Entropy-Based Distortion in Hashimoto's fractal in his symbolic Collatz model

We introduce in an exploratory level an entropy-based symbolic model motivated by the binary representation of preimages in the continuous Collatz framework. Using Shannon entropy on finite binary words and their subwords, we define local and global distortion factors depending on the empirical information content of symbol sequences.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-09
DOI
https://doi.org/10.5281/zenodo.18557189
Primary Topic
Benford’s Law and Fraud Detection
Type
article
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article

Entropy-Based Distortion in Hashimoto's fractal in his symbolic Collatz model

Thomas Emile Ouellette
Zenodo (CERN European Organization for Nuclear Research)
Benford’s Law and Fraud Detection
article

Entropy-Based Distortion in Hashimoto's fractal in his symbolic Collatz model

Thomas Emile Ouellette
article en

Abstract

We introduce in an exploratory level an entropy-based symbolic model motivated by the binary representation of preimages in the continuous Collatz framework. Using Shannon entropy on finite binary words and their subwords, we define local and global distortion factors depending on the empirical information content of symbol sequences.

Zenodo (CERN European Organization for Nuclear Research)
Reduced inequalities
Openalex Percentile: Top 65%
Benford’s Law and Fraud Detection
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Entropy-Based Distortion in Hashimoto's fractal in his symbolic Collatz model — Thomas Emile Ouellette · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS