quantum-tunnelling-oscillators-cognition

name	quantum-tunnelling-oscillators-cognition
description	Quantum-tunnelling oscillator model as universal dynamical engine for quantum cognition — models optical illusion perception and group decision making as quantum-mechanical agents with context-dependent state transitions, networked into quantum-cognitive neural systems. Activation: quantum cognition, quantum tunnelling oscillators, optical illusion perception, group decision making, quantum-cognitive neural systems, context-dependent transitions, 量子认知振荡器, 量子隧穿, 群体决策
metadata	{"arxiv_id":"2604.03940","published":"2026-04-05","authors":"Ivan S. Maksymov"}

Quantum-Tunnelling Oscillators for Cognition

Description

Universal dynamical engine for quantum cognition theory — models individuals as quantum-mechanical agents whose choices shift through context-dependent transitions rather than classical probabilities. Networked oscillators form quantum-cognitive neural systems reproducing collective and perceptual phenomena.

Core Concepts

Quantum-Tunnelling Oscillator (QTO) Model

• Individual agents modeled as quantum oscillators with tunnelling between cognitive states
• State transitions governed by quantum amplitudes, not classical probabilities
• Context-dependence emerges naturally from superposition and interference

Application Domains

1. Optical illusion perception: Bistable perception explained as quantum superposition of interpretations
2. Group decision making: Collective behavior from networked QTOs with inter-agent coupling
3. Counterintuitive processes: Naturally handles phenomena challenging classical probabilistic models

Networked Quantum-Cognitive Systems

• Individual QTOs coupled into networks form collective cognitive dynamics
• Reproduces familiar collective phenomena from individual quantum-level dynamics
• Compact, physically grounded framework for thinking, perception, and decision processes

Usage Patterns

Pattern 1: Bistable Perception Modeling

For modeling ambiguous stimuli perception:

1. Map each interpretation to a quantum oscillator state
2. Model perceptual switching as quantum tunnelling between states
3. Context effects enter as perturbation Hamiltonians

Pattern 2: Group Decision Dynamics

For modeling collective decision processes:

1. Each individual = one QTO unit
2. Inter-agent influence = coupling term in Hamiltonian
3. Collective phenomena emerge from network dynamics
4. Context shifts = time-dependent perturbations

Methodology

1. Define cognitive state space as Hilbert space of oscillator eigenstates
2. Construct Hamiltonian with tunnelling terms between relevant states
3. Add context-dependent perturbation terms
4. Solve time-dependent Schrödinger equation for state evolution
5. Extract observable predictions from measurement probabilities

Activation Keywords

• quantum tunnelling oscillator cognition
• quantum-cognitive neural system
• optical illusion quantum model
• quantum group decision making
• bistable perception quantum
• context-dependent quantum transitions
• 量子隧穿振荡器认知
• 量子认知神经网络
• 群体决策量子模型

Pitfalls

• QTO model is a metaphorical/engineering model — not claiming literal quantum effects in biological neurons
• Parameters (tunnelling rates, coupling strengths) must be calibrated empirically
• Classical limit (large decoherence) should recover standard probabilistic models
• Distinguish from GKSL open-system approaches — QTO uses closed-system Hamiltonian dynamics