Optimization-Aided Construction of Multivariate Chebyshev Polynomials

Fuente: arXiv
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Main Authors: Dressler, Mareike, Foucart, Simon, Joldes, Mioara, de Klerk, Etienne, Lasserre, Jean Bernard, Xu, Yuan
Format: Preprint
Published: 2024
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_version_ 1866914991459794944
author Dressler, Mareike
Foucart, Simon
Joldes, Mioara
de Klerk, Etienne
Lasserre, Jean Bernard
Xu, Yuan
author_facet Dressler, Mareike
Foucart, Simon
Joldes, Mioara
de Klerk, Etienne
Lasserre, Jean Bernard
Xu, Yuan
contents This article is concerned with an extension of univariate Chebyshev polynomials of the first kind to the multivariate setting, where one chases best approximants to specific monomials by polynomials of lower degree relative to the uniform norm. Exploiting the Moment-SOS hierarchy, we devise a versatile semidefinite-programming-based procedure to compute such best approximants, as well as associated signatures. Applying this procedure in three variables leads to the values of best approximation errors for all monomials up to degree six on the euclidean ball, the simplex, and the cross-polytope. Furthermore, inspired by numerical experiments, we obtain explicit expressions for Chebyshev polynomials in two cases unresolved before, namely for the monomial $x_1^2 x_2^2 x_3$ on the euclidean ball and for the monomial $x_1^2 x_2 x_3$ on the simplex.
format Preprint
id arxiv_https___arxiv_org_abs_2405_10438
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimization-Aided Construction of Multivariate Chebyshev Polynomials
Dressler, Mareike
Foucart, Simon
Joldes, Mioara
de Klerk, Etienne
Lasserre, Jean Bernard
Xu, Yuan
Optimization and Control
Numerical Analysis
41A10, 65D15, 90C22
This article is concerned with an extension of univariate Chebyshev polynomials of the first kind to the multivariate setting, where one chases best approximants to specific monomials by polynomials of lower degree relative to the uniform norm. Exploiting the Moment-SOS hierarchy, we devise a versatile semidefinite-programming-based procedure to compute such best approximants, as well as associated signatures. Applying this procedure in three variables leads to the values of best approximation errors for all monomials up to degree six on the euclidean ball, the simplex, and the cross-polytope. Furthermore, inspired by numerical experiments, we obtain explicit expressions for Chebyshev polynomials in two cases unresolved before, namely for the monomial $x_1^2 x_2^2 x_3$ on the euclidean ball and for the monomial $x_1^2 x_2 x_3$ on the simplex.
title Optimization-Aided Construction of Multivariate Chebyshev Polynomials
topic Optimization and Control
Numerical Analysis
41A10, 65D15, 90C22
url https://arxiv.org/abs/2405.10438