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End date: 2024 × Start date: 2020 × Start date: 2020 × DDC: 510 × Publisher: [Madralin] : EMIS ELibEMS × Subject: Random walks in random environment ×

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    Random walks in random hypergeometric environment
    ([Madralin] : EMIS ELibEMS, 2020) Orenshtein, Tal; Sabot, Christophe
    We consider one-dependent random walks on Zd in random hypergeometric environment for d≥3. These are memory-one walks in a large class of environments parameterized by positive weights on directed edges and on pairs of directed edges which includes the class of Dirichlet environments as a special case. We show that the walk is a.s. transient for any choice of the parameters, and moreover that the return time has some finite positive moment. We then give a characterization for the existence of an invariant measure for the process from the point of view of the walker which is absolutely continuous with respect to the initial distribution on the environment in terms of a function κ of the initial weights. These results generalize [Sab11] and [Sab13] on random walks in Dirichlet environment. It turns out that κ coincides with the corresponding parameter in the Dirichlet case, and so in particular the existence of such invariant measures is independent of the weights on pairs of directed edges, and determined solely by the weights on directed edges.
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    Rough invariance principle for delayed regenerative processes
    ([Madralin] : EMIS ELibEMS, 2021) Orenshtein, Tal
    We derive an invariance principle for the lift to the rough path topology of stochastic processes with delayed regenerative increments under an optimal moment condition. An interesting feature of the result is the emergence of area anomaly, a correction term in the second level of the limiting rough path which is identified as the average stochastic area on a regeneration interval. A few applications include random walks in random environment and additive functionals of recurrent Markov chains. The result is formulated in the p-variation settings, where a rough path version of Donsker’s Theorem is available under the second moment condition. The key renewal theorem is applied to obtain an optimal moment condition.