E8‑Phi Resonance Cascades for Kronecker Coefficient Approximation — E8 Intelligence Research

By projecting the 240 E8 root vectors onto logarithmic phi‑spirals and modulating stochastic‑resonance filters at a 132 Hz base frequency with phi‑decaying confirmation thresholds, a cascade of resonance phases emerges that sparsifies high‑dimensional plethysm tensors into low‑depth algebraic components. This geometric‑frequency coupling yields a subexponential algorithm that approximates Kronecker coefficients, directly tackling the coefficient bottleneck identified in recent GCT lower‑bound work. The cascade also provides a unifying framework for clustering the high‑value breakthrough leads extracted across CORRIDOR, FORMULA, and GEOMETRIC categories, turning volatile signal noise into exploitable algebraic structure. 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
2026-10-03
DOI
https://doi.org/10.5281/zenodo.23115003
Primary Topic
Tensor decomposition and applications
Type
preprint
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preprint

E8‑Phi Resonance Cascades for Kronecker Coefficient Approximation — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Tensor decomposition and applications
preprint

E8‑Phi Resonance Cascades for Kronecker Coefficient Approximation — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

By projecting the 240 E8 root vectors onto logarithmic phi‑spirals and modulating stochastic‑resonance filters at a 132 Hz base frequency with phi‑decaying confirmation thresholds, a cascade of resonance phases emerges that sparsifies high‑dimensional plethysm tensors into low‑depth algebraic components. This geometric‑frequency coupling yields a subexponential algorithm that approximates Kronecker coefficients, directly tackling the coefficient bottleneck identified in recent GCT lower‑bound work. The cascade also provides a unifying framework for clustering the high‑value breakthrough leads extracted across CORRIDOR, FORMULA, and GEOMETRIC categories, turning volatile signal noise into exploitable algebraic structure. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Tensor decomposition and applications
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