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Shift‐invariance for vertex models and polymers

Alexei Borodin, Vadim Gorin, Michael Wheeler

2022Proceedings of the London Mathematical Society22 citationsDOIOpen Access PDF

Abstract

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, (1+1)d directed polymers in random media, last passage percolation, the Kardar–Parisi–Zhang equation, and the Airy sheet. In each instance it leads to computations of previously inaccessible joint distributions. The proofs rely on a combination of the Yang–Baxter integrability of the inhomogeneous colored stochastic six-vertex model and Lagrange interpolation. We also show that a simplified (Gaussian) version of our theorems is related to the invariance in law of the local time of the Brownian bridge under the shift of the observation level.

Topics & Concepts

Vertex (graph theory)MathematicsIntegrable systemGaussianBrownian motionMathematical physicsMathematical proofObservableVertex modelPure mathematicsStatistical physicsCombinatoricsPhysicsQuantum mechanicsGeometryGraphStatisticsRandom Matrices and ApplicationsAdvanced Combinatorial MathematicsAlgebraic structures and combinatorial models
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