Random Lozenge Waterfall: Dimensional Collapse of Gibbs Measures
Abstract
We investigate the asymptotic behavior of the q-Racah probability measure on lozenge tilings of a hexagon whose side lengths scale linearly with a large parameter , while the parameters and remain fixed. This regime differs fundamentally from the traditional case , in which random tilings are locally governed by two-dimensional translation-invariant ergodic Gibbs measures. In the fixed-q regime we uncover a new macroscopic phase, the waterfall (previously only observed experimentally), where the two-dimensional Gibbs structure collapses into a one-dimensional random stepped interface that we call a barcode. We prove a law of large numbers and exponential concentration, showing that the random tilings converge to a deterministic waterfall profile. We further conjecture an explicit correlation kernel of the one-dimensional barcode process arising in the limit. Remarkably, the limit is invariant under shifts by but not by , exhibiting an emergent period-two structure absent from the original weights. Our conjectures are supported by extensive numerical evidence and perfect sampling simulations. The kernel is built from a family of functions orthogonal in both spaces and , that may be of independent interest. Our proofs adapt the spectral projection method of Borodin-Gorin-Rains (arXiv:0905.0679) to the regime with fixed~q. The resulting asymptotic analysis is substantially more involved, and leads to non-self-adjoint operators. We overcome these challenges in the exponential concentration result by a separate argument based on sharp bounds for the ratios of probabilities under the q-Racah orthogonal polynomial ensemble.
Keywords
Cite
@article{arxiv.2507.22011,
title = {Random Lozenge Waterfall: Dimensional Collapse of Gibbs Measures},
author = {Alisa Knizel and Leonid Petrov},
journal= {arXiv preprint arXiv:2507.22011},
year = {2025}
}
Comments
65 pages; 14 figures; 5 tables; includes Mathematica code and a python sampling program as ancillary file