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 Experiment Videos

Probabilistic prediction in scale-free networks: diameter changes.

J-H Kim1, K-I Goh, B Kahng

  • 1School of Physics and Center for Theoretical Physics, Seoul National University, Seoul 151-747, Korea.

Physical Review Letters
|August 9, 2003
PubMed
Summary

Network changes after vertex deletion are diverse but predictable probabilistically. Scale-free networks show diameter changes with algebraic decay, with a robust exponent around 2.2, except for networks like the Internet.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Heterogeneous network topology induces the Widom line.

Physical review. E·2026
Same author

Entropy-induced phase transitions in a hidden Potts model.

Physical review. E·2024
Same author

Exploring nonlinear dynamics and network structures in Kuramoto systems using machine learning approaches.

Chaos (Woodbury, N.Y.)·2023
Same author

Prediction and mitigation of nonlocal cascading failures using graph neural networks.

Chaos (Woodbury, N.Y.)·2023
Same author

Extended mean-field approach for chimera states in random complex networks.

Chaos (Woodbury, N.Y.)·2022
Same author

COVID-19 epidemic under the K-quarantine model: Network approach.

Chaos, solitons, and fractals·2022

Area of Science:

  • Complex Systems Science
  • Network Science
  • Statistical Physics

Background:

  • Complex systems exhibit unpredictable responses to small perturbations.
  • Understanding network robustness is crucial for real-world applications.
  • Scale-free networks are common models for complex systems.

Purpose of the Study:

  • To investigate the probabilistic prediction of network responses.
  • To analyze diameter changes in scale-free networks upon single vertex deletion.
  • To determine the robustness and characteristics of these changes.

Main Methods:

  • Analysis of diameter changes in various in silico and real-world scale-free networks.
  • Statistical analysis of the distribution of diameter changes.

Related Experiment Videos

  • Identification of the exponent (zeta) in the algebraic decay of change distribution.

    • Main Results:

    • Diameter changes in scale-free networks are diverse and follow an algebraic decay.
    • The decay exponent (zeta) is approximately 2.2(1) for most scale-free networks.
    • A distinct network type, including the Internet, shows zeta approximately 1.7(1).

    Conclusions:

    • The probabilistic approach effectively predicts diverse network responses.
    • Scale-free network diameter changes exhibit a robust, predictable decay pattern.
    • Network topology influences the specific decay exponent, highlighting distinct network behaviors.