Least multivariate Chebyshev polynomials on diagonally determined domains - LAAS-Décision et Optimisation
Preprints, Working Papers, ... Year : 2024

Least multivariate Chebyshev polynomials on diagonally determined domains

Abstract

We consider a new multivariate generalization of the classical monic (univariate) Chebyshev polynomial that minimizes the uniform norm on the interval $[-1,1]$. Let $Π^*_n$ be the subset of polynomials of degree at most $n$ in $d$ variables, whose homogeneous part of degree $n$ has coefficients summing up to $1$. The problem is determining a polynomial in $Π^*_n$ with the smallest uniform norm on a domain $Ω$, which we call a least Chebyshev polynomial (associated with $Ω$). Our main result solves the problem for $Ω$ belonging to a non-trivial class of domains, defined by a property of its diagonal, and establishes the remarkable result that a least Chebyshev polynomial can be given via the classical, univariate, Chebyshev polynomial. In particular, the solution can be independent of the dimension. The result is valid for fairly general domains that can be non-convex and highly irregular.
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Dates and versions

hal-04727563 , version 1 (09-10-2024)

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Mareike Dressler, Simon Foucart, Mioara Joldeş, Etienne de Klerk, Jean-Bernard Lasserre, et al.. Least multivariate Chebyshev polynomials on diagonally determined domains. 2024. ⟨hal-04727563⟩
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