English
Related papers

Related papers: An efficient preconditioner for evolutionary parti…

200 papers

The focus of this study is the construction and numerical validation of parallel block preconditioners for low order virtual element discretizations of the three-dimensional Maxwell equations. The virtual element method (VEM) is a recent…

Numerical Analysis · Mathematics 2023-02-22 Nicolás A. Barnafi , Franco Dassi , Simone Scacchi

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

We present and analyze a two-level restricted additive Schwarz (RAS) preconditioner for heterogeneous Helmholtz problems, based on a multiscale spectral generalized finite element method (MS-GFEM) proposed in [C. Ma, C. Alber, and R.…

Numerical Analysis · Mathematics 2025-03-04 Chupeng Ma , Christian Alber , Robert Scheichl , Yongwei Zhang

We introduce a discrete scheme for second order fully nonlinear parabolic PDEs with Caputo's time fractional derivatives. We prove the convergence of the scheme in the framework of the theory of viscosity solutions. The discrete scheme can…

Analysis of PDEs · Mathematics 2019-02-26 Yoshikazu Giga , Qing Liu , Hiroyoshi Mitake

Most finite element methods for solving time-harmonic wave-propagation problems lead to a linear system with a non-normal coefficient matrix. The non-normality is due to boundary conditions and losses. One way to solve these systems is to…

Numerical Analysis · Mathematics 2015-06-01 Antti Hannukainen

We present a simple way to discretize and precondition mixed variational formulations. Our theory connects with, and takes advantage of, the classical theory of symmetric saddle point problems and the theory of preconditioning symmetric…

Numerical Analysis · Mathematics 2018-05-18 Constantin Bacuta , Jacob Jacavage

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

Multigrid preconditioners and solvers for the indefinite Helmholtz equation suffer from non-stability of the stationary smoothers due to the indefinite spectrum of the operator. In this paper we explore GMRES as a replacement for the…

Numerical Analysis · Computer Science 2015-03-17 Bram Reps , Wim Vanroose , Hisham bin Zubair

We consider the use of multipreconditioning to solve linear systems when more than one preconditioner is available but the optimal choice is not known. In particular, we consider a selective multipreconditioned GMRES algorithm where we…

Numerical Analysis · Mathematics 2021-07-08 Niall Bootland , Andrew Wathen

We introduce a space-time finite element method for the linear time-dependent Schr\"odinger equation with Dirichlet conditions in a bounded Lipschitz domain. The proposed discretization scheme is based on a space-time variational…

Numerical Analysis · Mathematics 2025-04-11 Marco Zank

This paper presents a novel space-time topology optimisation framework for time-dependent thermal conduction problems, aiming to significantly reduce the time-to-solution. By treating time as an additional spatial dimension, we discretise…

Computational Engineering, Finance, and Science · Computer Science 2025-08-14 Joe Alexandersen , Magnus Appel

Solving parametric partial differential equations (PDEs) presents significant challenges for data-driven methods due to the sensitivity of spatio-temporal dynamics to variations in PDE parameters. Machine learning approaches often struggle…

Machine Learning · Computer Science 2024-11-11 Armand Kassaï Koupaï , Jorge Mifsut Benet , Yuan Yin , Jean-Noël Vittaut , Patrick Gallinari

We propose an augmented Lagrangian-based preconditioner to accelerate the convergence of Krylov subspace methods applied to linear systems of equations with a block three-by-three structure such as those arising from mixed finite element…

Numerical Analysis · Mathematics 2023-10-26 Fatemeh P. A. Beik , Michele Benzi

In this paper, we develop the auxiliary space preconditioners for solving the linear system arising from the virtual element methods discretization on polytopal meshes for the second order elliptic equations. The preconditioners are…

Numerical Analysis · Mathematics 2018-12-12 Yunrong Zhu

The solution of matrices with $2\times 2$ block structure arises in numerous areas of computational mathematics, such as PDE discretizations based on mixed-finite element methods, constrained optimization problems, or the implicit or steady…

Numerical Analysis · Mathematics 2023-07-07 Ben S. Southworth , Abdullah A. Sivas , Sander Rhebergen

Polynomial preconditioning is an important tool in solving large linear systems and eigenvalue problems. A polynomial from GMRES can be used to precondition restarted GMRES and restarted Arnoldi. Here we give methods for indefinite matrices…

Numerical Analysis · Mathematics 2025-10-17 Hayden Henson , Ronald B. Morgan

In this paper, we study an evolution equation that involves a half-Laplacian operator derived from the Riesz fractional Laplacian, combined with a differential operator \(\mathcal{L}\). Using the identity $(-\Delta)^{1/2}=\mathcal…

Numerical Analysis · Mathematics 2026-03-18 Pu Yuan , Paul Zegeling , Xian-Ming Gu

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

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

Gaussian processes are flexible probabilistic regression models which are widely used in statistics and machine learning. However, a drawback is their limited scalability to large data sets. To alleviate this, full-scale approximations…

Methodology · Statistics 2026-01-13 Tim Gyger , Reinhard Furrer , Fabio Sigrist
‹ Prev 1 8 9 10 Next ›