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We extend to Barvinok's valuations the Euler-Maclaurin expansion formula which we obtained previously for the sum of values of a polynomial over the integral points of a rational polytope. This leads to an improvement of Barvinok's…

Combinatorics · Mathematics 2016-08-14 Velleda Baldoni , Nicole Berline , Michèle Vergne

Given samples of a real or complex-valued function on a set of distinct nodes, the traditional linear Chebyshev approximation is to compute the best minimax approximation on a prescribed linear functional space. Lawson's iteration is a…

Numerical Analysis · Mathematics 2023-08-16 Linyi Yang , Lei-Hong Zhang , Ya-Nan Zhang

We address the problem of the best uniform approximation by linear combinations of a finite system of functions. If the system is Chebyshev and the problem is unconstrained, then the classical Remez algorithm provides a fast and precise…

Numerical Analysis · Mathematics 2025-07-08 Vladimir Yu. Protasov , Rinat Kamalov

The Householder's method is a root-find algorithm which is a natural extension of the methods of Newton and Halley. The current paper mostly focuses on approximating the square root of a positive real number based on these methods. The…

General Mathematics · Mathematics 2025-01-10 Yann Dijoux

We present a semi-analytic method for the integrand reduction of one-loop amplitudes, based on the systematic application of the Laurent expansions to the integrand-decomposition. In the asymptotic limit, the coefficients of the master…

High Energy Physics - Phenomenology · Physics 2015-06-04 Pierpaolo Mastrolia , Edoardo Mirabella , Tiziano Peraro

In a recent paper Lima, Panario and Wang have provided a new method to multiply polynomials in Chebyshev basis which aims at reducing the total number of multiplication when polynomials have small degree. Their idea is to use Karatsuba's…

Computational Complexity · Computer Science 2013-09-10 Pascal Giorgi

Efficient and stable algorithms for the calculation of spectral quantities and correlation functions are some of the key tools in computational condensed matter physics. In this article we review basic properties and recent developments of…

Other Condensed Matter · Physics 2007-05-23 Alexander Weisse , Gerhard Wellein , Andreas Alvermann , Holger Fehske

We investigate the problem of numerical differentiation of bivariate functions from weighted Wiener classes using Chebyshev polynomial expansions. We develop and analyze a new version of the truncation method based on Chebyshev polynomials…

Numerical Analysis · Mathematics 2026-02-02 Maksym Kyselov , Sergiy G. Solodky

Nowadays, low-rank approximations of matrices are an important component of many methods in science and engineering. Traditionally, low-rank approximations are considered in unitary invariant norms, however, recently element-wise…

Numerical Analysis · Mathematics 2026-05-15 Stanislav Morozov , Dmitry Zheltkov , Alexander Osinsky

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

This paper presents four novel domain decomposition algorithms integrated with nonlinear mapping techniques to address collocation-based solutions of eigenvalue problems involving sharp interfaces or steep gradients. The proposed methods…

Numerical Analysis · Mathematics 2025-02-14 Jinwei Yang , Vinod Srinivasan

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 consider discrete linear Chebyshev approximation problems in which the unknown parameters of linear function are fitted by minimizing the maximum absolute deviation of errors. Such problems find application in the solution of…

Optimization and Control · Mathematics 2020-12-22 Nikolai Krivulin

We propose a novel method for reconstructing Laurent expansion of rational functions using $p$-adic numbers. By evaluating the rational functions in $p$-adic fields rather than finite fields, it is possible to probe the expansion…

High Energy Physics - Theory · Physics 2025-11-10 Tianya Xia , Li Lin Yang

For a function that is analytic on and around an interval, Chebyshev polynomial interpolation provides spectral convergence. However, if the function has a singularity close to the interval, the rate of convergence is near one. In these…

Numerical Analysis · Mathematics 2017-08-10 Kevin W. Aiton , Tobin A. Driscoll

In a recent paper we have suggested that the finite temperature density matrix can be computed efficiently by a combination of polynomial expansion and iterative inversion techniques. We present here significant improvements over this…

Materials Science · Physics 2010-10-19 Michele Ceriotti , Thomas D. Kühne , Michele Parrinello

The dominant cost in solving least-square problems using Newton's method is often that of factorizing the Hessian matrix over multiple values of the regularization parameter ($\lambda$). We propose an efficient way to interpolate the…

Machine Learning · Computer Science 2015-06-11 Da Kuang , Alex Gittens , Raffay Hamid

Estimating the Domain of Attraction (DA) of non-polynomial systems is a challenging problem. Taylor expansion is widely adopted for transforming a nonlinear analytic function into a polynomial function, but the performance of Taylor…

Systems and Control · Computer Science 2017-09-18 Dongkun Han , Dimitra Panagou

One of the purposes in this paper is to provide a better understanding of the alternance property which occurs in Chebyshev polynomial approximation and piecewise polynomial approximation problems. In the first part of this paper, we…

Numerical Analysis · Mathematics 2018-01-23 Jean-Pierre Crouzeix , Nadezda Sukhorukova , Julien Ugon

Recurrent tasks such as pricing, calibration and risk assessment need to be executed accurately and in real-time. Simultaneously we observe an increase in model sophistication on the one hand and growing demands on the quality of risk…

Computational Finance · Quantitative Finance 2016-07-11 Maximilian Gaß , Kathrin Glau , Mirco Mahlstedt , Maximilian Mair