Frequency of patterns in smooth sequences over the alphabet {1, 3}

TL;DR

This paper develops an ergodic theory framework to analyze the statistical properties and pattern frequencies in smooth sequences over the alphabet {1, 3}, revealing their structure and ergodic behavior.

Contribution

It introduces a novel ergodic theory approach to classify and analyze smooth sequences over {1, 3}, establishing their unique ergodicity and pattern frequency properties.

Findings

Asymptotic pattern frequencies are well-defined for all smooth sequences.

Sequences are partitioned into subshifts based on their type sequences.

All these subshifts are uniquely ergodic, ensuring statistical regularity.

Abstract

We provide an ergodic theory framework to study statistical properties of smooth sequences over the odd alphabet {1, 3}. The arithmetic nature of this alphabet yields a partition of the subshift of smooth sequences based on their local structure, defining a notion of type for those sequences. We describe the substitutive structure of the smaller subshifts obtained by fixing the sequence of types of the successive derivatives of smooth sequences, from which we obtain the unique ergodicity of all these subshifts. A direct consequence is that the asymptotic frequency of any finite pattern in a smooth sequence over {1, 3} is always well-defined and depends on its type sequence. Finally, we characterize the minimality of these subshifts, and propose some perspectives.