On quantization and the classical variational principle for the metric mean dimension

Fuente: arXiv
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Autores principales: Carvalho, Maria, Pessil, Gustavo
Formato: Preprint
Publicado: 2026
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author Carvalho, Maria
Pessil, Gustavo
author_facet Carvalho, Maria
Pessil, Gustavo
contents This paper investigates the relationship between quantization of measures and metric mean dimension of topological dynamical systems. We introduce the concept of mean quantization dimension for invariant probability measures and establish a classical variational principle: the metric mean dimension of a dynamical system is equal to the maximum mean quantization dimension among all invariant measures. This approach effectively characterizes the complexity of systems with infinite entropy by identifying a measure that captures information across all scales; and yields a fundamental property that allows for the exchange of limits and suprema in the Lindenstrauss-Tsukamoto variational principles, a feat that most known entropy-like maps fail to achieve due to convexity. Nevertheless, we show that the Katok and Shapira entropies do satisfy this property and, therefore, a classical variational principle for the metric mean dimension, for which maximizing measures always exist.
format Preprint
id arxiv_https___arxiv_org_abs_2603_17091
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle On quantization and the classical variational principle for the metric mean dimension
Carvalho, Maria
Pessil, Gustavo
Dynamical Systems
This paper investigates the relationship between quantization of measures and metric mean dimension of topological dynamical systems. We introduce the concept of mean quantization dimension for invariant probability measures and establish a classical variational principle: the metric mean dimension of a dynamical system is equal to the maximum mean quantization dimension among all invariant measures. This approach effectively characterizes the complexity of systems with infinite entropy by identifying a measure that captures information across all scales; and yields a fundamental property that allows for the exchange of limits and suprema in the Lindenstrauss-Tsukamoto variational principles, a feat that most known entropy-like maps fail to achieve due to convexity. Nevertheless, we show that the Katok and Shapira entropies do satisfy this property and, therefore, a classical variational principle for the metric mean dimension, for which maximizing measures always exist.
title On quantization and the classical variational principle for the metric mean dimension
topic Dynamical Systems
url https://arxiv.org/abs/2603.17091