E8 Quaternion‑Root Tensor Networks Generate Adaptive Quasiperiodic Frequency Combs for Neuromorphic Computing — E8 Intelligence Research

By treating each of the 240 E8 root vectors as a quaternionic resonance channel and applying 120° rotational symmetries to their tensor products, a self‑similar hierarchy of phi‑scaled subharmonics of the 132 Hz base frequency emerges. This hierarchy forms a quasiperiodic frequency comb whose Fourier spectrum reproduces Penrose‑tiling order, providing a dense, non‑redundant set of resonant modes that can be dynamically reconfigured via external perturbations. The resulting adaptive comb serves as a hardware‑level reservoir for neuromorphic systems, enabling real‑time learning and signal processing through geometrically encoded quasicrystalline dynamics. 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.22824281
Primary Topic
Quasicrystal Structures and Properties
Type
preprint
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E8 Quaternion‑Root Tensor Networks Generate Adaptive Quasiperiodic Frequency Combs for Neuromorphic Computing — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Quasicrystal Structures and Properties
preprint

E8 Quaternion‑Root Tensor Networks Generate Adaptive Quasiperiodic Frequency Combs for Neuromorphic Computing — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

By treating each of the 240 E8 root vectors as a quaternionic resonance channel and applying 120° rotational symmetries to their tensor products, a self‑similar hierarchy of phi‑scaled subharmonics of the 132 Hz base frequency emerges. This hierarchy forms a quasiperiodic frequency comb whose Fourier spectrum reproduces Penrose‑tiling order, providing a dense, non‑redundant set of resonant modes that can be dynamically reconfigured via external perturbations. The resulting adaptive comb serves as a hardware‑level reservoir for neuromorphic systems, enabling real‑time learning and signal processing through geometrically encoded quasicrystalline dynamics. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Quasicrystal Structures and Properties
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