Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Condensed Matter > Disordered Systems and Neural Networks

arXiv:cond-mat/0306625 (cond-mat)
[Submitted on 24 Jun 2003 (v1), last revised 6 Jul 2003 (this version, v2)]

Title:Heterogeneity in oscillator networks: Are smaller worlds easier to synchronize?

Authors:Takashi Nishikawa, Adilson E. Motter, Ying-Cheng Lai, Frank C. Hoppensteadt
View PDF
Abstract: Small-world and scale-free networks are known to be more easily synchronized than regular lattices, which is usually attributed to the smaller network distance between oscillators. Surprisingly, we find that networks with a homogeneous distribution of connectivity are more synchronizable than heterogeneous ones, even though the average network distance is larger. We present numerical computations and analytical estimates on synchronizability of the network in terms of its heterogeneity parameters. Our results suggest that some degree of homogeneity is expected in naturally evolved structures, such as neural networks, where synchronizability is desirable.
Comments: 4 pages, 2 figures, REVTeX4
Subjects: Disordered Systems and Neural Networks (cond-mat.dis-nn); Mathematical Physics (math-ph); Chaotic Dynamics (nlin.CD); Neurons and Cognition (q-bio.NC)
Cite as: arXiv:cond-mat/0306625 [cond-mat.dis-nn]
  (or arXiv:cond-mat/0306625v2 [cond-mat.dis-nn] for this version)
  https://doi.org/10.48550/arXiv.cond-mat/0306625
Journal reference: Phys. Rev. Lett. 91, 014101 (2003)
Related DOI: https://doi.org/10.1103/PhysRevLett.91.014101

Submission history

From: Takashi Nishikawa [view email]
[v1] Tue, 24 Jun 2003 22:39:05 UTC (19 KB)
[v2] Sun, 6 Jul 2003 21:39:13 UTC (19 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
cond-mat.dis-nn
< prev   |   next >
new | recent | 2003-06

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender (What is IArxiv?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)