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Related papers: On Optimal Algebraic Multigrid Methods

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The method of constructing trigonometric Hermite splines, which interpolate the values of some periodic function and its derivatives in the nodes of a uniform grid, is considered. The proposed method is based on the periodicity properties…

Numerical Analysis · Mathematics 2021-10-12 V. P. Denysiuk

The method of constructing Hermite trigonometric polynomials, which interpolate the values of a certain periodic function and its derivatives up to (including ) the -th ( ) order in nodes of a uniform grid, is considered. The proposed…

Numerical Analysis · Mathematics 2019-02-13 V. P. Denysiuk

We present error estimates of the fully semi-Lagrangian scheme with high-order interpolation operators, solving the initial value problems for the one-dimensional nonlinear diffusive conservation laws, including the Burgers equations. We…

Numerical Analysis · Mathematics 2025-09-22 Haruki Takemura

Interpolatory methods offer a powerful framework for generating reduced-order models (ROMs) for non-parametric or parametric systems with time-varying inputs. Choosing the interpolation points adaptively remains an area of active interest.…

Numerical Analysis · Mathematics 2021-10-13 Sridhar Chellappa , Lihong Feng , Valentin de la Rubia , Peter Benner

A method is suggested for interpolating between small-variable and large-variable asymptotic expansions. The method is based on self-similar approximation theory resulting in self-similar root approximants. The latter are more general than…

High Energy Physics - Phenomenology · Physics 2015-07-01 V. I. Yukalov , S. Gluzman

Algebraic multigrid (AMG) methods derive their optimal efficiency from the interplay between a relaxation process and a corresponding coarse grid correction. In many standard formulations, relaxation and coarse-graining are analyzed and…

Numerical Analysis · Mathematics 2026-03-30 Rayan Moussa , Karsten Kahl

We consider an optimization problem related to semi-active damping of vibrating systems. The main problem is to determine the best damping matrix able to minimize influence of the input on the output of the system. We use a minimization…

Dynamical Systems · Mathematics 2017-07-07 Zoran Tomljanović , Christopher Beattie , Serkan Gugercin

Full polarimetric radio interferometric calibration is performed by estimating 2 by 2 Jones matrices representing instrumental and propagation effects. The solutions obtained in this way differ from the true solutions by a 2 by 2 unitary…

Instrumentation and Methods for Astrophysics · Physics 2013-07-19 Sarod Yatawatta

This paper investigates the algebraic properties of the hyperinterpolation class $\mathbf{HC}(\mathbb{S}^d)$ on the unit sphere $ \mathbb{S}^d $. We focus on operators derived from the classical hyperinterpolation with bounded $ L_2 $…

Functional Analysis · Mathematics 2025-08-04 Congpei An , Jiashu Ran

We establish error estimates for semi-Lagrangian schemes for the initial value problem of one-dimensional conservation laws with a dispersive term, including the Korteweg--de Vries equation. The schemes considered in this paper are based on…

Numerical Analysis · Mathematics 2025-12-03 Haruki Takemura

The aim of this paper is to develop an approach to obtain self-adjoint extensions of symmetric operators acting on anti-dual pairs. The main advantage of such a result is that it can be applied for structures not carrying a Hilbert space…

Functional Analysis · Mathematics 2020-02-17 Zsigmond Tarcsay , Tamás Titkos

Let $z_{1},\ldots,z_{K}$ be distinct grid points. If $f_{k,0}$ is the prescribed value of a function at the grid point $z_{k}$, and $f_{k,r}$ the prescribed value of the $r$\foreignlanguage{american}{-th} derivative, for $1\leq r\leq…

Numerical Analysis · Mathematics 2014-08-28 Burhan Sadiq , Divakar Viswanath

Efficient numerical solvers for sparse linear systems are crucial in science and engineering. One of the fastest methods for solving large-scale sparse linear systems is algebraic multigrid (AMG). The main challenge in the construction of…

Machine Learning · Computer Science 2020-09-25 Ilay Luz , Meirav Galun , Haggai Maron , Ronen Basri , Irad Yavneh

Optimization decomposition methods are a fundamental tool to develop distributed solution algorithms for large scale optimization problems arising in fields such as machine learning and optimal control. In this paper, we present an…

Optimization and Control · Mathematics 2024-03-12 Tyler Hanks , Matthew Klawonn , Evan Patterson , Matthew Hale , James Fairbanks

Effective verification and validation techniques for modern scientific machine learning workflows are challenging to devise. Statistical methods are abundant and easily deployed, but often rely on speculative assumptions about the data and…

Machine Learning · Computer Science 2025-02-11 Tyler Chang , Andrew Gillette , Romit Maulik

This paper establishes new upper bounds for the $A$-numerical radius of operator matrices in semi-Hilbertian spaces by leveraging the $A$-Buzano inequality and developing refined techniques for operator matrices. We present several sharp…

Functional Analysis · Mathematics 2025-07-08 M. H. M. Rashid

Multi-level preconditioners for Discontinuous Galerkin (DG) discretizations are widely used to solve elliptic equations, and a main ingredient of such solvers is the interpolation operator to transfer information from the coarse to the fine…

Numerical Analysis · Mathematics 2021-03-04 Jose Pablo Lucero Lorca , Martin Jakob Gander

Iterative solvers preconditioned with algebraic multigrid have been devised as an optimal technology to speed up the response of large sparse linear systems. In this work, this technique was implemented in the framework of the dual…

Geophysics · Physics 2020-01-22 M. A. Sbai , A. Larabi

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 study in this paper the function approximation error of multivariate linear extrapolation. The sharp error bound of linear interpolation already exists in the literature. However, linear extrapolation is used far more often in…

Optimization and Control · Mathematics 2026-05-20 Liyuan Cao , Zaiwen Wen , Ya-xiang Yuan
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