The fractal uncertainty principle via Dolgopyat’smethod in higher dimensions

We prove a fractal uncertainty principle with exponent 1 2 d + , > 0, for Ahlfors-David regular subsets of d with dimension which satisfy a suitable "nonorthogonality condition".This generalizes the application of Dolgopyat's method by Dyatlov and Jin (2018) to higher dimensions.As a corollary, we get a quantitative essential spectral gap for the Laplacian on convex cocompact hyperbolic manifolds of arbitrary dimension with Zariski-dense fundamental groups.

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Publication Details

Journal
Analysis & PDE
Published
2025-06-13
DOI
https://doi.org/10.2140/apde.2025.18.1769
Primary Topic
Mathematical Dynamics and Fractals
Type
article
Field-Weighted Citation Impact
0.00

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article

The fractal uncertainty principle via Dolgopyat’smethod in higher dimensions

Zhongkai Tao, James Leng, Aidan Backus
Analysis & PDE
Mathematical Dynamics and Fractals
article

The fractal uncertainty principle via Dolgopyat’smethod in higher dimensions

Zhongkai Tao, James Leng, Aidan Backus
article en

Abstract

We prove a fractal uncertainty principle with exponent 1 2 d + , > 0, for Ahlfors-David regular subsets of d with dimension which satisfy a suitable "nonorthogonality condition".This generalizes the application of Dolgopyat's method by Dyatlov and Jin (2018) to higher dimensions.As a corollary, we get a quantitative essential spectral gap for the Laplacian on convex cocompact hyperbolic manifolds of arbitrary dimension with Zariski-dense fundamental groups.

Analysis & PDEVol. 18(7)
University of California, Los Angeles (US), Brown University (US), University of California, Berkeley (US)
National Science Foundation
Openalex Percentile: Top 80%
Mathematical Dynamics and Fractals
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