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

Adaptability and "intermediate phase" in randomly connected networks.

J Barré1, A R Bishop, T Lookman

  • 1Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA. jbarre@cnls.lanl.gov

Physical Review Letters
|August 11, 2005
PubMed
Summary
This summary is machine-generated.

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

Patterns and Stability of Coupled Multi-Stable Nonlinear Oscillators.

Chaos, solitons, and fractals·2023
Same author

Measurement and memory in the periodically driven complex Ginzburg-Landau equation.

Physical review. E·2022
Same author

Bubble lifetimes in DNA gene promoters and their mutations affecting transcription.

The Journal of chemical physics·2021
Same author

Distributions of bubble lifetimes and bubble lengths in DNA.

Physical review. E·2021
Same author

Speed-of-light pulses in the massless nonlinear Dirac equation with a potential.

Physical review. E·2018
Same author

Variational approach to studying solitary waves in the nonlinear Schrödinger equation with complex potentials.

Physical review. E·2016
Same journal

Erratum: Bacterial Turbulence at Compressible Fluid Interfaces [Phys. Rev. Lett. 136, 138301 (2026)].

Physical review letters·2026
Same journal

Unveiling Light-Quark Yukawa Flavor Structure via Dihadron Fragmentation at Lepton Colliders.

Physical review letters·2026
Same journal

Adaptable Route to Fast Coherent State Transport via Bang-Bang-Bang Protocols.

Physical review letters·2026
Same journal

Topological Transition and Emergence of Elasticity of Dislocation in Skyrmion Lattice: Beyond Kittel's Magnetic-Polar Analogy.

Physical review letters·2026
Same journal

Pound-Drever-Hall Method for Superconducting-Qubit Readout.

Physical review letters·2026
Same journal

Coupling a ^{73}Ge Nuclear Spin to an Electrostatically Defined Quantum Dot in Silicon.

Physical review letters·2026
See all related articles

We developed a model to understand how random networks change from floppy to rigid, revealing a self-adaptive phase that reduces stress. This finding has implications for computational problems like vertex cover.

Area of Science:

  • Statistical Mechanics
  • Network Science
  • Computational Complexity

Background:

  • Random networks exhibit diverse mechanical properties.
  • Understanding transitions between floppy and rigid states is crucial for material science and network analysis.
  • Self-adaptation mechanisms in physical systems are of significant interest.

Purpose of the Study:

  • To analytically characterize the floppy to rigid transition in random bond networks.
  • To identify and describe an associated self-adaptive intermediate phase.
  • To explore potential applications in computational problems.

Main Methods:

  • Development of a simple analytical model for random bond networks.
  • Characterization of network transitions and intermediate phases.

Related Experiment Videos

  • Computational simulations to verify the model's predictions.

    • Main Results:

    • Analytical characterization of a floppy to rigid transition.
    • Identification of a self-adaptive intermediate phase where networks reduce stress.
    • Simulations confirmed the model's predictions of network behavior.

    Conclusions:

    • The study provides a novel model for understanding network transitions.
    • The self-adaptive phase offers insights into stress reduction mechanisms.
    • The findings suggest potential applications in solving complex computational problems such as vertex cover and K-satisfiability.