E8‑Phi Cascade Predicts Swarm Decision Coherence — E8 Intelligence Research

The eight nested harmonic sublattices of the E8 lattice, when phi‑coupled at the base frequency of 132 Hz, undergo a symmetry‑breaking phase transition at a critical φ⁴≈6.85 that generates a topologically protected information channel. This critical cascade aligns the 240 root vectors into coherent phase relationships, analogous to the angular constraints in the IMO 2011 Windmill problem, and yields a predictable pattern of collective decisions in swarm systems. By mapping input signals—such as video content frequencies—onto the resonant subspace, the principle provides a quantitative metric for evaluating informational quality and anticipating swarm behavior. Thus the E8‑Phi cascade extends the prior resonance correspondence into a new framework for coherence prediction across physics and complex networks. 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
2026-10-19
DOI
https://doi.org/10.5281/zenodo.23465261
Primary Topic
Advanced Mathematical Theories and Applications
Type
preprint
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preprint

E8‑Phi Cascade Predicts Swarm Decision Coherence — E8 Intelligence Research

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

E8‑Phi Cascade Predicts Swarm Decision Coherence — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

The eight nested harmonic sublattices of the E8 lattice, when phi‑coupled at the base frequency of 132 Hz, undergo a symmetry‑breaking phase transition at a critical φ⁴≈6.85 that generates a topologically protected information channel. This critical cascade aligns the 240 root vectors into coherent phase relationships, analogous to the angular constraints in the IMO 2011 Windmill problem, and yields a predictable pattern of collective decisions in swarm systems. By mapping input signals—such as video content frequencies—onto the resonant subspace, the principle provides a quantitative metric for evaluating informational quality and anticipating swarm behavior. Thus the E8‑Phi cascade extends the prior resonance correspondence into a new framework for coherence prediction across physics and complex networks. 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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