English

The fractal uncertainty principle via Dolgopyat's method in higher dimensions

Classical Analysis and ODEs 2025-06-18 v3 Dynamical Systems Spectral Theory

Abstract

We prove a fractal uncertainty principle with exponent d2δ+ε\frac{d}{2} - \delta + \varepsilon, ε>0\varepsilon > 0, for Ahlfors--David regular subsets of Rd\mathbb R^d with dimension δ\delta which satisfy a suitable "nonorthogonality condition". This generalizes the application of Dolgopyat's method by Dyatlov--Jin (arXiv:1702.03619) to prove the same result in the special case d=1d = 1. As a corollary, we get a quantitative spectral gap for the Laplacian on convex cocompact hyperbolic manifolds of arbitrary dimension with Zariski dense fundamental groups.

Keywords

Cite

@article{arxiv.2302.11708,
  title  = {The fractal uncertainty principle via Dolgopyat's method in higher dimensions},
  author = {Aidan Backus and James Leng and Zhongkai Tao},
  journal= {arXiv preprint arXiv:2302.11708},
  year   = {2025}
}

Comments

33 pages, 5 figures, comments welcome. Contains corrections and improved graphics