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Tail estimates for the stationary stochastic six-vertex model and ASEP

Benjamin Landon and Philippe Sosoe

Vol. 6 (2025), No. 4, 1327–1378
Abstract

We study the tail exponents for the height function of the stationary stochastic six-vertex model in the moderate deviations regime. For the upper tail of the height function we find upper and lower bounds of matching order, with a tail exponent of 3 2, characteristic of KPZ distributions. We also obtain an upper bound for the lower tail of the same order.

Our results for the stochastic six-vertex model hold under a restriction on the model parameters for which a certain “microscopic concavity” condition holds. Nevertheless, our estimates are sufficiently strong to pass through the degeneration of the stochastic six-vertex model to the ASEP. We therefore obtain tail estimates for both the current as well as the location of a second-class particle in the ASEP with stationary (Bernoulli) initial data. Our estimates complement the variance bounds obtained in the seminal work of Balázs and Seppäläinen.

Keywords
KPZ universality, moderate deviations, six-vertex model
Mathematical Subject Classification
Primary: 60J99
Milestones
Received: 10 June 2024
Revised: 2 June 2025
Accepted: 24 June 2025
Published: 12 October 2025
Authors
Benjamin Landon
Department of Mathematics
University of Toronto
Toronto, ON
Canada
Philippe Sosoe
Department of Mathematics
Cornell University
Ithaca, NY
United States