From Carbon Nanotubes to Cognitive Emergence_ Rewriting Chirality Vector Mapping for the Age of Coherence

Main article Abstract: This paper introduces a complete epistemic reorientation of chirality—from its traditional role in material science (e.g., carbon nanotube classification) to a time-evolving resonance architecture that governs intelligence, perception, and emergent cognition. Using the CODES framework (Chirality of Dynamic Emergent Systems), it redefines chirality vectors (C_n(t) = [A_n · sin(φ_n(t))] · P_n) as phase-based directional operators, replacing probabilistic logic with deterministic phase alignment. We introduce Coherence Score (CS) and Coherence Score Threshold (CST) as inference mechanisms native to structured resonance rather than stochastic inference. This formalism grounds the design of the Resonance Intelligence Core (RIC)—a non-stochastic AGI substrate that operates through phase-lock resolution rather than sampling or backpropagation. The document rigorously contrasts Bayesian softmax inference with CST-based resonance lock, integrates examples across physics, biology, and cognition, and positions CODES chirality as the ontological substrate of intelligent behavior. Appendices provide classification tables, algorithmic logic, and a glossary to support implementation.