On large deviations for Gibbs measures, mean energy and Gamma-convergence
Robert J. Berman

TL;DR
This paper develops a general framework for establishing large deviation principles for Gibbs measures associated with N-particle Hamiltonians, connecting energy functionals and Gamma-convergence, with applications to complex geometry and singular mean field models.
Contribution
It extends the Messer-Spohn approach to a broader class of Hamiltonians, providing new conditions for large deviations and exploring Gamma-convergence in this context.
Findings
Established LDPs for Gibbs measures at positive and negative temperatures.
Connected large deviations with Gamma-convergence of energy functionals.
Applied results to models like Coulomb gases and 2D vortex systems.
Abstract
We consider the random point processes on a measure space X defined by the Gibbs measures associated to a given sequence of N-particle Hamiltonians H^{(N)}. Inspired by the method of Messer-Spohn for proving concentration properties for the laws of the corresponding empirical measures, we propose a number of hypotheses on H^{(N)} which are quite general, but still strong enough to extend the approach of Messer-Spohn. The hypotheses are formulated in terms of the asymptotics of the corresponding mean energy functionals. We show that in many situations the approach even yields a Large Deviation Principle (LDP) for the corresponding laws. Connections to Gamma-convergence of (free) energy type functionals at different levels are also explored. The focus is on differences between positive and negative temperature situations, motivated by applications to complex geometry. The results yield,…
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.
Taxonomy
TopicsMarkov Chains and Monte Carlo Methods · Stochastic processes and statistical mechanics · Geometric Analysis and Curvature Flows
