A Connected Positive Model with a Nonsemialgebraic Likelihood Cell

We give a connected compact rational polygonal model on four outcomes, all of whose probabilities are at least 1/32, with a nonsemialgebraic logarithmic Voronoi cell at a smooth rational point. Near a positive data vector, the cell is the epigraph of an explicit binary entropy expression in rational coordinates. A uniform likelihood gap shows that the connecting segment does not alter this boundary. An elementary proof establishes nonsemialgebraicity over the real numbers. Four outcomes are minimal at a positive-dimensional smooth interior model point, by log-normal containment and convexity. This five-page note complements the earlier work of Alexandr and Heaton and Alexandr's 2026 nonalgebraicity results. It provides a complete explicit theorem relevant to AIM-COMPUTATION-0040, not a full closure of the open-ended AIM Question 26. AI-assisted, self-audited and unrefereed; no formal verification, independent peer review, or absolute priority is claimed.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-18
DOI
https://doi.org/10.5281/zenodo.23444648
Primary Topic
Polynomial and algebraic computation
Type
preprint
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preprint

A Connected Positive Model with a Nonsemialgebraic Likelihood Cell

Alper Ferudun
Zenodo (CERN European Organization for Nuclear Research)
Polynomial and algebraic computation
preprint

A Connected Positive Model with a Nonsemialgebraic Likelihood Cell

Alper Ferudun
preprint en

Abstract

We give a connected compact rational polygonal model on four outcomes, all of whose probabilities are at least 1/32, with a nonsemialgebraic logarithmic Voronoi cell at a smooth rational point. Near a positive data vector, the cell is the epigraph of an explicit binary entropy expression in rational coordinates. A uniform likelihood gap shows that the connecting segment does not alter this boundary. An elementary proof establishes nonsemialgebraicity over the real numbers. Four outcomes are minimal at a positive-dimensional smooth interior model point, by log-normal containment and convexity. This five-page note complements the earlier work of Alexandr and Heaton and Alexandr's 2026 nonalgebraicity results. It provides a complete explicit theorem relevant to AIM-COMPUTATION-0040, not a full closure of the open-ended AIM Question 26. AI-assisted, self-audited and unrefereed; no formal verification, independent peer review, or absolute priority is claimed.

Zenodo (CERN European Organization for Nuclear Research)
Polynomial and algebraic computation
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