Indexed metadata

MaxCut for MTP2\mathrm{MTP}_2 Covariances

Gleb Smirnov

Source record

Source: arXiv

Published: Sep 9, 2026

arXiv: 2609.10474

Open original source ↗

Source abstract

Let X=(X1,,Xn){0,1}nX=(X_1,\dots,X_n)\in\{0,1\}^n have a multivariate totally positive (MTP2\mathrm{MTP}_2) law. We prove that i<jE[Cov(Xi,XjX[n]{i,j})]n/2, \sum_{i<j}\mathbb{E}\left[\left|\mathrm{Cov}(X_i,X_j \mid X_{[n]\setminus\{i,j\}})\right|\right] \le n/2, and more generally a weighted MaxCut inequality for the fully conditioned covariances. As an application, we confirm a conjecture of Allen and O'Donnell on correlation rounding for signed MTP2\mathrm{MTP}_2 laws.

Evidence graph

No public relationships recorded yet.

Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.