| 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
- Optical illusion perception: Bistable perception explained as quantum superposition of interpretations
- Group decision making: Collective behavior from networked QTOs with inter-agent coupling
- 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:
- Map each interpretation to a quantum oscillator state
- Model perceptual switching as quantum tunnelling between states
- Context effects enter as perturbation Hamiltonians
Pattern 2: Group Decision Dynamics
For modeling collective decision processes:
- Each individual = one QTO unit
- Inter-agent influence = coupling term in Hamiltonian
- Collective phenomena emerge from network dynamics
- Context shifts = time-dependent perturbations
Methodology
- Define cognitive state space as Hilbert space of oscillator eigenstates
- Construct Hamiltonian with tunnelling terms between relevant states
- Add context-dependent perturbation terms
- Solve time-dependent Schrödinger equation for state evolution
- 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
