Squared polynomial approximation kernels for the hypercube: improved error bounds and implications for Lasserre hierarchies

Fuente: arXiv
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Auteurs principaux: Gribling, Sander, de Klerk, Etienne, Vera, Juan C.
Format: Preprint
Publié: 2026
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author Gribling, Sander
de Klerk, Etienne
Vera, Juan C.
author_facet Gribling, Sander
de Klerk, Etienne
Vera, Juan C.
contents We propose a new family of polynomial approximation kernels for approximating nonnegative polynomials on the hypercube $[-1,1]^n$. Our Kernels produce polynomial sums-of-squares of degree $r$, achieving an $O(\log^3 r/r^2)$ error in the $\ell_1$-norm of the coefficients. This improves on the known error bound $O(1/r)$ from the literature. As a corollary, we obtain an improved convergence rate for the Lasserre hierarchy for polynomial optimization on the hypercube, again improving a known rate by Baldi and Slot from $O(1/r)$ to $O(\log^3 r/r^2)$.
format Preprint
id arxiv_https___arxiv_org_abs_2605_31496
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Squared polynomial approximation kernels for the hypercube: improved error bounds and implications for Lasserre hierarchies
Gribling, Sander
de Klerk, Etienne
Vera, Juan C.
Optimization and Control
We propose a new family of polynomial approximation kernels for approximating nonnegative polynomials on the hypercube $[-1,1]^n$. Our Kernels produce polynomial sums-of-squares of degree $r$, achieving an $O(\log^3 r/r^2)$ error in the $\ell_1$-norm of the coefficients. This improves on the known error bound $O(1/r)$ from the literature. As a corollary, we obtain an improved convergence rate for the Lasserre hierarchy for polynomial optimization on the hypercube, again improving a known rate by Baldi and Slot from $O(1/r)$ to $O(\log^3 r/r^2)$.
title Squared polynomial approximation kernels for the hypercube: improved error bounds and implications for Lasserre hierarchies
topic Optimization and Control
url https://arxiv.org/abs/2605.31496