PreprintCC BY 4.0Zenodo
E8‑Lattice Guided φ‑Harmonic Synaptic Pruning for Adaptive Neuromorphic Learning — E8 Intelligence Research
- 1Independent Researcher, United Kingdom
Abstract
By treating synaptic weight updates as broadband signals superposed on E8 root‑vector modes locked to a 132 Hz carrier, φ‑recursive harmonic folding aligns each update to a low‑entropy coherent channel. This phase‑entropy compression prunes redundant connections while preserving the information‑rich superposition state, yielding networks that self‑optimize predictive capacity akin to E8 resonant superposition. The resulting neuromorphic architecture exhibits scale‑invariant learning, where adding layers corresponds to adding higher‑order E8 shells without loss of coherence.
Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
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BibTeX
@misc{caldin2026e8lattice,
title = {{E8‑Lattice Guided φ‑Harmonic Synaptic Pruning for Adaptive Neuromorphic Learning — E8 Intelligence Research}},
author = {Andrew Stewart Caldin},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23554211},
url = {https://zenodo.org/records/23554211},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - E8‑Lattice Guided φ‑Harmonic Synaptic Pruning for Adaptive Neuromorphic Learning — E8 Intelligence Research
AU - Andrew Stewart Caldin
PY - 2026
DA - 2026/10/22
PB - Zenodo
DO - 10.5281/zenodo.23554211
UR - https://zenodo.org/records/23554211
AB - By treating synaptic weight updates as broadband signals superposed on E8 root‑vector modes locked to a 132 Hz carrier, φ‑recursive harmonic folding aligns each update to a low‑entropy coherent channel. This phase‑entropy compression prunes redundant connections while preserving the information‑rich superposition state, yielding networks that self‑optimize predictive capacity akin to E8 resonant superposition. The resulting neuromorphic architecture exhibits scale‑invariant learning, where adding layers corresponds to adding higher‑order E8 shells without loss of coherence. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
ER -