IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v509y2026ics0096300325003923.html
   My bibliography  Save this article

Closeness spectra and structural uniqueness of special graph classes

Author

Listed:
  • Farhad, Qaisar
  • Hussain, Mumtaz
  • Xu, Shou-Jun

Abstract

For a graph G with vertex set V(G) and edge set E(G). Let d(u,v) be the distance between vertices u and v. The closeness matrix of a graph G is a symmetric matrix, where each entry cG(u,v) is defined as cG(u,v)=2−d(u,v) for u≠v, and cG(u,v)=0, if u=v. In the present study, we investigate the closeness spectra of connected graphs and inquire whether specific graph classes may be distinguished by their closeness eigenvalues. We inspect the tree T3,n−3, the path Pn, the complete graph Kn, and the join graph (P1∪P3)∨Kn−4‾. Applying careful spectral computation, we demonstrate that such graphs are uniquely specified by their closeness spectra. Additionally, we confirm that the tree T3,n−3 achieves the second-smallest closeness eigenvalue among trees of diameter 3. Our findings emphasize the importance of closeness matrices in spectral graph theory and lead to more clarity of the relationship between the structure of graphs and its spectrum.

Suggested Citation

  • Farhad, Qaisar & Hussain, Mumtaz & Xu, Shou-Jun, 2026. "Closeness spectra and structural uniqueness of special graph classes," Applied Mathematics and Computation, Elsevier, vol. 509(C).
  • Handle: RePEc:eee:apmaco:v:509:y:2026:i:c:s0096300325003923
    DOI: 10.1016/j.amc.2025.129666
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300325003923
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2025.129666?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:509:y:2026:i:c:s0096300325003923. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.