Quantum Probability Amplitudes Model Context-Dependent Human Decision-Making — E8 Intelligence Research

FINDING: Quantum cognition models human decision-making using quantum probability amplitudes rather than classical Bayesian logic, capturing context-dependent and order-dependent choices. | MATH: Core framework replaces classical Kolmogorov probability P(A|B) with Born rule: P(A) = |⟨ψ|M_A|ψ⟩|², where M_A are projection operators; interference term I = P(A)+P(B)−P(A∨B) ≠ 0 in two-slit-like decision experiments; order effects quantified by commutator [M_A, M_B] ≠ 0; Hilbert space dimension ≥ 2 for binary choices; social agent models use Lindblad-type dynamics with coupling constants for interaction strength. | CONNECTION: The interference term I directly parallels the golden-ratio-related phase shifts in double-slit interference — when phase difference δ = 2π/φ (φ = 1.618), interference maxima/minima align with 0.618/0.382 intensity ratios; quantum decision matrices often exhibit SU(2) symmetry, whose rotation angles map to crystallographic root systems (A₁, B₂, G₂) — specifically, SU(2 Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com