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We are interested in obtaining approximate solutions to parameterized linear systems of the form $A(\mu) x(\mu) = b$ for many values of the parameter $\mu$. Here $A(\mu)$ is large, sparse, and nonsingular, with a nonlinear analytic…

Numerical Analysis · Mathematics 2022-06-13 Siobhán Correnty , Elias Jarlebring , Kirk M. Soodhalter

An effective power based parallel preconditioner is proposed for general large sparse linear systems. The preconditioner combines a power series expansion method with some low-rank correction techniques, where the Sherman-Morrison-Woodbury…

Numerical Analysis · Mathematics 2020-02-04 Qingqing Zheng , Yuanzhe Xi , Yousef Saad

Prior to the parallel solution of a large linear system, it is required to perform a partitioning of its equations/unknowns. Standard partitioning algorithms are designed using the considerations of the efficiency of the parallel…

Numerical Analysis · Mathematics 2013-11-19 Eugene Vecharynski , Yousef Saad , Masha Sosonkina

This work proposes a new class of preconditioners for the low rank Generalized Minimal Residual Method (GMRES) for multiterm matrix equations arising from implicit timestepping of linear matrix differential equations. We are interested in…

Numerical Analysis · Mathematics 2024-10-11 Shixu Meng , Daniel Appelo , Yingda Cheng

We consider one-level additive Schwarz domain decomposition preconditioners for the Helmholtz equation with variable coefficients (modelling wave propagation in heterogeneous media), subject to boundary conditions that include wave…

Numerical Analysis · Mathematics 2020-10-06 Shihua Gong , Ivan G. Graham , Euan A. Spence

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

We consider the preconditioned conjugate gradient method (PCG) with optimal preconditioner in the frame of the boundary element method (BEM) for elliptic first-kind integral equations. Our adaptive algorithm steers the termination of PCG as…

Numerical Analysis · Mathematics 2019-03-21 Thomas Führer , Alexander Haberl , Dirk Praetorius , Stefan Schimanko

In this study, the $\theta$-method is used for discretizing a class of evolutionary partial differential equations. Then, we transform the resultant all-at-once linear system and introduce a novel one-sided preconditioner, which can be fast…

Numerical Analysis · Mathematics 2024-08-08 Yuan-Yuan Huang , Po Yin Fung , Sean Y. Hon , Xue-Lei Lin

The eXtended Finite Element Method (XFEM) is an approach for solving problems with non-smooth solutions. In the XFEM, the approximate solution is locally enriched to capture discontinuities without requiring a mesh which conforms to the…

Numerical Analysis · Mathematics 2013-12-23 Christapher Lang , David Makhija , Alireza Doostan , Kurt Maute

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

Numerical Analysis · Mathematics 2016-01-15 Sumedh Joshi , Peter Diamessis

We propose a novel preconditioned inexact primal-dual interior point method for constrained convex quadratic programming problems. The algorithm we describe invokes the preconditioned conjugate gradient method on a new reduced Schur…

Numerical Analysis · Mathematics 2021-12-28 Samah Karim , Edgar Solomonik

The Helmholtz equation poses significant computational challenges due to its oscillatory solutions, particularly for large wavenumbers. Inspired by the Schur complement system for elliptic problems, this paper presents a novel…

Numerical Analysis · Mathematics 2025-05-02 Yi Yu , Marcus Sarkis , Guanglian Li , Zhiwen Zhang

This paper introduces a fully algebraic two-level additive Schwarz preconditioner for general sparse large-scale matrices. The preconditioner is analyzed for symmetric positive definite (SPD) matrices. For those matrices, the coarse space…

Numerical Analysis · Mathematics 2024-01-09 Hussam Al Daas , Pierre Jolivet , Frédéric Nataf , Pierre-Henri Tournier

This paper rigorously analyses preconditioners for the time-harmonic Maxwell equations with absorption, where the PDE is discretised using curl-conforming finite-element methods of fixed, arbitrary order and the preconditioner is…

Numerical Analysis · Mathematics 2020-03-23 Marcella Bonazzoli , Victorita Dolean , Ivan G. Graham , Euan A. Spence , Pierre-Henri Tournier

The use of multigrid and related preconditioners with the finite element method is often limited by the difficulty of applying the algorithm effectively to a problem, especially when the domain has a complex shape or adaptive refinement. We…

Numerical Analysis · Computer Science 2015-03-19 Peter R. Brune , Matthew G. Knepley , L. Ridgway Scott

We present additive Schwarz preconditioners for a class of elliptic optimal control problems discretized by a partition of unity method. The discrete problem is solved by a primal-dual active set algorithm, where the auxiliary system in…

Numerical Analysis · Mathematics 2018-11-20 Susanne C. Brenner , Christopher B. Davis , Li-yeng Sung

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

Motivated by the theory of self-duality which provides a variational formulation and resolution for non self-adjoint partial differential equations \cite{G1, G2}, we propose new templates for solving large non-symmetric linear systems. The…

Numerical Analysis · Mathematics 2008-01-28 Nassif Ghoussoub , Amir Moradifam

We consider the least-squares finite element method (lsfem) for systems of nonlinear ordinary differential equations and establish an optimal error estimate for this method when piecewise linear elements are used. The main assumptions are…

Numerical Analysis · Mathematics 2021-10-01 Matthias Chung , Justin Krueger , Honghu Liu

For linear problems, domain decomposition methods can be used directly as iterative solvers, but also as preconditioners for Krylov methods. In practice, Krylov acceleration is almost always used, since the Krylov method finds a much better…

Numerical Analysis · Mathematics 2016-05-17 V. Dolean , M. J. Gander , F. Kwok , R. Masson , W. Kheriji