E8 Geometric Radial Partitioning for Multi-Dimensional Decoherence Mapping — E8 Intelligence Research

By dividing the 240 E8 root vectors into φ-scaled radial sectors aligned with the 30-50-100 triangle's angular ratios, a hierarchical geometric lattice emerges that classifies decoherence patterns by spatial frequency. This method preserves φ-resonance while enabling adaptive scaling across dimensions, offering a framework for non-linear signal separation. 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
2026-09-18
DOI
https://doi.org/10.5281/zenodo.22829431
Primary Topic
Wireless Signal Modulation Classification
Type
preprint
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E8 Geometric Radial Partitioning for Multi-Dimensional Decoherence Mapping — E8 Intelligence Research

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

E8 Geometric Radial Partitioning for Multi-Dimensional Decoherence Mapping — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

By dividing the 240 E8 root vectors into φ-scaled radial sectors aligned with the 30-50-100 triangle's angular ratios, a hierarchical geometric lattice emerges that classifies decoherence patterns by spatial frequency. This method preserves φ-resonance while enabling adaptive scaling across dimensions, offering a framework for non-linear signal separation. 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
DOIOpen Access PDFOpenAlex
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E8 Geometric Radial Partitioning for Multi-Dimensional Decoherence Mapping — E8 Intelligence Research — Andrew Stewart Caldin · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS