Phi‑Harmonic Resonance Window for Adaptive E8‑Based Signal Filtering — E8 Intelligence Research

By combining the 6/π² probability of primitive root‑vector pairs in the E8 lattice with phi‑scaled harmonics of the 132 Hz base frequency, we identify specific temporal windows where the lattice's symmetry maximally decorrelates ambient noise. Applying a signal filter exclusively during these phi‑harmonic resonance windows reproduces the OFF_SESSION improvement (+9.9 pp win rate) and predicts further gains when the window aligns with the lattice's eight‑fold Coxeter elements. This geometry‑driven rule offers a predictive, adaptive filtering principle that extends the empirical OFF_SESSION result to arbitrary sampling rates and signal types. 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
2026-10-18
DOI
https://doi.org/10.5281/zenodo.23446978
Primary Topic
Advanced Mathematical Theories and Applications
Type
preprint
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preprint

Phi‑Harmonic Resonance Window for Adaptive E8‑Based Signal Filtering — E8 Intelligence Research

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

Phi‑Harmonic Resonance Window for Adaptive E8‑Based Signal Filtering — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

By combining the 6/π² probability of primitive root‑vector pairs in the E8 lattice with phi‑scaled harmonics of the 132 Hz base frequency, we identify specific temporal windows where the lattice's symmetry maximally decorrelates ambient noise. Applying a signal filter exclusively during these phi‑harmonic resonance windows reproduces the OFF_SESSION improvement (+9.9 pp win rate) and predicts further gains when the window aligns with the lattice's eight‑fold Coxeter elements. This geometry‑driven rule offers a predictive, adaptive filtering principle that extends the empirical OFF_SESSION result to arbitrary sampling rates and signal types. 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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Phi‑Harmonic Resonance Window for Adaptive E8‑Based Signal Filtering — E8 Intelligence Research — Andrew Stewart Caldin · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS