2021
DOI: 10.48550/arxiv.2105.09402
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Optimal-order exit point bounds in exponential last-passage percolation via the coupling technique

Abstract: We develop a new probabilistic method for deriving deviation estimates in directed planar polymer and percolation models. The key estimates are for exit points of geodesics as they cross transversal down-right boundaries. These bounds are of optimal cubic-exponential order. We derive them in the context of last-passage percolation with exponential weights with near-stationary boundary conditions. As a result, the probabilistic coupling method is empowered to treat a variety of problems optimally, which could p… Show more

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Cited by 3 publications
(16 citation statements)
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“…Along the way, we also prove some novel results about geometric last-passage percolation in order to verify our hypotheses. In particular, we prove a new, sharp bound for exit times in increment-stationary geometric last-passage percolation following a strategy recently introduced in [21,22]. This is recorded as Theorem B.1 below.…”
Section: Introductionmentioning
confidence: 99%
“…Along the way, we also prove some novel results about geometric last-passage percolation in order to verify our hypotheses. In particular, we prove a new, sharp bound for exit times in increment-stationary geometric last-passage percolation following a strategy recently introduced in [21,22]. This is recorded as Theorem B.1 below.…”
Section: Introductionmentioning
confidence: 99%
“…More specifically, this article presents a new derivation of optimal-order central moment bounds in planar directed last-passage percolation (LPP). Our technique builds on a recent strengthening [49,50] of the coupling method, and requires no input from integrable probability or random matrix theory. A main appeal of our approach is that it would in principle be conveniently applicable in both zero and positive temperature settings, as long as the associated increment-stationary LPP and free energy processes are sufficiently tractable.…”
mentioning
confidence: 99%
“…The present work introduces our argument in the context of the exponential LPP, one of the quintessential models in the KPZ universality class, with the aim of serving as a detailed blueprint for potential adaptations to the aforementioned settings. Because the inputs from [49,50] were developed for the exponential LPP, this model is also where our presentation can be most concise. 1.2.…”
mentioning
confidence: 99%
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