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In the context of the coloured stochastic vertex model in a quadrant, we identify a family of observables whose averages are given by explicit contour integrals. The observables are certain linear combinations of $q$-moments of the coloured…

Probability · Mathematics 2020-11-25 Alexei Borodin , Michael Wheeler

We discover a new property of the stochastic colored six-vertex model called flip-invariance. We use it to show that for a given collection of observables of the model, any transformation that preserves the distribution of each individual…

Probability · Mathematics 2020-12-21 Pavel Galashin

We study the stochastic six vertex model and prove that under weak asymmetry scaling (i.e., when the parameter $\Delta\to 1^+$ so as to zoom into the ferroelectric/disordered phase critical point) its height function fluctuations converge…

Probability · Mathematics 2019-03-15 Ivan Corwin , Promit Ghosal , Hao Shen , Li-Cheng Tsai

We consider a homogeneous stochastic higher spin six vertex model in a quadrant. For this model we derive concise integral representations for multi-point q-moments of the height function and for the q-correlation functions. At least in the…

Probability · Mathematics 2016-05-05 Alexei Borodin , Leonid Petrov

We consider a fully inhomogeneous stochastic higher spin six vertex model in a quadrant. For this model we derive concise integral representations for multi-point q-moments of the height function and for the q-correlation functions. At…

Probability · Mathematics 2016-01-22 Alexei Borodin , Leonid Petrov

We establish a symmetry in a variety of integrable stochastic systems: Certain multi-point distributions of natural observables are unchanged under a shift of a subset of observation points. The property holds for stochastic vertex models,…

Probability · Mathematics 2022-02-02 Alexei Borodin , Vadim Gorin , Michael Wheeler

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…

Probability · Mathematics 2024-04-30 Amol Aggarwal , Ivan Corwin , Milind Hegde

In this paper we consider the Higher Spin Six Vertex Model on the lattice $\mathbb{Z}_{\geq 2} \times \mathbb{Z}_{\geq 1}$. We first identify a family of translation invariant measures and subsequently we study the one point distribution of…

Mathematical Physics · Physics 2019-01-25 Takashi Imamura , Matteo Mucciconi , Tomohiro Sasamoto

We study a new integrable probabilistic system, defined in terms of a stochastic colored vertex model on a square lattice. The main distinctive feature of our model is a new family of parameters attached to diagonals rather than to rows or…

Probability · Mathematics 2022-03-08 Sergei Korotkikh

We introduce a four-parameter family of interacting particle systems on the line which can be diagonalized explicitly via a complete set of Bethe ansatz eigenfunctions, and which enjoy certain Markov dualities. Using this, for the systems…

Probability · Mathematics 2019-06-07 Ivan Corwin , Leonid Petrov

In this article we study the stochastic six vertex model under the scaling proposed by Borodin and Gorin (2018), where the weights of corner-shape vertices are tuned to zero, and prove Conjecture 6.1 therein: that the height fluctuation…

Probability · Mathematics 2018-07-13 Hao Shen , Li-Cheng Tsai

We develop the theory of colored bosonic models (initiated by Borodin and Wheeler). We will show how a family of such models can be used to represent the values of Iwahori vectors in the "spherical model" of representations of $GL_r(F)$,…

Representation Theory · Mathematics 2024-02-19 Daniel Bump , Slava Naprienko

In this paper we consider the stochastic six-vertex model in the quadrant started with step initial data. After a long time $T$, it is known that the one-point height function fluctuations are of order $T^{1/3}$ and governed by the…

Probability · Mathematics 2021-12-06 Evgeni Dimitrov

We study the asymmetric six-vertex model in the quadrant with parameters on the stochastic line. We show that the random height function of the model converges to an explicit deterministic limit shape as the mesh size tends to 0. We further…

Probability · Mathematics 2016-03-16 Alexei Borodin , Ivan Corwin , Vadim Gorin

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…

Probability · Mathematics 2022-02-01 Matthew Nicoletti , Leonid Petrov

We prove an identity that relates the q-Laplace transform of the height function of a (higher spin inhomogeneous) stochastic six vertex model in a quadrant on one side, and a multiplicative functional of a Macdonald measure on the other.…

Mathematical Physics · Physics 2016-08-05 Alexei Borodin

We prove that the joint distribution of the values of the height function for the stochastic six vertex model in a quadrant along a down-right path coincides with that for the lengths of the first columns of partitions distributed according…

Probability · Mathematics 2016-11-30 Alexei Borodin , Alexey Bufetov , Michael Wheeler

This work studies 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…

Probability · Mathematics 2025-10-15 Benjamin Landon , Philippe Sosoe

To obtain Russo-Seymour-Welsh estimates for the height function of the six-vertex model under sloped boundary conditions, which can be leveraged to demonstrate that the height function logarithmically delocalizes under a broader class of…

Probability · Mathematics 2024-08-09 Pete Rigas

In this paper, we study the stationary distributions for the stochastic vertex models. Our main focus is the stochastic six vertex (S6V) model. We show that the extremal stationary distributions of the S6V model are given by product…

Probability · Mathematics 2023-03-23 Yier Lin
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