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Bibliographic Details
Main Author: Hutz, Benjamin
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.11482
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author Hutz, Benjamin
author_facet Hutz, Benjamin
contents We describe a genetic algorithm to find extreme examples in the arithmetic of dynamical systems. The algorithm is applied to four problems: small (non-zero) canonical heights, many rational preperiodic points, long rational cycles, and long rational tails. Data is provided for extreme examples generated for polynomials up to degree 13 and rational functions up to degree 5. This work significantly expands the known examples of extreme behavior for several of the conjectured behaviors in arithmetic dynamics and provides a foundation from which to begin a more advanced application of machine learning techniques in the creation of extreme examples for arithmetic dynamics.
format Preprint
id arxiv_https___arxiv_org_abs_2601_11482
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Genetic Algorithm for Generating Extreme Examples in Arithmetic Dynamics
Hutz, Benjamin
Dynamical Systems
We describe a genetic algorithm to find extreme examples in the arithmetic of dynamical systems. The algorithm is applied to four problems: small (non-zero) canonical heights, many rational preperiodic points, long rational cycles, and long rational tails. Data is provided for extreme examples generated for polynomials up to degree 13 and rational functions up to degree 5. This work significantly expands the known examples of extreme behavior for several of the conjectured behaviors in arithmetic dynamics and provides a foundation from which to begin a more advanced application of machine learning techniques in the creation of extreme examples for arithmetic dynamics.
title A Genetic Algorithm for Generating Extreme Examples in Arithmetic Dynamics
topic Dynamical Systems
url https://arxiv.org/abs/2601.11482