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

The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

61.4K
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.
61.4K
Network Function of a Circuit01:25

Network Function of a Circuit

995
Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
995
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

3.4K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
3.4K
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

1.3K
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?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the...
1.3K
The Entropy as a State Function01:14

The Entropy as a State Function

70
Consider an arbitrary process that moves between two specific states (A and B) in a cyclic manner. This process is reversible and broken down into smaller parts that each follow a Carnot cycle. A Carnot cycle has two isothermal (constant temperature) processes. During these processes, the ratio of the amount of heat transferred to their respective temperature remains constant. The other two processes in the Carnot cycle are also reversible but adiabatic, which means they occur without any heat...
70
Reynolds Transport Theorem01:24

Reynolds Transport Theorem

2.1K
The Reynolds transport theorem provides a framework to relate the time rate of change of an extensive property within a system to that in a control volume, which is crucial for analyzing fluid dynamics. Extensive properties, such as mass, velocity, acceleration, temperature, and momentum, can be expressed in terms of the mass of a fluid portion. These properties are called extensive because they depend on the system's size, while intensive properties are their corresponding values per unit...
2.1K

You might also read

Related Articles

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

Sort by
Same author

Interlinks enhance quantum transport on multilayer networks.

Physical review. E·2026
Same author

Number of Local Minima in Discrete-Time Fractional Brownian Motion.

Physical review letters·2026
Same author

Visitation Dynamics of d-Dimensional Fractional Brownian Motion.

Physical review letters·2025
Same author

Evidence and quantification of memory effects in competitive first-passage events.

Science advances·2025
Same author

Viscoelastic relaxation of random scale-free copolymer networks.

Physical review. E·2025
Same author

Full-record statistics of one-dimensional random walks.

Physical review. E·2024

Related Experiment Video

Updated: Mar 24, 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

1.2K

Complex quantum networks: From universal breakdown to optimal transport.

Oliver Mülken1, Maxim Dolgushev1, Mircea Galiceanu2,3

  • 1Physikalisches Institut, Universität Freiburg, Hermann-Herder-Strasse 3, D-79104 Freiburg, Germany.

Physical Review. E
|March 18, 2016
PubMed
Summary

We investigated quantum network transport efficiency. Optimal transport occurs in ringlike networks, while complete-graph networks show transport breakdown, tunable via small-world modifications.

More Related Videos

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
05:39

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

Published on: August 2, 2019

10.5K
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

9.8K

Related Experiment Videos

Last Updated: Mar 24, 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

1.2K
Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
05:39

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

Published on: August 2, 2019

10.5K
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

9.8K

Area of Science:

  • Quantum physics
  • Complex networks
  • Transport phenomena

Background:

  • Understanding excitation transport in quantum networks is crucial for quantum technologies.
  • Network topology significantly influences transport efficiency.
  • Loops in quantum networks can impede or facilitate excitation transport.

Purpose of the Study:

  • To investigate the impact of network topology, specifically loops, on the efficiency of excitation transport in complex quantum networks.
  • To identify conditions that lead to optimal transport versus transport breakdown.
  • To explore methods for controlling transport efficiency through network modifications.

Main Methods:

  • Theoretical analysis based on the spectral properties of the network's Hamiltonian.
  • Numerical Monte Carlo simulations.
  • Modeling sequentially growing networks with varying subgraph topologies (complete-graph-like vs. ringlike).
  • Implementing a small-world procedure to reduce loops.

Main Results:

  • Sequentially growing networks with complete-graph-like subgraphs exhibit a complete breakdown of transport.
  • Ringlike sequential subgraphs facilitate optimal transport.
  • Systematically reducing loops in complete-graph-like networks via a small-world procedure triggers a transition to optimal transport.
  • Scale-free size distribution of subgraphs and small-world transitions were observed in simulations.

Conclusions:

  • Network topology, particularly the presence and arrangement of loops, critically determines excitation transport efficiency.
  • Optimal transport can be achieved by modifying network structure, such as reducing loops in complete-graph-like networks.
  • Spectral properties of the Hamiltonian provide a theoretical basis for understanding these transport phenomena.