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

Network Function of a Circuit01:25

Network Function of a Circuit

332
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.
332
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

101
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
101
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.6K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.6K
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

2.6K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
2.6K
Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

4.5K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
4.5K
Poisson Probability Distribution01:09

Poisson Probability Distribution

8.3K
A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
8.3K

You might also read

Related Articles

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

Sort by
Same author

Identifiability limits and deep-learning-assisted reconstruction of rotational density matrices for symmetric-top molecules.

The Journal of chemical physics·2026
Same author

Safety and hemodynamic efficacy of the LVIS stent in the endovascular treatment of intracranial wide-necked aneurysms: a single-center retrospective study.

Chinese neurosurgical journal·2026
Same author

Sensor-Driven Short-Term Forecasting on the Metropolitan LA Traffic Dataset: A Comparative Study for Multi-Step Prediction.

Sensors (Basel, Switzerland)·2026
Same author

<i>Schistosoma japonicum</i> Worms Alter the miRNA Expression Profile of Hepatic Stellate Cells with Potential Implications for Liver Fibrosis and Hepatocellular Carcinoma.

Tropical medicine and infectious disease·2026
Same author

Training and transfer effect of evoked brain responses by brain-computer interaction.

IEEE transactions on bio-medical engineering·2026
Same author

Immunosenescence and Bone Homeostasis: From Mechanisms of Homeostasis Disruption to Therapeutic Opportunities in Age-Related Skeletal Disorders.

International journal of molecular sciences·2026

Related Experiment Video

Updated: Jul 30, 2025

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

611

Cost-Optimization-Based Quantum Key Distribution over Quantum Key Pool Optical Networks.

Jie Jia1,2, Bowen Dong1,2, Le Kang1,2

  • 1Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices, Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials, South China Normal University, Guangzhou 510006, China.

Entropy (Basel, Switzerland)
|May 16, 2023
PubMed
Summary

This study introduces an improved Measurement-Device-Independent-Quantum Key Distribution (MDI-QKD) network design. The new architecture significantly cuts costs for large-scale quantum key distribution networks.

Keywords:
cost optimizationmeasurement-device-independent quantum key distributionoptical networksquantum key pooltrusted and untrusted relay

More Related Videos

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.9K
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

14.6K

Related Experiment Videos

Last Updated: Jul 30, 2025

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

611
Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.9K
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

14.6K

Area of Science:

  • Quantum Information Science
  • Network Security
  • Applied Physics

Background:

  • Measurement-Device-Independent-Quantum Key Distribution (MDI-QKD) enhances secure communication distances.
  • Hybrid-Trusted and Untrusted Relay (HTUR) strategies are crucial for cost-effective, large-scale Quantum Key Distribution (QKD) networks.
  • Optimizing QKD network architecture is essential for balancing performance and deployment expenses.

Purpose of the Study:

  • To propose an improved QKD network architecture integrating MDI-QKD with HTUR.
  • To reduce the number of required QKD transmitters and incorporate a quantum key pool (QKP).
  • To address the cost optimization challenge in deploying large-scale QKD networks.

Main Methods:

  • Development of a novel Hybrid-QKD-Network-Cost (HQNC) heuristic algorithm for cost optimization.
  • Simulation-based analysis of the proposed QKD network architecture.
  • Comparative cost analysis against existing QKD network deployment strategies.

Main Results:

  • The proposed scheme significantly simplifies QKD network architecture.
  • Incorporation of a quantum key pool (QKP) further enhances network efficiency.
  • Simulations demonstrated potential cost savings exceeding 50% and reaching 90% in specific scenarios.

Conclusions:

  • The improved MDI-QKD network architecture offers substantial cost reductions for large-scale deployments.
  • The HQNC algorithm effectively optimizes QKD network costs.
  • This research provides a viable strategy for more economical and scalable quantum communication networks.