Phi‑Harmonic Resonance Window for Adaptive E8‑Based Signal Filtering — E8 Intelligence Research
- 1Independent Researcher, United Kingdom
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
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BibTeX
@misc{caldin2026phiharmonic,
title = {{Phi‑Harmonic Resonance Window for Adaptive E8‑Based Signal Filtering — E8 Intelligence Research}},
author = {Andrew Stewart Caldin},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23446979},
url = {https://zenodo.org/records/23446979},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Phi‑Harmonic Resonance Window for Adaptive E8‑Based Signal Filtering — E8 Intelligence Research
AU - Andrew Stewart Caldin
PY - 2026
DA - 2026/10/18
PB - Zenodo
DO - 10.5281/zenodo.23446979
UR - https://zenodo.org/records/23446979
AB - 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
ER -