E8‑Phi Resonant Lattice as Holographic Quantum Memory for Neuromorphic AI — E8 Intelligence Research

The synchronized 132 Hz phi‑phase offsets of the 240 E8 root vectors create a dynamic holographic substrate whose contraction flow compresses information into a self‑referencing manifold. By mapping synaptic activation patterns onto this phi‑weighted lattice, neural synchrony is amplified and stored as stable interference nodes, forming a quantum‑enhanced memory that self‑organizes via E8's hyperbolic geometry. This establishes a scalable principle for ultra‑dense, phase‑coherent data encoding that bridges high‑frequency lattice dynamics, golden‑ratio phase locking, and neuromorphic computation. 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
2026-09-29
DOI
https://doi.org/10.5281/zenodo.23030991
Primary Topic
Neural Networks and Reservoir Computing
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
preprint

E8‑Phi Resonant Lattice as Holographic Quantum Memory for Neuromorphic AI — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Reservoir Computing
preprint

E8‑Phi Resonant Lattice as Holographic Quantum Memory for Neuromorphic AI — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

The synchronized 132 Hz phi‑phase offsets of the 240 E8 root vectors create a dynamic holographic substrate whose contraction flow compresses information into a self‑referencing manifold. By mapping synaptic activation patterns onto this phi‑weighted lattice, neural synchrony is amplified and stored as stable interference nodes, forming a quantum‑enhanced memory that self‑organizes via E8's hyperbolic geometry. This establishes a scalable principle for ultra‑dense, phase‑coherent data encoding that bridges high‑frequency lattice dynamics, golden‑ratio phase locking, and neuromorphic computation. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Reservoir Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.