Scaling limit of the colored ASEP and stochastic six-vertex models
Amol Aggarwal, Ivan Corwin, Milind Hegde

TL;DR
This paper proves that colored ASEP and stochastic six-vertex models, under KPZ scaling, converge to the Airy sheet and directed landscape, revealing deep connections to KPZ universality and non-linear fluctuating hydrodynamics.
Contribution
It introduces a framework for analyzing the edge scaling limits of colored models via colored Hall-Littlewood line ensembles, establishing convergence to the Airy sheet and related KPZ structures.
Findings
Convergence of height functions to the Airy sheet under KPZ scaling.
Colored ASEP stationary measures converge to the stationary horizon.
Decoupling of height functions aligns with non-linear fluctuating hydrodynamics predictions.
Abstract
We consider the colored asymmetric simple exclusion process (ASEP) and stochastic six vertex (S6V) model with fully packed initial conditions; the states of these models can be encoded by 2-parameter height functions. We show under Kardar-Parisi-Zhang (KPZ) scaling of time, space, and fluctuations that these height functions converge to the Airy sheet. Several corollaries follow. (1) For ASEP and the S6V model under the basic coupling, we consider the 4-parameter height function at position and time with a step initial condition at position and time , and prove that under KPZ scaling it converges to the directed landscape. (2) We prove that ASEPs under the basic coupling, with multiple general initial data, converge to KPZ fixed points coupled through the directed landscape. (3) We prove that the colored ASEP stationary measures converge to the stationary horizon.…
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Taxonomy
TopicsRandom Matrices and Applications · Statistical Methods and Inference
