Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Structures of Solids02:22

Structures of Solids

14.0K
Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
14.0K
The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

41.9K
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.
41.9K
Electronic Structure of Atoms02:28

Electronic Structure of Atoms

20.9K

An atom comprises protons and neutrons, which are contained inside the dense, central core called the nucleus, with electrons present around the nucleus. Taking into account the wave–particle duality of electrons and the uncertainty in position around the nucleus, quantum mechanics provides a more accurate model for the atomic structure. It describes atomic orbitals as the regions around the nucleus where electrons of discrete energy exist, characterized by four quantum...
20.9K
Classification of Systems-I01:26

Classification of Systems-I

168
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
168
Quantum Numbers02:43

Quantum Numbers

34.2K
It is said that the energy of an electron in an atom is quantized; that is, it can be equal only to certain specific values and can jump from one energy level to another but not transition smoothly or stay between these levels.
34.2K
Lattice Centering and Coordination Number02:33

Lattice Centering and Coordination Number

9.5K
The structure of a crystalline solid, whether a metal or not, is best described by considering its simplest repeating unit, which is referred to as its unit cell. The unit cell consists of lattice points that represent the locations of atoms or ions. The entire structure then consists of this unit cell repeating in three dimensions. The three different types of unit cells present in the cubic lattice are illustrated in Figure 1.
Types of Unit Cells
Imagine taking a large number of identical...
9.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Quantum Error Mitigation in Optimized Circuits for Particle-Density Correlations in Real-Time Dynamics of the Schwinger Model.

Entropy (Basel, Switzerland)·2025
Same author

Thermodynamic Efficiency of Interactions in Self-Organizing Systems.

Entropy (Basel, Switzerland)·2021
Same author

On critical dynamics and thermodynamic efficiency of urban transformations.

Royal Society open science·2018
Same author

Thermodynamic efficiency of contagions: a statistical mechanical analysis of the SIS epidemic model.

Interface focus·2018
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: May 31, 2025

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
09:23

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

Published on: May 30, 2014

14.4K

Density Classification with Non-Unitary Quantum Cellular Automata.

Elisabeth Wagner1,2, Federico Dell'Anna3,4, Ramil Nigmatullin1,5

  • 1School of Mathematical and Physical Sciences, Macquarie University, Sydney, NSW 2109, Australia.

Entropy (Basel, Switzerland)
|January 24, 2025
PubMed
Summary
This summary is machine-generated.

This study explores quantum cellular automata for density classification. Quantum models achieve fixed-point solutions efficiently, with one solving the majority voting problem in linear time.

Keywords:
density classificationmajority problemopen quantum systemsquantum cellular automataquantum computingquantum simulation

More Related Videos

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

480
Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

8.9K

Related Experiment Videos

Last Updated: May 31, 2025

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
09:23

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

Published on: May 30, 2014

14.4K
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

480
Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

8.9K

Area of Science:

  • Quantum Information Science
  • Computational Physics
  • Complex Systems

Background:

  • Density Classification (DC) is a fundamental computation mapping global density to local density.
  • Cellular automata (CA) are widely used models for studying complex systems.
  • Quantum Cellular Automata (QCAs) offer a quantum mechanical framework for computation.

Purpose of the Study:

  • To investigate the application of one-dimensional non-unitary quantum cellular automata (QCAs) to the density classification task.
  • To develop and analyze QCAs that preserve number density and perform majority voting.
  • To explore quantum features and interaction types within QCA models for DC.

Main Methods:

  • Development of two number-preserving QCAs, one based on a classical probabilistic automaton and a novel quantum model.
  • Analysis of QCA dynamics, including continuous-time Lindblad dynamics.
  • Introduction of a hybrid QCA rule combining discrete-time and continuous-time three-body interactions.

Main Results:

  • Number-preserving QCAs achieve fixed-point solutions with time complexity scaling quadratically with system size.
  • A novel two-body interaction QCA demonstrates additional quantum features.
  • A hybrid three-body interaction QCA solves the majority voting problem with linear time complexity.

Conclusions:

  • Non-unitary QCAs provide effective models for solving the density classification task.
  • Quantum approaches offer advantages in computational efficiency compared to classical counterparts.
  • The study highlights the potential of QCAs for exploring quantum computation and complex system dynamics.