collaborators

13 papers

math.AP2026

Uncertainty Principles, Spectral Localization, and Singular Schrödinger Operators on Compact Manifolds

Alex Iosevich, Chamsol Park

We establish uncertainty principles on compact Riemannian manifolds without boundary by combining restriction estimates for orthonormal systems with spectral projection bounds for…

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…

cs.IT2026

High-Dimensional Signal Compression: Lattice Point Bounds and Metric Entropy

A. Iosevich, A. Vagharshakyan, E. Wyman

We study worst-case signal compression under an energy constraint, with coordinate-dependent quantization precisions. The compression problem is reduced to counting lattic…

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…