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This paper introduces a bi-discriminator GAN for synthesizing tabular datasets containing continuous, binary, and discrete columns. Our proposed approach employs an adapted preprocessing scheme and a novel conditional term for the generator…

A new preconditioner is developed for high order finite element approximation of linear elastic problems on triangular meshes in two dimensions. The new preconditioner results in a condition number that is bounded independently of the…

Numerical Analysis · Mathematics 2023-02-10 Mark Ainsworth , Charles Parker

Recent advances in the field of machine learning open a new era in high performance computing. Applications of machine learning algorithms for the development of accurate and cost-efficient surrogates of complex problems have already…

Numerical Analysis · Mathematics 2022-08-26 Stefanos Nikolopoulos , Ioannis Kalogeris , Vissarion Papadopoulos , George Stavroulakis

We present a modified version of the PRESB preconditioner for two-by-two block system of linear equations with the coefficient matrix $$\textbf{A}=\left(\begin{array}{cc} F & -G^* G & F \end{array}\right),$$ where $F\in\mathbb{C}^{n\times…

Numerical Analysis · Mathematics 2024-05-15 Owe Axelsson , Dovod Khojasteh Slakuyeh

Two-level domain decomposition (DD) methods are very powerful techniques for the efficient numerical solution of partial differential equations (PDEs). A two-level domain decomposition method requires two main components: a one-level…

Numerical Analysis · Mathematics 2021-04-22 Gabriele Ciaramella , Tommaso Vanzan

Wave propagation problems governed by the Helmholtz equation remain among the most challenging in scientific computing, due to their indefinite nature. Domain decomposition methods with spectral coarse spaces have emerged as some of the…

Numerical Analysis · Mathematics 2026-04-10 Victorita Dolean , Mark Fry , Matthias Langer

We introduce a novel strategy for constructing symmetric positive definite (SPD) preconditioners for linear systems with symmetric indefinite matrices. The strategy, called absolute value preconditioning, is motivated by the observation…

Numerical Analysis · Mathematics 2016-10-20 Eugene Vecharynski , Andrew V. Knyazev

We construct an algebraic multigrid (AMG) based preconditioner for the reduced Hessian of a linear-quadratic optimization problem constrained by an elliptic partial differential equation. While the preconditioner generalizes a geometric…

Numerical Analysis · Mathematics 2020-02-03 Andrew T. Barker , Andrei Draganescu

In the past decade, there are many works on the finite element methods for the fully nonlinear Hamilton--Jacobi--Bellman (HJB) equations with Cordes condition. The linearised systems have large condition numbers, which depend not only on…

Numerical Analysis · Mathematics 2021-08-12 Guangwei Gao , Shuonan Wu

We introduce a new preconditioner for a recently developed pressure-robust hybridized discontinuous Galerkin (HDG) finite element discretization of the Stokes equations. A feature of HDG methods is the straightforward elimination of…

Numerical Analysis · Mathematics 2023-07-07 Sander Rhebergen , Garth N. Wells

The efficient solution of discretisations of coupled systems of partial differential equations (PDEs) is at the core of much of numerical simulation. Significant effort has been expended on scalable algorithms to precondition Krylov…

Mathematical Software · Computer Science 2018-02-22 Robert C. Kirby , Lawrence Mitchell

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

A new iteration bound for the preconditioned conjugate gradient (PCG) method is presented that more accurately captures convergence for systems with clustered eigenspectra, where the classical condition number-based bound is too…

Numerical Analysis · Mathematics 2025-11-18 Philip Soliman , Filipe Cumaru , Alexander Heinlein

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

In [McDonald, Pestana and Wathen, \textit{SIAM J. Sci. Comput.}, 40 (2018), pp. A1012--A1033], a block circulant preconditioner is proposed for all-at-once linear systems arising from evolutionary partial differential equations, in which…

Numerical Analysis · Mathematics 2021-03-04 X. -L. Lin , M. Ng

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

The numerical simulation of structural mechanics applications via finite elements usually requires the solution of large-size and ill-conditioned linear systems, especially when accurate results are sought for derived variables interpolated…

Numerical Analysis · Mathematics 2019-06-26 Andrea Franceschini , Victor A. Paludetto Magri , Gianluca Mazzucco , Nicolò Spiezia , Carlo Janna

Multiphase flow is a critical process in a wide range of applications, including carbon sequestration, contaminant remediation, and groundwater management. Typically, this process is modeled by a nonlinear system of partial differential…

Numerical Analysis · Mathematics 2018-01-26 Quan M. Bui , Howard C. Elman , J. D. Moulton

Unfitted finite element methods, e.g., extended finite element techniques or the so-called finite cell method, have a great potential for large scale simulations, since they avoid the generation of body-fitted meshes and the use of graph…

Numerical Analysis · Mathematics 2021-09-29 Santiago Badia , Francesc Verdugo

The discretization of certain integral equations, e.g., the first-kind Fredholm equation of Laplace's equation, leads to symmetric positive-definite linear systems, where the coefficient matrix is dense and often ill-conditioned. We…

Numerical Analysis · Mathematics 2022-08-22 Chao Chen , George Biros