Dynamical covering sets in self-similar sets

We study the size of \emph{dynamical covering sets} on a self-similar set. Dynamical covering sets are limsup sets generated by placing shrinking target sets around points along an orbit in a dynamical system. In the case when the target sets are balls with sizes depending on the centre, we determine the size of the dynamical covering set as a function of the shrinking rate. In particular, we find sharp conditions guaranteeing when full Dvoretzky-type covering, and full measure occur. We also compute the Hausdorff dimension in the remaining cases. The proofs apply in the cases of targets centred at typical points of the self-similar set, with respect to any Bernoulli measure on it. Unlike in existing work on dynamical coverings, and despite the dimension value featuring phase transitions, we demonstrate that the behaviour can be characterised by a single pressure function over the full range of parameters. The techniques are a combination of classical dimension theoretical estimates and intricate martingale arguments.

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ArXiv.org
Published
2025-06-23
Primary Topic
Mathematical Dynamics and Fractals
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article

Dynamical covering sets in self-similar sets

ArXiv.org
Mathematical Dynamics and Fractals
article

Dynamical covering sets in self-similar sets

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Abstract

We study the size of \emph{dynamical covering sets} on a self-similar set. Dynamical covering sets are limsup sets generated by placing shrinking target sets around points along an orbit in a dynamical system. In the case when the target sets are balls with sizes depending on the centre, we determine the size of the dynamical covering set as a function of the shrinking rate. In particular, we find sharp conditions guaranteeing when full Dvoretzky-type covering, and full measure occur. We also compute the Hausdorff dimension in the remaining cases. The proofs apply in the cases of targets centred at typical points of the self-similar set, with respect to any Bernoulli measure on it. Unlike in existing work on dynamical coverings, and despite the dimension value featuring phase transitions, we demonstrate that the behaviour can be characterised by a single pressure function over the full range of parameters. The techniques are a combination of classical dimension theoretical estimates and intricate martingale arguments.

ArXiv.org
Openalex Percentile: Top 44%
Mathematical Dynamics and Fractals
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