Closest Distance between Iterates of Typical Points

Fuente: arXiv
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1. Verfasser: Zhao, Boyuan
Format: Preprint
Veröffentlicht: 2023
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author Zhao, Boyuan
author_facet Zhao, Boyuan
contents The shortest distance between the first $n$ iterates of a typical point can be quantified with a log rule for some dynamical systems admitting Gibbs measures. We show this in two settings. For topologically mixing Markov shifts with at most countably infinite alphabet admitting a Gibbs measure with respect to a locally Hölder potential, we prove the asymptotic length of the longest common substring for a typical point converges and the limit depends on the Rényi entropy. For interval maps with the Gibbs-Markov structure, we prove a similar rule relating the correlation dimension of Gibbs measures with the shortest distance between two iterates in the orbit generated by a typical point.
format Preprint
id arxiv_https___arxiv_org_abs_2306_01628
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Closest Distance between Iterates of Typical Points
Zhao, Boyuan
Dynamical Systems
37B20, 37B10 (Primary) 60F10 (Secondary)
The shortest distance between the first $n$ iterates of a typical point can be quantified with a log rule for some dynamical systems admitting Gibbs measures. We show this in two settings. For topologically mixing Markov shifts with at most countably infinite alphabet admitting a Gibbs measure with respect to a locally Hölder potential, we prove the asymptotic length of the longest common substring for a typical point converges and the limit depends on the Rényi entropy. For interval maps with the Gibbs-Markov structure, we prove a similar rule relating the correlation dimension of Gibbs measures with the shortest distance between two iterates in the orbit generated by a typical point.
title Closest Distance between Iterates of Typical Points
topic Dynamical Systems
37B20, 37B10 (Primary) 60F10 (Secondary)
url https://arxiv.org/abs/2306.01628