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Theoretical model demonstrates self-correcting topological memory in neural networks via golden-ratio phase shifts, suggesting fault-tolerant computing architectures.
The φ-scaled coupling of the 240 E8 root vectors defines a discrete Fibonacci-phyllotaxis sequence within the neural synchrony regime, mapping Clifford-graded anyonic braid patterns directly onto information processing manifolds. By synchronizing 132 Hz stochastic resonances with Fibonacci-ordered periodic orbits, the system establishes a self-correcting topological memory substrate that prevents error propagation through golden-ratio-scaled phase shifts. This principle enables a new class of "Fibonacci-stabilized" neural networks where information is encoded in the braiding of quasi-particles within a geometric E8 lattice. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
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Andrew Stewart Caldin (2026) studied this question.
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