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Autores principales: Agulnick, Aaron, Busick-Warner, Toby
Formato: Preprint
Publicado: 2026
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Acceso en línea:https://arxiv.org/abs/2604.13310
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author Agulnick, Aaron
Busick-Warner, Toby
author_facet Agulnick, Aaron
Busick-Warner, Toby
contents The question of determining a signal from its higher-order autocorrelation data is of practical interest in fields as varied as X-ray crystallography, image processing, and satellite communications. At the heart of the issue is how much of this autocorrelation data one truly needs. We prove two new upper bounds on the order of data needed to determine a signal on a general (i.e. not necessarily cyclic) finite abelian group depending on some knowledge of the vanishing of the signal's Fourier transform. In investigating lower bounds on the required data, we classify signals on $\mathbb{Z}_6$ not determined by their fifth-order data and provide analogous examples on $\mathbb{Z}_{30}$.
format Preprint
id arxiv_https___arxiv_org_abs_2604_13310
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Higher-Order Autocorrelations on Finite Abelian Groups
Agulnick, Aaron
Busick-Warner, Toby
Functional Analysis
43A25
The question of determining a signal from its higher-order autocorrelation data is of practical interest in fields as varied as X-ray crystallography, image processing, and satellite communications. At the heart of the issue is how much of this autocorrelation data one truly needs. We prove two new upper bounds on the order of data needed to determine a signal on a general (i.e. not necessarily cyclic) finite abelian group depending on some knowledge of the vanishing of the signal's Fourier transform. In investigating lower bounds on the required data, we classify signals on $\mathbb{Z}_6$ not determined by their fifth-order data and provide analogous examples on $\mathbb{Z}_{30}$.
title Higher-Order Autocorrelations on Finite Abelian Groups
topic Functional Analysis
43A25
url https://arxiv.org/abs/2604.13310