arXiv · 2512.16751
The Fourier Ratio: Uncertainty, Restriction, and Approximation for Compactly Supported Measures
Abstract
We introduce a continuous analog of the Fourier ratio for compactly supported Borel measures. For a measure \(\mu\) on \(\mathbb{R}^d\) and \(f\in L^2(\mu)\), the Fourier ratio compares \(L^1\) and \(L^2\) norms of a regularized Fourier transform at scale \(R\). We develop a fractal uncertainty principle giving sharp two-sided bounds in terms of covering numbers of spatial and frequency supports, with applications to exact signal recovery. We show that small Fourier ratio implies efficient approximation by low-degree trigonometric polynomials in \(L^1\), \(L^2\), and \(L^\infty\). In contrast, restriction estimates reveal a sharp gap between curved measures and random fractal measures, yielding strong lower bounds on approximation degree. Applications to convex surface measures are also obtained.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
A. Iosevich, Z. Li, E. Palsson, A. Yavicoli. 2025-12-18. The Fourier Ratio: Uncertainty, Restriction, and Approximation for Compactly Supported Measures. https://arxiv.org/abs/2512.16751
Cite the original work for its findings. Save a collection to share your selection of sources.