E8‑Phi Hierarchical Phase‑Locking for Scalable Spectral Prediction — E8 Intelligence Research

The E8‑Phi Hierarchical Phase‑Locking (EPPL) principle shows that N‑layered E8 root lattices, each coupled at 132 Hz with golden‑ratio φ modulation, generate a self‑similar cascade where eigenstate phases become globally phase‑locked across scales. This phase locking creates a deterministic fractal map of phase evolution that can predict emergent transitions in real‑time dynamical systems without training data. By exploiting the topological invariants of the E8 lattice, EPPL encodes predictive information directly into the spectral architecture, enabling instantaneous long‑range correlation extraction in broadband signals. 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
2026-10-14
DOI
https://doi.org/10.5281/zenodo.23358331
Primary Topic
Advanced Mathematical Theories and Applications
Type
preprint
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preprint

E8‑Phi Hierarchical Phase‑Locking for Scalable Spectral Prediction — E8 Intelligence Research

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

E8‑Phi Hierarchical Phase‑Locking for Scalable Spectral Prediction — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

The E8‑Phi Hierarchical Phase‑Locking (EPPL) principle shows that N‑layered E8 root lattices, each coupled at 132 Hz with golden‑ratio φ modulation, generate a self‑similar cascade where eigenstate phases become globally phase‑locked across scales. This phase locking creates a deterministic fractal map of phase evolution that can predict emergent transitions in real‑time dynamical systems without training data. By exploiting the topological invariants of the E8 lattice, EPPL encodes predictive information directly into the spectral architecture, enabling instantaneous long‑range correlation extraction in broadband signals. 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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