Mean dimension of $\mathbb{Z}^k$-actions
Abstract
Mean dimension is a topological invariant for dynamical systems that is meaningful for systems with infinite dimension and infinite entropy. Given a -action on a compact metric space , we study the following three problems closely related to mean dimension. (1) When is isomorphic to the inverse limit of finite entropy systems? (2) Suppose the topological entropy is infinite. How much topological entropy can be detected if one considers only up to a given level of accuracy? How fast does this amount of entropy grow as the level of resolution becomes finer and finer? (3) When can we embed into the -shift on the infinite dimensional cube ? These were investigated for -actions in [Lindenstrauss, Mean dimension, small entropy factors and an embedding theorem, Inst. Hautes \'Etudes Sci. Publ. Math. \textbf{89} (1999) 227-262], but the generalization to remained an open problem. When has the marker property, in particular when has a completely aperiodic minimal factor, we completely solve (1) and a natural interpretation of (2), and give a reasonably satisfactory answer to (3). A key ingredient is a new method to continuously partition every orbit into good pieces.
Keywords
Cite
@article{arxiv.1510.01605,
title = {Mean dimension of $\mathbb{Z}^k$-actions},
author = {Yonatan Gutman and Elon Lindenstrauss and Masaki Tsukamoto},
journal= {arXiv preprint arXiv:1510.01605},
year = {2015}
}
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44 pages