathematics 2013-02-18 Xiaozhe Hu , Shuhong Wu , Xiao-Hui Wu , Jinchao Xu , Chen-Song Zhang , Shiquan Zhang , Ludmil Zikatanov

This paper presents a large-scale parallel solver, specifically designed to tackle the challenges of solving high-dimensional and high-contrast linear systems in heat transfer topology optimization. The solver incorporates an interpolation…

Numerical Analysis · Mathematics 2025-01-14 Yingjie Zhou , Changqing Ye , Yucheng Liu , Shubin Fu , Eric T. Chung

We are interested in the numerical solution of nonsymmetric linear systems arising from the discretization of convection-diffusion partial differential equations with separable coefficients and dominant convection. Preconditioners based on…

Numerical Analysis · Mathematics 2015-01-14 Davide Palitta , Valeria Simoncini

In this work, we develop algebraic solvers for linear systems arising from the discretization of second-order elliptic partial differential equations by saddle-point mixed finite element methods of arbitrary polynomial degree $p \ge 0$ on…

Numerical Analysis · Mathematics 2026-02-03 Ani Miraçi , Jan Papež , Martin Vohralík , Ivan Yotov

In this note, we consider preconditioned Krylov subspace methods for discrete fluid-structure interaction problems with a nonlinear hyperelastic material model and covering a large range of flows, e.g, water, blood, and air with highly…

Numerical Analysis · Mathematics 2016-03-15 U. Langer , H. Yang

Most efficient linear solvers use composable algorithmic components, with the most common model being the combination of a Krylov accelerator and one or more preconditioners. A similar set of concepts may be used for nonlinear algebraic…

Numerical Analysis · Mathematics 2016-07-15 Peter R. Brune , Matthew G. Knepley , Barry F. Smith , Xuemin Tu

We develop a robust solver for a mixed finite element convex splitting scheme for the Cahn-Hilliard equation. The key ingredient of the solver is a preconditioned minimal residual algorithm (with a multigrid preconditioner) whose…

Numerical Analysis · Mathematics 2017-09-14 Susanne C. Brenner , Amanda E. Diegel , Li-Yeng Sung

In the context of isogeometric analysis, we consider two discretization approaches that make the resulting stiffness matrix nonsymmetric even if the differential operator is self-adjoint. These are the collocation method and the…

Numerical Analysis · Mathematics 2017-05-15 Mattia Tani

Mixed-dimensional elliptic equations exhibiting a hierarchical structure are commonly used to model problems with high aspect ratio inclusions, such as flow in fractured porous media. We derive general abstract estimates based on the theory…

Numerical Analysis · Mathematics 2022-04-21 Jhabriel Varela , Elyes Ahmed , Eirik Keilegavlen , Jan Martin Nordbotten , Florin Adrian Radu

In this article we present a new multigrid preconditioner for the linear systems arising in the semismooth Newton method solution of certain control-constrained, quadratic distributed optimal control problems. Using a piecewise constant…

Numerical Analysis · Mathematics 2016-02-16 Andrei Draganescu , Jyoti Saraswat

Compatible finite element discretisations for the atmospheric equations of motion have recently attracted considerable interest. Semi-implicit timestepping methods require the repeated solution of a large saddle-point system of linear…

In this paper, we propose a space-time least-squares isogeometric method to solve parabolic evolution problems, well suited for high-degree smooth splines in the space-time domain. We focus on the linear solver and its computational…

Numerical Analysis · Mathematics 2019-09-17 Monica Montardini , Matteo Negri , Giancarlo Sangalli , Mattia Tani

We consider large linear systems arising from the isogeometric discretization of the Poisson problem on a single-patch domain. The numerical solution of such systems is considered a challenging task, particularly when the degree of the…

Numerical Analysis · Mathematics 2016-07-22 Giancarlo Sangalli , Mattia Tani

Elliptic partial differential equations (PDEs) frequently arise in continuum descriptions of physical processes relevant to science and engineering. Multilevel preconditioners represent a family of scalable techniques for solving discrete…

Mathematical Software · Computer Science 2016-04-26 Dave A. May , Patrick Sanan , Karl Rupp , Matthew G. Knepley , Barry F. Smith

In this paper, we derive a practical, general framework for creating adaptive iterative (linearization or splitting) algorithms to solve multi-physics problems. This means that, given an iterative method, we derive \textit{a posteriori}…

Numerical Analysis · Mathematics 2026-01-26 Jakob S. Stokke , Kundan Kumar , Florin A. Radu

In this paper we consider second order elliptic partial differential equations with highly varying (heterogeneous) coefficients on a two-dimensional region. The problems are discretized by a composite finite element (FE) and discontinuous…

Numerical Analysis · Mathematics 2014-05-15 Rui Du , Yunfei Ma , Talal Rahman , Xuejun Xu

We present a two-level preconditioner for solving linear systems arising from the discretization of the elliptic, linear-elastic deformation equation, in displacement unknowns, over domains that have arbitrary geometric and topological…

Numerical Analysis · Mathematics 2025-09-25 Sabit Mahmood Khan , Yashar Mehmani

A high-order accurate adjoint-based optimization framework is presented for unsteady multiphysics problems. The fully discrete adjoint solver relies on the high-order, linearly stable, partitioned solver introduced in [1], where different…

Numerical Analysis · Mathematics 2019-01-01 Daniel Z. Huang , Per-Olof Persson , Matthew J. Zahr
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