Ergodicity and central limit theorem for random interval homeomorphisms
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ERGODICITY AND CENTRAL LIMIT THEOREM FOR RANDOM INTERVAL HOMEOMORPHISMS BY
Klaudiusz Czudek∗ Institute of Mathematics, Polish Academy of Sciences ´ Sniadeckich 8, 00-656 Warszawa, Poland e-mail: [email protected] AND
Tomasz Szarek∗∗ Institute of Mathematics, Polish Academy of Sciences Abrahama 18, 81-967 Sopot, Poland e-mail: [email protected] ABSTRACT
The central limit theorem for Markov chains generated by iterated function systems consisting of orientation-preserving homeomorphisms of the interval is proved. We study also ergodicity of such systems.
1. Introduction Random dynamical systems in general and iterated function systems in particular have been extensively studied for many years (see [2, 10, 19] and the references given there). This note is concerned with iterated function systems generated by orientation-preserving homeomorphisms on the interval [0, 1]. It contains a simple proof of unique ergodicity on the open interval (0, 1) for a wide class of iterated function systems. At first this phenomenon was proved by L. Alsed´a and M. Misiurewicz for some function systems consisting of piecewise linear homeomorphisms (see [1]). More general iterated function systems ∗ The research of Klaudiusz Czudek was supported by the Polish Ministry of Science
and Higher Education ”Diamond Grant” 0090/DIA/2017/46.
∗∗ The research Tomasz Szarek was supported by the Polish NCN grant
2016/21/B/ST1/00033. Received January 2, 2019 and in revised form August 13, 2019
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K. CZUDEK AND T. SZAREK
Isr. J. Math.
were considered by M. Gharaei and A. J. Homburg in [15]. Recently D. Malicet obtained unique ergodicity as a consequence of the contraction principle for time homogeneous random walks on the topological group of homeomorphisms defined on the circle and interval (see [26]). His proof, in turn, is based upon an invariance principle of A. Avila and M. Viana (see [3]). The second main objective of this note is to establish a quenched central limit theorem for random interval homeomorphisms. The proof is based on the Maxwell–Woodroofe approach for ergodic stationary Markov chains (see [27]) which generalises the martingale approximation method due to M. D. Gordin and B. A. Lifˇsic (see [16]). Their result allows us to prove the central limit theorem for the stationary Markov chain (the annealed central limit theorem). On the other hand, using some coupling techniques we are able to evaluate the distance between the Fourier transform of the stationary and an arbitrary non-stationary Markov chain. Hence the quenched central limit theorems follows. Lately, quenched central limit theorems have been proved for various nonstationary Markov processes in [22, 17, 24] (see also [11]). For more information we refer the readers to the book by T. Komorowski et al. [21], where a more detailed description of recent results is provided. Many results were formulated for Markov processes with transition probabilities satisfying the spectral gap property in the total variation norm or, at least, in the Kantorovich–Rubinstein no
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