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 -variational inequalities on spaces. This is the first instance of a discrete operator in the literature where bounds are provided for the entire range of . 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