E8 Polytope Hyper-Torsion for Non-Euclidean Signal Decoupling — E8 Intelligence Research

By applying a rotation matrix derived from the E8 Weyl group to the 12 resonance channels, we induce hyper-torsion across the 132Hz frequency plane. This process separates overlapping stochastic signals into discrete geometric manifolds, allowing the 240 root vectors to act as unique identifiers for signal origin. This prevents the statistical artifacts observed in tight-phase filtering by leveraging the symmetry of the lattice rather than arbitrary angular thresholds. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-15
DOI
https://doi.org/10.5281/zenodo.22762612
Primary Topic
Wireless Signal Modulation Classification
Type
preprint
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E8 Polytope Hyper-Torsion for Non-Euclidean Signal Decoupling — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Wireless Signal Modulation Classification
preprint

E8 Polytope Hyper-Torsion for Non-Euclidean Signal Decoupling — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

By applying a rotation matrix derived from the E8 Weyl group to the 12 resonance channels, we induce hyper-torsion across the 132Hz frequency plane. This process separates overlapping stochastic signals into discrete geometric manifolds, allowing the 240 root vectors to act as unique identifiers for signal origin. This prevents the statistical artifacts observed in tight-phase filtering by leveraging the symmetry of the lattice rather than arbitrary angular thresholds. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Wireless Signal Modulation Classification
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