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HALF-SPACE MACDONALD PROCESSES

Author(s)
BARRAQUAND, GUILLAUME; BORODIN, ALEXEI; CORWIN, IVAN
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Abstract
© 2020 Journal of Materials Research. All rights reserved. Macdonald processes are measures on sequences of integer partitions built using the Cauchy summation identity for Macdonald symmetric functions. These measures are a useful tool to uncover the integrability of many probabilistic systems, including the Kardar-Parisi-Zhang (KPZ) equation and a number of other models in its universality class. In this paper, we develop the structural theory behind half-space variants of these models and the corresponding half-space Macdonald processes. These processes are built using a Littlewood summation identity instead of the Cauchy identity, and their analysis is considerably harder than their full-space counterparts. We compute moments and Laplace transforms of observables for general half-space Macdonald measures. Introducing new dynamics preserving this class of measures, we relate them to various stochastic processes, in particular the log-gamma polymer in a half-quadrant (they are also related to the stochastic six-vertex model in a half-quadrant and the half-space ASEP). For the polymer model, we provide explicit integral formulas for the Laplace transform of the partition function. Nonrigorous saddle-point asymptotics yield convergence of the directed polymer free energy to either the Tracy-Widom (associated to the Gaussian orthogonal or symplectic ensemble) or the Gaussian distribution depending on the average size of weights on the boundary.
Date issued
2020
URI
https://hdl.handle.net/1721.1/135957
Department
Massachusetts Institute of Technology. Department of Mathematics
Journal
Forum of Mathematics, Pi
Publisher
Cambridge University Press (CUP)

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