Uniqueness of Gibbs Measures for Continuous Hardcore Models
David Gamarnik, Kavita Ramanan

TL;DR
This paper introduces a continuous version of the hardcore model on graphs, proving uniqueness of Gibbs measures on regular trees and analyzing the model's behavior in relation to phase transitions and convex polytopes.
Contribution
It formulates a continuous hardcore model, proves the uniqueness of Gibbs measures on regular trees, and connects these results to convex polytopes and partition function approximations.
Findings
Unique Gibbs measure for each activity parameter on regular trees.
No phase transition occurs in the continuous model unlike the discrete case.
Provides asymptotic volume calculations for convex polytopes related to the model.
Abstract
We formulate a continuous version of the well known discrete hardcore (or independent set) model on a locally finite graph, parameterized by the so-called activity parameter . In this version, the state or "spin value" of any node of the graph lies in the interval , the hardcore constraint is satisfied for every edge of the graph, and the space of feasible configurations is given by a convex polytope. When the graph is a regular tree, we show that there is a unique Gibbs measure associated to each activity parameter . Our result shows that, in contrast to the standard discrete hardcore model, the continuous hardcore model does not exhibit a phase transition on the infinite regular tree. We also consider a family of continuous models that interpolate between the discrete and continuous hardcore models on a regular tree…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
