Skip to main navigation Skip to search Skip to main content

Maximal averages on the affine group Gn and applications

Ji Li, Chun‐Yen Shen, Chaojie Wen

Research output: Contribution to journal › Article › peer-review

Abstract

Let (Formula presented.) be equipped with the left Haar measure (Formula presented.). We study maximal averages associated with three basic motions on (Formula presented.) : horizontal translations, vertical dilations, and fixed hyperbolic geodesics in the upper half-space model. The translation maximal operator is the Euclidean Hardy–Littlewood maximal operator on each horizontal slice. The Haar-compatible dilation maximal operator is of weak type (Formula presented.) and bounded on (Formula presented.) for (Formula presented.), but it is not strongly bounded on (Formula presented.). By contrast, the unweighted Lebesgue dilation average is unbounded on every finite (Formula presented.) and is not of weak type (Formula presented.). For fixed hyperbolic geodesic averages, the large-time part is strongly bounded on (Formula presented.) because of modular exponential decay. The small-time part is a finite-type parabolic maximal problem. Using the corresponding local finite-type (Formula presented.) endpoint estimate for the geodesic slice, we prove (Formula presented.) in weak Orlicz form, together with the strong (Formula presented.) bounds for (Formula presented.). We also show that the strong (Formula presented.) endpoint fails. Finally, we record a discrete random-walk maximal inequality whose sufficient condition is expressed through the modular drift (Formula presented.), where (Formula presented.) is the probability measure defining the right random walk.

Original languageEnglish
Article numbere70252
JournalMathematische Nachrichten
DOIs
Publication statusE-pub ahead of print - 3 Sept 2026

Keywords

  • Lp$L^p$-boundedness
  • isotropic affine groups
  • maximal averages
  • weak-type endpoint estimates

Fingerprint

Dive into the research topics of 'Maximal averages on the affine group Gn and applications'. Together they form a unique fingerprint.

Cite this