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20242026
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12 papers · 1 filter

math.CA2026

Uncertainty principles and singular potentials

A. Iosevich, C. Park

We establish uncertainty principles on compact Riemannian manifolds without boundary in the setting of Laplace-Beltrami operators, including the case of real-valued singular potent…

math.CA2026

Spectral synthesis with the complexity parameter

S. Deodhar, A. Iosevich

We show that spectral synthesis thresholds are governed by a quantitative spectral complexity parameter, the Fourier Ratio, in addition to the geometric size of the Fourier support…

math.CA2026

Spectral synthesis on Riemannian manifolds

A. Iosevich, A. Mayeli, E. Wyman

We study spectral synthesis for measures supported on thin subsets of compact Riemannian manifolds. We prove that under natural non-concentration conditions, such measures admit qu…

math.CA2026

Discretization, sampling, and the Fourier ratio

A. Iosevich, E. Palsson, A. Yavicoli

We derive fundamental sampling bounds for smooth signals in continuous settings without sparsity assumptions. By introducing the Fourier ratio as a measure of spectral compressibil…

math.CA2026

The Fourier Ratio: A Unifying Measure of Complexity for Recovery, Localization, and Learning

Will Burstein, Alex Iosevich, Hari Sarang Nathan

We introduce a generalized Fourier ratio, the \(\ell^1/\ell^2\) norm ratio of coefficients in an \emph{arbitrary} orthonormal system, as a single, basis-invariant measure of \emph{…

math.CA2025

The Fourier Ratio and complexity of signals

K. Aldaleh, W. Burstein, G. Garza +12

We study the Fourier ratio of a signal , \[ \mathrm{FR}(f)\ :=\ \sqrt{N}\,\frac{\|\widehat f\|_{L^1(μ)}}{\|\widehat f\|_{L^2(μ)}} \ =\ \frac{\|\widehat…