English

Dimension-free discretizations of the uniform norm by small product sets

Functional Analysis 2025-01-27 v6 Analysis of PDEs Classical Analysis and ODEs Probability Quantum Physics

Abstract

Let ff be an analytic polynomial of degree at most K1K-1. A classical inequality of Bernstein compares the supremum norm of ff over the unit circle to its supremum norm over the sampling set of the KK-th roots of unity. Many extensions of this inequality exist, often understood under the umbrella of Marcinkiewicz-Zygmund-type inequalities for Lp,1pL^p,1\le p\leq \infty norms. We study dimension-free extensions of these discretization inequalities in the high-dimension regime, where existing results construct sampling sets with cardinality growing with the total degree of the polynomial. In this work we show that dimension-free discretizations are possible with sampling sets whose cardinality is independent of deg(f)\deg(f) and is instead governed by the maximum individual degree of ff; i.e., the largest degree of ff when viewed as a univariate polynomial in any coordinate. For example, we find that for nn-variate analytic polynomials ff of degree at most dd and individual degree at most K1K-1, fL(Dn)C(X)dfL(Xn)\|f\|_{L^\infty(\mathbf{D}^n)}\leq C(X)^d\|f\|_{L^\infty(X^n)} for any fixed XX in the unit disc D\mathbf{D} with X=K|X|=K. The dependence on dd in the constant is tight for such small sampling sets, which arise naturally for example when studying polynomials of bounded degree coming from functions on products of cyclic groups. As an application we obtain a proof of the cyclic group Bohnenblust-Hille inequality with an explicit constant O(logK)2dO(\log K)^{2d}.

Keywords

Cite

@article{arxiv.2310.07926,
  title  = {Dimension-free discretizations of the uniform norm by small product sets},
  author = {Lars Becker and Ohad Klein and Joseph Slote and Alexander Volberg and Haonan Zhang},
  journal= {arXiv preprint arXiv:2310.07926},
  year   = {2025}
}

Comments

27 pages. Previously titled, "Dimension-free Remez Inequalities and norm designs."