An Algorithmic Classification of Generalized Pseudo-Anosov Homeomorphisms via Geometric Markov Partitions
Inti Cruz Diaz

TL;DR
This thesis develops an algorithmic method to classify generalized pseudo-Anosov homeomorphisms using geometric Markov partitions and their types, providing a complete invariant for conjugacy classes.
Contribution
It introduces a new classification approach based on geometric types, including an algorithm to determine conjugacy of generalized pseudo-Anosov homeomorphisms.
Findings
Geometric type is a complete invariant of conjugation.
An algorithm to decide conjugacy of generalized pseudo-Anosov homeomorphisms.
Criteria for realizing geometric types by pseudo-Anosov homeomorphisms.
Abstract
This thesis provides a classification of generalized pseudo-Anosov homeomorphisms up to topological conjugacy using an algorithmic approach. A Markov partition of a generalized pseudo-Anosov homeomorphism is a decomposition of the surface into a finite number of rectangles with disjoint interiors, such that their images intersect with any other rectangle in the Markov partition along a finite number of horizontal sub-rectangles. Every generalized pseudo-Anosov homeomorphism has a Markov partition, and, by using the surface's orientation, we can endow any Markov partition with a geometrization. The geometric type of a geometric Markov partition was defined by Bonatti and Langevin in their book, "Diffeomorphismes de Smale des surfaces", to classify saddle-type basic pieces for structurally stable diffeomorphisms on surfaces. A geometric type is an abstract combinatorial object that…
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Taxonomy
TopicsMathematical Dynamics and Fractals · Advanced Topology and Set Theory · Topological and Geometric Data Analysis
