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A Deterministic Symbolic Sequence from Phonetic Letter Encoding: Sublinear Complexity and an LCR near π
Open accessAbstract
We report a deterministic symbolic sequence generated from a single English letter name using a recursive operator on phonetic encodings. The first 2,000 symbols exhibit sublinear factor complexity, zero topological entropy, near-deterministic letter transitions, and a limiting growth ratio close to π. The sequence is shown over a 16-letter alphabet that has been permuted by a fixed 1–1 substitution for staged disclosure. The original mapping and operator are withheld under the EOA staged disclosure policy and can be made available under a signed collaboration agreement. We provide the sequence, its statistics, and open questions. We invite collaboration to identify the underlying substitution or automaton and to explain the observed phenomena.
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Metadata
- Authors
- Budargham, B.
- Affiliations
- Neurolabs Inc.
- Corresponding author
- Budargham, Bahaa
- ORCID
- Budargham, Bahaa
- Venue
- Zenodo
- Publisher
- Zenodo
- Published
- 2026-09-21
- OpenAlex
- W7213920279
- Cited by
- 0
- References
- 0
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Zenodo (CERN European Organization for Nuclear Research) (cc-by)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › semigroups and automata theory
- Physical Sciences › Mathematics › Theoretical Computer Science › Algorithms and Data Compression
- Physical Sciences › Mathematics › Mathematical Physics › Mathematical Dynamics and Fractals
- Keywords
- topological entropy, pi, automata
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- The paper
- Budargham, B. (2026). A Deterministic Symbolic Sequence from Phonetic Letter Encoding: Sublinear Complexity and an LCR near π. Zenodo. https://doi.org/10.5281/zenodo.22880373
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
