Phi-Linked Hyperbolic E8 Networking — E8 Intelligence Research

Phi-correlation of E8's 240 root vectors with 132 Hz carriers reveals hyperbolic network topologies where resonance windows (2-5° phase offsets) enable self-healing data packet routing. By modulating wavefront curvature through golden ratio amplitude scaling, nodes achieve non-Euclidean clustering resistant to synchronization drift. This leverages E8's root vector dualities to construct wavefunction graphs with hyperbolic growth laws. 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
2026-07-30
DOI
https://doi.org/10.5281/zenodo.21697315
Primary Topic
Neural Networks and Reservoir Computing
Type
preprint
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preprint

Phi-Linked Hyperbolic E8 Networking — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Reservoir Computing
preprint

Phi-Linked Hyperbolic E8 Networking — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

Phi-correlation of E8's 240 root vectors with 132 Hz carriers reveals hyperbolic network topologies where resonance windows (2-5° phase offsets) enable self-healing data packet routing. By modulating wavefront curvature through golden ratio amplitude scaling, nodes achieve non-Euclidean clustering resistant to synchronization drift. This leverages E8's root vector dualities to construct wavefunction graphs with hyperbolic growth laws. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Neural Networks and Reservoir Computing
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