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Related papers: Generalized Chebyshev Acceleration

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In one of the most important methods in Density Functional Theory - the Full-Potential Linearized Augmented Plane Wave (FLAPW) method - dense generalized eigenproblems are organized in long sequences. Moreover each eigenproblem is strongly…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-05-23 Mario Berljafa , Edoardo Di Napoli

This paper is devoted to studying the global and finite convergence of the semi-smooth Newton method for solving a piecewise linear system that arises in cone-constrained quadratic programming problems and absolute value equations. We first…

Optimization and Control · Mathematics 2023-01-24 Nicolas F. Armijo , Yunier Bello-Cruz , Gabriel Haeser

We present numerical solutions for differential equations by expanding the unknown function in terms of Chebyshev polynomials and solving a system of linear equations directly for the values of the function at the extrema (or zeros) of the…

Computational Physics · Physics 2009-10-31 Bogdan Mihaila , Ioana Mihaila

The generalized Gearhart-Koshy acceleration is a recent exact affine search technique designed for the method of cyclic projections onto hyperplanes, i.e., the Kaczmarz method. However, its convergence properties, particularly the linear…

Numerical Analysis · Mathematics 2026-04-08 Yijie Wang , Yonghan Sun , Deren Han , Jiaxin Xie

In this article, we introduce and study accelerated Landweber methods for linear ill-posed problems obtained by an alteration of the coefficients in the three-term recurrence relation of the \nu-methods. The residual polynomials of the…

Numerical Analysis · Mathematics 2012-12-21 Wolfgang Erb

In this paper, we investigate the AMLI-cycle method and make two contributions. First, we revisit the AMLI-cycle using the Chebyshev polynomials and establish a theory for its uniform convergence, assuming the two-grid method converges…

Numerical Analysis · Mathematics 2025-06-17 Chunyan Niu , Yunhui He , Xiaozhe Hu

We investigate the use of piecewise linear systems, whose coefficient matrix is a piecewise constant function of the solution itself. Such systems arise, for example, from the numerical solution of linear complementarity problems and in the…

Numerical Analysis · Mathematics 2012-06-21 Luigi Brugnano , Alessandra Sestini

In this paper a new method which is a generalization of the Ehrlich-Kjurkchiev method is developed. The method allows to find simultaneously all roots of the algebraic equation in the case when the roots are supposed to be multiple with…

Numerical Analysis · Mathematics 2025-10-20 Anton I. Iliev

We propose new linear combinations of compositions of a basic second-order scheme with appropriately chosen coefficients to construct higher order numerical integrators for differential equations. They can be considered as a generalization…

Numerical Analysis · Mathematics 2024-04-25 Sergio Blanes , Fernando Casas , Luke Shaw

In this paper we demonstrate that a well known linear inequality method developed for rational Chebyshev approximation is equivalent to the application of the bisection method used in quasiconvex optimisation. Although this correspondence…

Optimization and Control · Mathematics 2020-11-17 Vinesha Peiris , Nadezda Sukhorukova

Complex valued systems with an indefinite matrix term arise in important applications such as for certain time-harmonic partial differential equations such as the Maxwell's equation and for the Helmholtz equation. Complex systems with…

Numerical Analysis · Mathematics 2021-10-04 Owe Axelsson , Maeddeh Pourbagher , Davod Khojasteh Salkuyeh

In this paper, we establish a general semilocal convergence theorem (with computationally verifiable initial conditions and error estimates) for iterative methods for simultaneous approximation of polynomial zeros. As application of this…

Numerical Analysis · Mathematics 2015-11-13 Petko D. Proinov

The Kaczmarz method is a row-action method for solving consistent non-square linear systems, and Gearhart-Koshy acceleration is a line-search that minimizes the Euclidean norm of the error along a ray in the direction of a Kaczmarz step.…

Numerical Analysis · Mathematics 2025-06-18 Markus Hegland , Janosch Rieger

We introduce the generalized equidistant Chebyshev polynomials T(k,h) of kind k of hyperkind h, where k,h are positive integers. They are obtained by a generalization of standard and monic Chebyshev polynomials of the first and second…

Mathematical Physics · Physics 2018-10-17 A. M. Pavlyuk

Approximation theorem is one of the most important aspects of numerical analysis that has evolved over the years with many different approaches. Some of the most popular approximation methods include the Lebesgue approximation theorem, the…

Numerical Analysis · Mathematics 2024-04-16 Ishmael N. Amartey

We employ the generalized Remez algorithm, initially suggested by P. T. P. Tang, to perform an experimental study of Chebyshev polynomials in the complex plane. Our focus lies particularly on the examination of their norms and zeros. What…

Complex Variables · Mathematics 2025-07-11 Lennart Aljoscha Hübner , Olof Rubin

Global spectral methods offer the potential to compute solutions of partial differential equations numerically to very high accuracy. In this work, we develop a novel global spectral method for linear partial differential equations on cubes…

Numerical Analysis · Mathematics 2022-10-25 Christoph Strössner , Daniel Kressner

We develop the Akhiezer iteration, a generalization of the classical Chebyshev iteration, for the inner product-free, iterative solution of indefinite linear systems using orthogonal polynomials for measures supported on multiple, disjoint…

Numerical Analysis · Mathematics 2024-01-18 Cade Ballew , Thomas Trogdon

The Kaczmarz method is an iterative numerical method for solving large and sparse rectangular systems of linear equations. Gearhart, Koshy and Tam have developed an acceleration technique for the Kaczmarz method that minimizes the distance…

Numerical Analysis · Mathematics 2022-01-26 Janosch Rieger

Nonlinear acceleration algorithms improve the performance of iterative methods, such as gradient descent, using the information contained in past iterates. However, their efficiency is still not entirely understood even in the quadratic…

Optimization and Control · Mathematics 2019-03-22 Damien Scieur