Quantum-Tunnelling Oscillators for Cognitive Modelling and Neural Computation: Foundations, Machine-Vision Realisation and Applications

TL;DR

This paper introduces a quantum-tunnelling oscillator model as a universal engine for quantum cognition, capable of simulating perception and decision-making processes in individuals and groups.

Contribution

It bridges quantum cognition theory and neural networks, providing a novel, physically grounded framework for modeling complex cognitive phenomena.

Findings

Reproduces collective and perceptual phenomena accurately

Accommodates counterintuitive cognitive processes

Models individuals and groups as quantum-mechanical agents

Abstract

I present a quantum-tunnelling oscillator model as a universal dynamical engine for two paradigmatic problems in quantum cognition theory -- optical illusion perception and group decision making -- where individuals are treated as quantum-mechanical agents whose choices shift through context-dependent transitions rather than simple probabilities. I show that, when networked together, these units form a quantum-cognitive neural system that reproduces familiar collective and perceptual phenomena while naturally accommodating counterintuitive processes that challenge classical models. Bridging ideas from quantum cognition theory and neural networks, this approach offers a compact, physically grounded way to describe how real individuals and groups think, perceive and decide.