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Use of the stochastic Galerkin finite element methods leads to large systems of linear equations obtained by the discretization of tensor product solution spaces along their spatial and stochastic dimensions. These systems are typically…

Numerical Analysis · Mathematics 2014-07-17 Bedřich Sousedík , Roger G. Ghanem , Eric T. Phipps

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

In this paper we develop and analyse domain decomposition methods for linear systems of equations arising from conforming finite element discretisations of positive Maxwell-type equations. Convergence of domain decomposition methods rely…

Numerical Analysis · Mathematics 2021-07-08 Niall Bootland , Victorita Dolean , Frédéric Nataf , Pierre-Henri Tournier

We consider the solution of full column-rank least squares problems by means of normal equations that are preconditioned, symmetrically or non-symmetrically, with a randomized preconditioner. With an effective preconditioner, the solutions…

Numerical Analysis · Mathematics 2025-12-29 Ilse C. F. Ipsen

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

For the solution of the cubic nonlinear Schr\"odinger equation in one space dimension, we propose and analyse a fully discrete low-regularity integrator. The scheme is explicit and can easily be implemented using the fast Fourier transform…

Numerical Analysis · Mathematics 2021-08-24 Alexander Ostermann , Fangyan Yao

In this paper we investigate the use of half-precision Kronecker product singular value decomposition (SVD) approximations as preconditioners for large-scale Tikhonov regularized least squares problems. Half precision reduces storage…

Numerical Analysis · Mathematics 2023-11-28 Yizhou Chen , Xiang Ji , James Nagy

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

We present a pollution-free first order system least squares (FOSLS) formulation for the Helmholtz equation, solved iteratively using a block preconditioner. This preconditioner consists of two components: one for the Schur complement,…

Numerical Analysis · Mathematics 2025-10-24 Harald Monsuur

We review a technique for solving a class of classical linear partial differential systems of relevance to physics in Minkowski spacetime. All the equations are amenable to analysis in terms of complex solutions in the kernel of the scalar…

General Relativity and Quantum Cosmology · Physics 2022-02-23 Robin W. Tucker , Timothy J. Walton

Operator splitting methods combined with finite element spatial discretizations are studied for time-dependent nonlinear Schr\"odinger equations. In particular, the Schr\"odinger-Poisson equation under homogeneous Dirichlet boundary…

Numerical Analysis · Mathematics 2016-12-22 Winfried Auzinger , Thomas Kassebacher , Othmar Koch , Mechthild Thalhammer

In this rather brief note we present and discuss techniques for solving Kronecker matrix product least squares problems. Our main contribution is an iterative approach that uses the efficient Kronecker matrix-vector multiplication strategy…

Numerical Analysis · Mathematics 2017-05-25 Pranay Seshadri

We present a stationary iteration based upon a block splitting for a class of indefinite least squares problem. Convergence of the proposed method is investigated and optimal value of the involving parameter is used. The induced…

Numerical Analysis · Mathematics 2025-12-15 Davod Khojasteh Salkuyeh

We consider linear systems arising from the use of the finite element method for solving scalar linear elliptic problems. Our main result is that these linear systems, which are symmetric and positive semidefinite, are well approximated by…

Numerical Analysis · Mathematics 2025-10-20 Erik Boman , Bruce Hendrickson , Stephen Vavasis

We present a space-time multigrid method based on tensor-product space-time finite element discretizations. The method is facilitated by the matrix-free capabilities of the {\ttfamily deal.II} library. It addresses both high-order…

Numerical Analysis · Mathematics 2024-08-12 Nils Margenberg , Peter Munch

In this study, we consider the numerical solution of large systems of linear equations obtained from the stochastic Galerkin formulation of stochastic partial differential equations. We propose an iterative algorithm that exploits the…

Numerical Analysis · Mathematics 2016-05-18 Kookjin Lee , Howard C. Elman

This paper introduces a methodology for improving the accuracy and efficiency of reduced order models (ROMs) constructed using the least-squares Petrov-Galerkin (LSPG) projection method through the introduction of preconditioning. Unlike…

Numerical Analysis · Mathematics 2022-03-24 Payton Lindsay , Jeffrey Fike , Irina Tezaur , Kevin Carlberg

In this paper, we are concerned with efficiently solving the sequences of regularized linear least squares problems associated with employing Tikhonov-type regularization with regularization operators designed to enforce edge recovery. An…

Numerical Analysis · Mathematics 2023-06-29 Matthias Bolten , Scott P. MacLachlan , Misha E. Kilmer

We propose a Fourier pseudo-spectral scheme for the space-fractional nonlinear Schr\"odinger equation. The proposed scheme has the following features: it is linearly implicit, it preserves two invariants of the equation, its unique…

Numerical Analysis · Mathematics 2019-09-04 Yuto Miyatake , Tai Nakagawa , Tomohiro Sogabe , Shao-Liang Zhang

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