Abstract

We show how geometric methods from the general theory of fractal dimensions and iterated function systems can be deployed to study symbolic dynamics in the zero entropy regime. More precisely, we establish a dimensional characterization of the topological notion of amorphic complexity. For subshifts with discrete spectrum associated to constant length substitutions, this characterization allows us to derive bounds for the amorphic complexity by interpreting the subshift as the attractor of an iterated function system in a suitable quotient space. As a result, we obtain the general finiteness and positivity of amorphic complexity in this setting and provide a closed formula in case of a binary alphabet.

Highlights

  • The relation between the dimension theory of dynamical systems and ergodic theory is nowadays a well-established field of research

  • In this article we provide this kind of relation for the topological notion of amorphic complexity which was recently introduced in [17] to study dynamical systems with zero entropy

  • An interesting consequence of Theorem 1.1 is that the amorphic complexity of infinite substitution subshifts over two symbols with discrete spectrum is always finite and bounded from below by one

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Summary

Introduction

The relation between the dimension theory of dynamical systems and ergodic theory is nowadays a well-established field of research. Of iterated function systems on general complete metric spaces to estimate the amorphic complexity of subshifts with discrete spectrum associated to primitive constant length substitutions, see Sect. An interesting consequence of Theorem 1.1 is that the amorphic complexity of infinite substitution subshifts over two symbols with discrete spectrum is always finite and bounded from below by one. As it turns out, this holds true over general alphabets. We want to point out that the proof of the previous theorem yields means to compute concrete lower and upper bounds for the amorphic complexity of infinite substitutive subshifts with discrete spectrum, see Sect.

Basic notation and definitions
Asymptotic separation numbers and amorphic complexity
Mean equicontinuity and finite separation numbers
Discrete spectrum and mean equicontinuity
Box dimension and amorphic complexity
Amorphic complexity of constant length substitution subshifts
Iterated function systems and cyclic partitions
Dimensional estimates and discrete spectrum
Finiteness and positivity of amorphic complexity
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