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Incomplete LU factorizations of sparse matrices are widely used as preconditioners in Krylov subspace methods to speed up solving linear systems. Unfortunately, computing the preconditioner itself can be time-consuming and sensitive to…

Machine Learning · Computer Science 2024-12-12 Paul Häusner , Aleix Nieto Juscafresa , Jens Sjölund

In this paper, we present a generic parametrization of generically zero-dimensional parametric polynomial systems. More specifically, we study the specialization properties of the Rational Univariate Representation and derive bounds on the…

Symbolic Computation · Computer Science 2026-02-09 Florent Corniquel

In this paper we study scalar multivariate subdivision schemes with general integer expanding dilation matrix. Our main result yields simple algebraic conditions on the symbols of such schemes that characterize their polynomial…

Numerical Analysis · Mathematics 2012-11-15 Maria Charina , Lucia Romani

Domain decomposition (DD) methods are widely used as preconditioner techniques. Their effectiveness relies on the choice of a locally constructed coarse space. Thus far, this construction was mostly achieved using non-assembled matrices…

Numerical Analysis · Mathematics 2021-09-14 Hussam Al Daas , Pierre Jolivet

In this paper we want to propose practical numerical methods to solve a class of initial-boundary problem of space-time fractional advection-diffusion equations. To start with, an implicit method based on two-sided Gr\"unwald formulae is…

Numerical Analysis · Mathematics 2016-06-22 Zhi Zhao , Xiao-Qing Jin , Matthew M. Lin

We consider the problem of finding a condition for a univariate polynomial having a given multiplicity structure when the number of distinct roots is given. It is well known that such conditions can be written as conjunctions of several…

Symbolic Computation · Computer Science 2020-08-04 Hoon Hong , Jing Yang

We consider the problem of iteratively solving large and sparse double saddle-point systems arising from the stationary Stokes-Darcy equations in two dimensions, discretized by the Marker-and-Cell (MAC) finite difference method. We analyze…

Numerical Analysis · Mathematics 2023-02-28 Chen Greif , Yunhui He

We present a preconditioning method for the linear systems arising from the boundary element discretization of the Laplace hypersingular equation on a $2$-dimensional triangulated surface $\Gamma$ in $\mathbb{R}^3$. We allow $\Gamma$ to…

Numerical Analysis · Mathematics 2023-10-16 Martin Averseng , Xavier Claeys , Ralf Hiptmair

A known characterization for entire functions that preserve all nonnegative matrices of order two is shown to characterize polynomials that preserve nonnegative matrices of order two. Equivalent conditions are derived and used to prove that…

Rings and Algebras · Mathematics 2022-05-03 Benjamin J. Clark , Pietro Paparella

We aim to solve the incompressible Navier-Stokes equations within the complex microstructure of a porous material. Discretizing the equations on a fine grid using a staggered (e.g., marker-and-cell, mixed FEM) scheme results in a nonlinear…

Numerical Analysis · Mathematics 2025-10-28 Kangan Li , Yashar Mehmani

In this paper, we develop a (preconditioned) GMRES solver based on integer arithmetic, and introduce an iterative refinement framework for the solver. We describe the data format for the coefficient matrix and vectors for the solver that is…

Numerical Analysis · Mathematics 2021-03-04 Takeshi Iwashita , Kengo Suzuki , Takeshi Fukaya

In this paper, we tackle the parametric complete multiplicity problem for a univariate polynomial. Our approach to the parametric complete multiplicity problem has a significant difference from the classical method, which relies on repeated…

Symbolic Computation · Computer Science 2024-12-31 Simin Qin , Bican Xia , Jing Yang

First, we derive explicit computable expressions of structured backward errors of approximate eigenelements of structured matrix polynomials including symmetric, skew-symmetric, Hermitian, skew-Hermitian, even and odd polynomials. We also…

Numerical Analysis · Mathematics 2009-07-16 Bibhas Adhikari , Rafikul Alam

A polynomial matrix inequality is a formula asserting that a polynomial matrix is positive semidefinite. Polynomial matrix optimization concerns minimizing the smallest eigenvalue of a symmetric polynomial matrix subject to a tuple of…

Optimization and Control · Mathematics 2025-06-06 Jared Miller , Jie Wang , Feng Guo

A system of polynomial ordinary differential equations (ODEs) is specified via a vector of multivariate polynomials, or vector field, $F$. A safety assertion $\psi\rightarrow[F]\phi$ means that the trajectory of the system will lie in a…

Logic in Computer Science · Computer Science 2020-03-31 Michele Boreale

The performance of optimization methods is often tied to the spectrum of the objective Hessian. Yet, conventional assumptions, such as smoothness, do often not enable us to make finely-grained convergence statements -- particularly not for…

Optimization and Control · Mathematics 2024-02-08 Nikita Doikov , Sebastian U. Stich , Martin Jaggi

Stationary iterative methods with a symmetric splitting matrix are performed as inner-iteration preconditioning for Krylov subspace methods. We give conditions such that the inner-iteration preconditioning matrix is definite, and show that…

Numerical Analysis · Mathematics 2019-05-20 Keiichi Morikuni

The authors proposed a general way to find particular solutions for overdetermined systems of PDEs previously, where the number of equations is greater than the number of unknown functions. In this paper, we propose an algorithm for finding…

Symbolic Computation · Computer Science 2019-12-30 Maxim Zaytsev , V'yacheslav Akkerman

Given the $n\times n$ matrix polynomial $P(x)=\sum_{i=0}^kP_i x^i$, we consider the associated polynomial eigenvalue problem. This problem, viewed in terms of computing the roots of the scalar polynomial $\det P(x)$, is treated in…

Numerical Analysis · Mathematics 2012-07-27 Dario A. Bini , V. Noferini

We study the solution of large symmetric positive-definite linear systems in a matrix-free setting with a limited iteration budget. We focus on the preconditioned conjugate gradient (PCG) method with spectral preconditioning. Spectral…

Numerical Analysis · Mathematics 2026-04-01 Youssef Diouane , Selime Gürol , Oussama Mouhtal , Dominique Orban