Determining Projection Constants of Univariate Polynomial Spaces

Simon Foucart (1) , Jean-Bernard Lasserre (2)

1 Department of Mathematics [Texas A&M University]
2 LAAS-MAC - Équipe Méthodes et Algorithmes en Commande

The long-standing problem of minimal projections is addressed from a computational point of view. Techniques to determine bounds on the projection constants of univariate polynomial spaces are presented. The upper bound, produced by a linear program, and the lower bound, produced by a semidefinite program exploiting the method of moments, are often close enough to deduce the projection constant with reasonable accuracy. The implementation of these programs makes it possible to find the projection constant of several three-dimensional spaces with five digits of accuracy, as well as the projection constants of the spaces of cubic, quartic, and quintic polynomials with four digits of accuracy. Beliefs about uniqueness and shape-preservation of minimal projections are contested along the way.

Mots clés: projection constant; semidefinite; linear programming; method of moments; AMS classification: 41A44; Minimal projection; 65K05; 90C47; programming; 90C22

Domaines: Analyse numérique [math.NA]; Analyse fonctionnelle [math.FA]; Optimisation et contrôle [math.OC]

Simon Foucart, Jean-Bernard Lasserre. Determining Projection Constants of Univariate Polynomial Spaces. Journal of Approximation Theory, 2018, 235, pp.74-91. ⟨10.1016/j.jat.2018.06.002⟩. ⟨hal-01679124⟩