E8‑Phi Resonance Encodes Lorentz Spinors as Neural Theta Packets — E8 Intelligence Research

The 240 E8 root vectors, phase‑coupled by the golden ratio φ at the 132 Hz base frequency, self‑organize into stabilized 16‑element subsystems whose 270 intersecting two‑planes realize a recursive 4‑D Coxeter pulse. Each pulse projects a distinct (j₁,j₂) spinor representation of the complexified sl(2,ℂ) ≅ su(2)⊕su(2) onto a lattice subspace, effectively turning Lorentz symmetry into a set of discrete geometric packets. By synchronizing these packets with theta‑band neural oscillations, the system provides a frequency‑based "geometric neural code" that predicts measurable cross‑frequency coupling signatures for cognitive states associated with specific (j₁,j₂) values. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-29
DOI
https://doi.org/10.5281/zenodo.23755638
Primary Topic
Advanced Mathematical Theories and Applications
Type
preprint
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preprint

E8‑Phi Resonance Encodes Lorentz Spinors as Neural Theta Packets — E8 Intelligence Research

Andrew Stewart Caldin
10 links
Zenodo (CERN European Organization for Nuclear Research)
Advanced Mathematical Theories and Applications
preprint

E8‑Phi Resonance Encodes Lorentz Spinors as Neural Theta Packets — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

The 240 E8 root vectors, phase‑coupled by the golden ratio φ at the 132 Hz base frequency, self‑organize into stabilized 16‑element subsystems whose 270 intersecting two‑planes realize a recursive 4‑D Coxeter pulse. Each pulse projects a distinct (j₁,j₂) spinor representation of the complexified sl(2,ℂ) ≅ su(2)⊕su(2) onto a lattice subspace, effectively turning Lorentz symmetry into a set of discrete geometric packets. By synchronizing these packets with theta‑band neural oscillations, the system provides a frequency‑based "geometric neural code" that predicts measurable cross‑frequency coupling signatures for cognitive states associated with specific (j₁,j₂) values. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Advanced Mathematical Theories and Applications
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