English

Uniform spanning trees and random matrix statistics

Probability 2025-12-24 v1 Mathematical Physics math.MP

Abstract

We consider a uniform spanning tree in a δ\delta-square grid approximation of a planar domain Ω\Omega. For given integer n2n\ge 2, we condition the tree on the following nn-arm event: we pick nn branches, emanating from nn points microscopically close to a given interior point, and condition them to connect to the boundary Ω\partial \Omega without intersecting. What can be said about the geometry of these branches? We derive an exact formula for the characteristic function of the total winding of the branches. A surprising consequence of this formula is that in the scaling limit, the behaviour of this function depends on the total number of branches nn only through its parity. We also describe the scaling limit of the branches. If Ω\Omega is the unit disc, then they hit the boundary (i.e., the unit circle) at random positions which coincide exactly with the eigenvalues of a random matrix of size nn drawn from the Circular Orthogonal Ensemble (COE, also called Cβ\betaE with β=1\beta =1). Furthermore, the branches converge to Loewner evolution driven by the circular Dyson Brownian motion with parameter β=4\beta = 4 (i.e., nn-sided radial SLEκ_\kappa with κ=2\kappa=2). We thus verify a prediction made by Cardy in this setting. Along the way, we develop a flow-line (imaginary geometry) coupling of nn-sided radial SLEκ_\kappa with the Gaussian free field, which may be of independent interest. Surprisingly, we find that the variance of the corresponding field near the singularity also does not depend on the number n2n\ge 2 of curves. In contrast, the variance of the the winding of the curves behaves as κ/n2\kappa/n^2, which agrees with the predictions from the physics literature made by Wieland and Wilson numerically, and by Duplantier and Binder using Coulomb gas methods -- but disagrees with a result of Kenyon.

Keywords

Cite

@article{arxiv.2512.20540,
  title  = {Uniform spanning trees and random matrix statistics},
  author = {Nathanaël Berestycki and Marcin Lis and Mingchang Liu and Eveliina Peltola},
  journal= {arXiv preprint arXiv:2512.20540},
  year   = {2025}
}

Comments

48 pages

R2 v1 2026-07-01T08:38:52.561Z