IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v362y2019ic17.html
   My bibliography  Save this article

“Melting” of complex networks. A mathematical model of complex networks resilience to external stress

Author

Listed:
  • Alalwan, Najlaa
  • Arenas, Alex
  • Estrada, Ernesto

Abstract

Complex networks are the representative graphs of interactions in many complex systems. Usually, these interactions are abstractions of the communication/diffusion channels between the units of the system. Recently we have proved analytically the existence of a universal phase transition in the communicability–a topological descriptor that reveals the efficiency of the network functionality in terms of these diffusive paths–of every simple network. This transition resembles the melting process occurring in solids. Here we study computationally this universal melting process in a large dataset of real-world networks and observe that the rate of melting of graphs changes either as an exponential or as a power-law with the inverse temperature representing the external stress to which the system is submitted to. At the local level we discover that the main driver for node melting is the eigenvector centrality of the corresponding node, particularly when the critical value of the inverse temperature approaches zero. That is, the most central nodes are the ones most at risk of triggering the melt down of the global network. These universal results can be used to sheds light on many dynamical diffusive-like processes on networks that present transitions as traffic jams, communication lost or failure cascades.

Suggested Citation

  • Alalwan, Najlaa & Arenas, Alex & Estrada, Ernesto, 2019. "“Melting” of complex networks. A mathematical model of complex networks resilience to external stress," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    • Handle: RePEc:eee:apmaco:v:362:y:2019:i:c:17
    DOI: 10.1016/j.amc.2019.124579
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300319305715
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2019.124579?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Douglas J. LaCount & Marissa Vignali & Rakesh Chettier & Amit Phansalkar & Russell Bell & Jay R. Hesselberth & Lori W. Schoenfeld & Irene Ota & Sudhir Sahasrabudhe & Cornelia Kurschner & Stanley Field, 2005. "A protein interaction network of the malaria parasite Plasmodium falciparum," Nature, Nature, vol. 438(7064), pages 103-107, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wu, Yipeng & Chen, Zhilong & Zhao, Xudong & Gong, Huadong & Su, Xiaochao & Chen, Yicun, 2021. "Propagation model of cascading failure based on discrete dynamical system," Reliability Engineering and System Safety, Elsevier, vol. 209(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Prajwal Devkota & Matt C Danzi & Stefan Wuchty, 2018. "Beyond degree and betweenness centrality: Alternative topological measures to predict viral targets," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-14, May.
    2. Luis P Fernandes & Alessia Annibale & Jens Kleinjung & Anthony C C Coolen & Franca Fraternali, 2010. "Protein Networks Reveal Detection Bias and Species Consistency When Analysed by Information-Theoretic Methods," PLOS ONE, Public Library of Science, vol. 5(8), pages 1-14, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:362:y:2019:i:c:17. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.