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Dimension-free estimates for discrete maximal functions and lattice points in high-dimensional spheres and balls with small radii

Jakub Niksiński, Błażej Wróbel

TL;DR

This work advances the discrete analogue of Stein's dimension-free maximal inequalities by proving dimension-free $\ell^p$ bounds for discrete maximal operators associated with Euclidean spheres and balls in high dimensions, in the small-scale regime. The authors develop a novel multi-parameter maximal operator $\mathcal{D}_{\overline{n}}$ and prove a dimension-free bound on $\ell^p(\mathbb{Z}^d)$ for $p\in[2,\infty]$, reducing the sphere problem to a combinatorial/multiplier framework built on Krawtchouk polynomials and diffusion semigroups. A cornerstone is a uniform saddle-point analysis yielding dimension-free lattice-point counts for $|\sqrt{n}B|$ and $|\sqrt{n}S|$ when $1\le n\le c d$, with explicit exponential-type asymptotics and initial coefficients $b_1=-\tfrac12$, $b_2=-\tfrac16$, $b_3=\tfrac{1}{24}$. By combining these lattice-counting results with precise multiplier difference estimates, the paper achieves dimension-free bounds for the full discrete maximal function over spheres (and, by a simple consequence, balls) on $\ell^p$ for $p\ge 2$ in the small-scale regime, providing a significant discrete analog to Stein's results and suggesting robust techniques for high-dimensional discrete harmonic analysis.

Abstract

We prove that the discrete Hardy-Littlewood maximal function associated with Euclidean spheres with small radii has dimension-free estimates on $\ell^p(\mathbb{Z}^d)$ for $p\in[2,\infty).$ This implies an analogous result for the Euclidean balls, thus making progress on a question of E.M. Stein from the mid 1990s. Our work provides the first dimension-free estimates for full discrete maximal functions related to spheres and balls without relying on comparisons with their continuous counterparts. An important part of our argument is a uniform (dimension-free) count of lattice points in high-dimensional spheres and balls with small radii. We also established a dimension-free estimate for a multi-parameter maximal function of a combinatorial nature, which is a new phenomenon and may be useful for studying similar problems in the future.

Dimension-free estimates for discrete maximal functions and lattice points in high-dimensional spheres and balls with small radii

TL;DR

This work advances the discrete analogue of Stein's dimension-free maximal inequalities by proving dimension-free bounds for discrete maximal operators associated with Euclidean spheres and balls in high dimensions, in the small-scale regime. The authors develop a novel multi-parameter maximal operator and prove a dimension-free bound on for , reducing the sphere problem to a combinatorial/multiplier framework built on Krawtchouk polynomials and diffusion semigroups. A cornerstone is a uniform saddle-point analysis yielding dimension-free lattice-point counts for and when , with explicit exponential-type asymptotics and initial coefficients , , . By combining these lattice-counting results with precise multiplier difference estimates, the paper achieves dimension-free bounds for the full discrete maximal function over spheres (and, by a simple consequence, balls) on for in the small-scale regime, providing a significant discrete analog to Stein's results and suggesting robust techniques for high-dimensional discrete harmonic analysis.

Abstract

We prove that the discrete Hardy-Littlewood maximal function associated with Euclidean spheres with small radii has dimension-free estimates on for This implies an analogous result for the Euclidean balls, thus making progress on a question of E.M. Stein from the mid 1990s. Our work provides the first dimension-free estimates for full discrete maximal functions related to spheres and balls without relying on comparisons with their continuous counterparts. An important part of our argument is a uniform (dimension-free) count of lattice points in high-dimensional spheres and balls with small radii. We also established a dimension-free estimate for a multi-parameter maximal function of a combinatorial nature, which is a new phenomenon and may be useful for studying similar problems in the future.

Paper Structure

This paper contains 13 sections, 30 theorems, 327 equations.

Key Result

Theorem 1.1

For any $\varepsilon>0$ there exists $C_\varepsilon>0$ depending only on $\varepsilon$ and such that holds uniformly in the dimension $d \in \mathbb{N}$ and $p\in[2,\infty]$.

Theorems & Definitions (63)

  • Theorem 1.1
  • Theorem 1.2
  • Theorem 1.3: Part of Theorem \ref{['thm:3.4']}
  • Corollary 1.4
  • Theorem 1.5
  • Remark 1
  • Remark 2
  • Remark 3
  • Definition 2.1
  • Lemma 2.2
  • ...and 53 more