Irreversible Markov Dynamics and Hydrodynamics for KPZ States in the Stochastic Six Vertex Model
Matthew Nicoletti, Leonid Petrov

TL;DR
This paper introduces irreversible Markov dynamics for the stochastic six vertex model, preserving KPZ states and analyzing hydrodynamics, with explicit drift calculations and connections to integrability via the Yang-Baxter equation.
Contribution
It constructs new irreversible Markov processes that preserve KPZ pure states and analyzes their hydrodynamic behavior using integrability techniques.
Findings
Constructed Markov processes preserve KPZ states
Explicit computation of average drift in KPZ states
Hydrodynamic analysis of non-stationary processes in quarter plane
Abstract
We introduce a family of Markov growth processes on discrete height functions defined on the 2-dimensional square lattice. Each height function corresponds to a configuration of the six vertex model on the infinite square lattice. We focus on the stochastic six vertex model corresponding to a particular two-parameter family of weights within the ferroelectric regime. It is believed (and partially proven, see Aggarwal, arXiv:2004.13272) that the stochastic six vertex model displays nontrivial pure (i.e., translation invariant and ergodic) Gibbs states of two types, KPZ and liquid. These phases have very different long-range correlation structure. The Markov processes we construct preserve the KPZ pure states in the full plane. We also show that the same processes put on the torus preserve arbitrary Gibbs measures for generic six vertex weights (not necessarily in the ferroelectric…
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Taxonomy
TopicsTheoretical and Computational Physics · Stochastic processes and statistical mechanics · Complex Systems and Time Series Analysis
