Convergence in law of the maximum of the two-dimensional discrete Gaussian free field
Maury Bramson, Jian Ding, Ofer Zeitouni

TL;DR
This paper proves that the distribution of the maximum value of a two-dimensional discrete Gaussian free field, after appropriate recentering, converges as the domain size grows, providing insights into its extreme value behavior.
Contribution
It establishes the convergence in law of the recentered maximum of the 2D Gaussian free field, a significant step in understanding its extreme value distribution.
Findings
Maximum of the field converges in distribution as N grows.
Recentered maximum exhibits a limiting law.
Provides a rigorous foundation for extreme value analysis of GFF.
Abstract
We consider the two-dimensional Gaussian Free Field on a box of side length , with Dirichlet boundary data, and prove the convergence of the law of the recentered maximum of the field.
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
TopicsStochastic processes and statistical mechanics · Stochastic processes and financial applications · Point processes and geometric inequalities
