February 2024 Detecting structured signals in Ising models
Nabarun Deb, Rajarshi Mukherjee, Sumit Mukherjee, Ming Yuan
Author Affiliations +
Ann. Appl. Probab. 34(1A): 1-45 (February 2024). DOI: 10.1214/23-AAP1929

Abstract

In this paper we study the effect of dependence on detecting a class of signals in Ising models, where the signals are present in a structured way. Examples include Ising models on lattices, and mean-field type Ising models (Erdős–Rényi, Random regular, and dense graphs). Our results rely on correlation decay and mixing type behavior for Ising models, and demonstrate the beneficial behavior of criticality in detection of strictly lower signals. As a by-product of our proof technique, we develop sharp control on mixing and spin-spin correlation for several mean-field type Ising models in all regimes of temperature–which might be of independent interest.

Funding Statement

The research of Sumit Mukherjee was supported in part by NSF Grant DMS-1712037.
The research of Ming Yuan was supported in part by NSF Grant DMS-2015285.

Citation

Download Citation

Nabarun Deb. Rajarshi Mukherjee. Sumit Mukherjee. Ming Yuan. "Detecting structured signals in Ising models." Ann. Appl. Probab. 34 (1A) 1 - 45, February 2024. https://doi.org/10.1214/23-AAP1929

Information

Received: 1 December 2020; Revised: 1 July 2022; Published: February 2024
First available in Project Euclid: 28 January 2024

MathSciNet: MR4696272
zbMATH: 07829137
Digital Object Identifier: 10.1214/23-AAP1929

Subjects:
Primary: 62C20 , 62G10 , 62G20

Keywords: correlation decay , Ising model , signal detection , structured sparsity

Rights: Copyright © 2024 Institute of Mathematical Statistics

Vol.34 • No. 1A • February 2024
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