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

Fuente: arXiv
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Hauptverfasser: Mirek, Mariusz, Szarek, Tomasz Z., Wróbel, Błażej
Format: Preprint
Veröffentlicht: 2025
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author Mirek, Mariusz
Szarek, Tomasz Z.
Wróbel, Błażej
author_facet Mirek, Mariusz
Szarek, Tomasz Z.
Wróbel, Błażej
contents 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 $r$-variational inequalities on $\ell^p(\mathbb{Z}^d)$ spaces. This is the first instance of a discrete operator in the literature where $\ell^p(\mathbb{Z}^d)$ bounds are provided for the entire range of $1 < p < \infty$. 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.
format Preprint
id arxiv_https___arxiv_org_abs_2503_11259
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Dimension-free estimates for discrete maximal functions related to normalized gaussians
Mirek, Mariusz
Szarek, Tomasz Z.
Wróbel, Błażej
Classical Analysis and ODEs
Functional Analysis
42B25, 42B15
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 $r$-variational inequalities on $\ell^p(\mathbb{Z}^d)$ spaces. This is the first instance of a discrete operator in the literature where $\ell^p(\mathbb{Z}^d)$ bounds are provided for the entire range of $1 < p < \infty$. 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.
title Dimension-free estimates for discrete maximal functions related to normalized gaussians
topic Classical Analysis and ODEs
Functional Analysis
42B25, 42B15
url https://arxiv.org/abs/2503.11259