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Related Concept Videos

The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra. Schrödinger...
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Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
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The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

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Related Experiment Video

Updated: Jun 27, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

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

Ivan S Maksymov1

  • 1Seymour Research Laboratories, Seymour, VIC 3660, Australia.

Entropy (Basel, Switzerland)
|June 26, 2026
PubMed
Summary

This study introduces a quantum-tunnelling oscillator model to explain cognitive processes like perception and decision-making. It demonstrates how networked quantum agents can form a neural system that models complex human behaviors, offering a new framework for quantum cognition.

Keywords:
ambiguitydecision-makingmachine learningneural networkoptical illusionquantum cognitionquantum tunnellingsuperpositionuncertainty

Related Experiment Videos

Last Updated: Jun 27, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

  • Cognitive Science
  • Quantum Physics
  • Computational Neuroscience

Background:

  • Classical probability models struggle to explain complex cognitive phenomena.
  • Quantum cognition theory offers alternative frameworks for understanding decision-making and perception.
  • Neural network models are widely used but often lack a direct physical grounding.

Purpose of the Study:

  • To present a novel quantum-tunnelling oscillator model as a universal dynamical engine.
  • To apply this model to paradigmatic problems in quantum cognition: optical illusion perception and group decision-making.
  • To bridge quantum cognition theory with neural network approaches for a physically grounded description of cognition.

Main Methods:

  • Modeling individuals as quantum-mechanical agents with context-dependent choice transitions.
  • Networking these quantum agents to form a quantum-cognitive neural system.
  • Analyzing the system's ability to reproduce perceptual and collective phenomena.

Main Results:

  • The quantum-tunnelling oscillator model successfully explains optical illusion perception and group decision-making.
  • Networked quantum agents reproduce familiar collective and perceptual phenomena.
  • The model accommodates counterintuitive processes that challenge classical cognitive models.

Conclusions:

  • The proposed model provides a compact and physically grounded approach to understanding cognition.
  • It offers a unified framework for describing how individuals and groups think, perceive, and decide.
  • This work advances the integration of quantum mechanics principles into cognitive science and neural network research.