Separation and cut edge in macroscopic clusters for metric graph Gaussian free fields
Zhenhao Cai, Jian Ding

TL;DR
This paper investigates the structure of sign clusters in the Gaussian free field on metric graphs of ^d, revealing new phenomena about cluster distances, pivotal edges, and the role of microscopic loops in higher dimensions.
Contribution
It establishes the existence of closely spaced macroscopic sign clusters in dimensions and higher, contrasting with 2D behavior, and links pivotal edges to the structure of the incipient infinite cluster.
Findings
Existence of two large sign clusters with small graph distance in dimensions and higher.
Typical number of pivotal edges for the one-arm event scales as N^{(rac{d}{2}-1)\u22c2 2}.
Dimension of cut edges in the IIC equals (rac{d}{2}-1) for d.
Abstract
We prove that for the Gaussian free field (GFF) on the metric graph of (for all except the critical dimension ), with uniformly positive probability there exist two distinct sign clusters of diameter at least within a box of size such that their graph distance is less than . This phenomenon contrasts sharply with the two-dimensional case, where the distance between two macroscopic clusters is typically on the order of their diameters, following from the basic property of the scaling limit ``conformal loop ensembles'' (Sheffield-Werner'2001). As a byproduct, we derive that the number of pivotal edges for the one-arm event (i.e., the sign cluster containing the origin has diameter at least ) is typically of order . This immediately implies that for the incipient infinite…
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 · Theoretical and Computational Physics · Random Matrices and Applications
