DETECTING STRUCTURED SIGNALS IN ISING MODELS

• 成果类型: Article
• 署名作者: Deb, Nabarun; Mukherjee, Rajarshi; Mukherjee, Sumit; Yuan, Ming
• 署名单位: Columbia University; Harvard University
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• DOI: 10.1214/23-AAP1929
• 发表日期: 2024
• 页码: 1-45
• 关键词: change-point detection; PHASE-TRANSITION; HIGHER CRITICISM; bump detection; Mean-field; SPARSE; statistics; networks

摘要

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 (Erdos-Renyi, 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.