A note on correlation inequalities for regular increasing families

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Chen, Yiming, Dai, Guozheng
Format: Preprint
Veröffentlicht: 2026
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866912981669904384
author Chen, Yiming
Dai, Guozheng
author_facet Chen, Yiming
Dai, Guozheng
contents This paper establishes quantitative correlation inequalities between monotone events and structured threshold objects in both the discrete cube and Gaussian space. We prove that for any increasing balanced family, there exists a linear threshold function yielding a covariance lower bound of $c \frac{\log n}{\sqrt{n}}$, and extend this principle to halfspaces in Gaussian space. These results verify the conjectures of Kalai, Keller, and Mossel regarding optimal correlation bounds for linear threshold functions and their Gaussian analogues.
format Preprint
id arxiv_https___arxiv_org_abs_2603_24066
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A note on correlation inequalities for regular increasing families
Chen, Yiming
Dai, Guozheng
Probability
This paper establishes quantitative correlation inequalities between monotone events and structured threshold objects in both the discrete cube and Gaussian space. We prove that for any increasing balanced family, there exists a linear threshold function yielding a covariance lower bound of $c \frac{\log n}{\sqrt{n}}$, and extend this principle to halfspaces in Gaussian space. These results verify the conjectures of Kalai, Keller, and Mossel regarding optimal correlation bounds for linear threshold functions and their Gaussian analogues.
title A note on correlation inequalities for regular increasing families
topic Probability
url https://arxiv.org/abs/2603.24066