English

Dimension-free estimates for discrete maximal functions related to normalized gaussians

Classical Analysis and ODEs 2025-03-17 v1 Functional Analysis

Abstract

In this paper, we investigate dimension-free estimates for maximal operators of convolutions with discrete normalized Gaussians (related to the Theta function) in the context of maximal, jump and rr-variational inequalities on p(Zd)\ell^p(\mathbb{Z}^d) spaces. This is the first instance of a discrete operator in the literature where p(Zd)\ell^p(\mathbb{Z}^d) bounds are provided for the entire range of 1<p<1 < p < \infty. The methods of proof rely on developing robust Fourier methods, which are combined with the fractional derivative, a tool that has not been previously applied to studying similar questions in the discrete setting.

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Cite

@article{arxiv.2503.11259,
  title  = {Dimension-free estimates for discrete maximal functions related to normalized gaussians},
  author = {Mariusz Mirek and Tomasz Z. Szarek and Błażej Wróbel},
  journal= {arXiv preprint arXiv:2503.11259},
  year   = {2025}
}

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27 pages