IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v199y2025ip3s0960077925009105.html

Analytical study of resistance distance and Kirchhoff index under edge perturbations in weighted graphs

Author

Listed:
  • Sardar, Muhammad Shoaib

Abstract

Let G=(V,E) be a connected, undirected graph with unit edge weights. Let G̃ be the graph obtained by perturbing the weight of a single edge [u,v]∈E by an amount Δwuv, so that its new weight becomes 1+Δwuv, while all other edge weights remain unchanged. In this paper, we analyze the effect of such localized edge perturbations on the resistance distance and Kirchhoff index of G̃, using matrix perturbation theory and the Woodbury identity. We derive closed-form expressions for the perturbed resistance distance r̃ij and perturbed Kirchhoff index Kf(G̃), providing analytical insight into the global impact of local structural changes. Through extremal analysis on complete and path graphs, we establish tight bounds for Kf(G̃) under single-edge perturbations and derive first-order sensitivity approximations to quantify the influence of individual edge weights. Building on this foundation, we propose the Max-Kirchhoff Impact Edge Detection (MKIED) technique to locate edges that have the greatest influence on the Kirchhoff index. Experiments on real-world networks, including Facebook, the Karate Club, and Les Miserables, illustrate the method’s efficacy in identifying structurally significant edges, frequently correlating to bridges or hub-hub connections. The results underscore the Kirchhoff index as an effective instrument for assessing structural vulnerability in complex networks.

Suggested Citation

  • Sardar, Muhammad Shoaib, 2025. "Analytical study of resistance distance and Kirchhoff index under edge perturbations in weighted graphs," Chaos, Solitons & Fractals, Elsevier, vol. 199(P3).
  • Handle: RePEc:eee:chsofr:v:199:y:2025:i:p3:s0960077925009105
    DOI: 10.1016/j.chaos.2025.116897
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077925009105
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2025.116897?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.

    References listed on IDEAS

    as
    1. Jiang, Zhuozhuo & Yan, Weigen, 2017. "Resistance between two nodes of a ring network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 21-26.
    2. R. B. Bapat & Somit Gupta, 2010. "Resistance distance in wheels and fans," Indian Journal of Pure and Applied Mathematics, Springer, vol. 41(1), pages 1-13, February.
    3. Sardar, Muhammad Shoaib & Pan, Xiang-Feng & Xu, Si-Ao, 2020. "Computation of resistance distance and Kirchhoff index of the two classes of silicate networks," Applied Mathematics and Computation, Elsevier, vol. 381(C).
    4. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    5. Sardar, Muhammad Shoaib & Pan, Xiang-Feng & Xu, Shou-Jun, 2024. "Computation of the resistance distance and the Kirchhoff index for the two types of claw-free cubic graphs," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    Full references (including those not matched with items on IDEAS)

    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. Sardar, Muhammad Shoaib & Pan, Xiang-Feng & Xu, Shou-Jun, 2024. "Computation of the resistance distance and the Kirchhoff index for the two types of claw-free cubic graphs," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    2. Sajjad, Wasim & Sardar, Muhammad Shoaib & Pan, Xiang-Feng, 2024. "Computation of resistance distance and Kirchhoff index of chain of triangular bipyramid hexahedron," Applied Mathematics and Computation, Elsevier, vol. 461(C).
    3. Jiang, Yaxin & Yang, Yujun, 2025. "Computation of resistance distances and Kirchhoff indices for two classes of graphs," Applied Mathematics and Computation, Elsevier, vol. 496(C).
    4. repec:plo:pone00:0008001 is not listed on IDEAS
    5. Sanjeev Goyal & Fernando Vega-Redondo, 2000. "Learning, Network Formation and Coordination," Econometric Society World Congress 2000 Contributed Papers 0113, Econometric Society.
    6. Quayle, A.P. & Siddiqui, A.S. & Jones, S.J.M., 2006. "Preferential network perturbation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 823-840.
    7. Chen, Lei & Yue, Dong & Dou, Chunxia, 2019. "Optimization on vulnerability analysis and redundancy protection in interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1216-1226.
    8. Bálint Mészáros & István Simon & Zsuzsanna Dosztányi, 2009. "Prediction of Protein Binding Regions in Disordered Proteins," PLOS Computational Biology, Public Library of Science, vol. 5(5), pages 1-18, May.
    9. Irina Rish & Guillermo Cecchi & Benjamin Thyreau & Bertrand Thirion & Marion Plaze & Marie Laure Paillere-Martinot & Catherine Martelli & Jean-Luc Martinot & Jean-Baptiste Poline, 2013. "Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-15, January.
    10. Ixandra Achitouv, 2025. "Dynamical analysis of financial stocks network: Improving forecasting using network properties," PLOS ONE, Public Library of Science, vol. 20(5), pages 1-23, May.
    11. Wang, Zhuoyang & Chen, Guo & Hill, David J. & Dong, Zhao Yang, 2016. "A power flow based model for the analysis of vulnerability in power networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 105-115.
    12. Bellingeri, Michele & Cassi, Davide & Vincenzi, Simone, 2014. "Efficiency of attack strategies on complex model and real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 174-180.
    13. Bech, Morten L. & Atalay, Enghin, 2010. "The topology of the federal funds market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5223-5246.
    14. Valentini, Luca & Perugini, Diego & Poli, Giampiero, 2007. "The “small-world” topology of rock fracture networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 323-328.
    15. Enrico Zio & Giovanni Sansavini, 2011. "Component Criticality in Failure Cascade Processes of Network Systems," Risk Analysis, John Wiley & Sons, vol. 31(8), pages 1196-1210, August.
    16. Chen, Binxia & Jiang, Yuanying & Zhou, Donghai, 2025. "Risk contagion network and characteristic measurement among international financial markets," Pacific-Basin Finance Journal, Elsevier, vol. 92(C).
    17. Ryan M. Hynes & Bernardo S. Buarque & Ronald B. Davies & Dieter F. Kogler, 2020. "Hops, Skip & a Jump - The Regional Uniqueness of Beer Styles," Working Papers 202013, Geary Institute, University College Dublin.
    18. Pi, Xiaochen & Tang, Longkun & Chen, Xiangzhong, 2021. "A directed weighted scale-free network model with an adaptive evolution mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    19. Lenore Newman & Ann Dale, 2007. "Homophily and Agency: Creating Effective Sustainable Development Networks," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 9(1), pages 79-90, February.
    20. Aybike Ulusan & Ozlem Ergun, 2018. "Restoration of services in disrupted infrastructure systems: A network science approach," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-28, February.
    21. Yang, Hyeonchae & Jung, Woo-Sung, 2016. "Structural efficiency to manipulate public research institution networks," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 21-32.

    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:chsofr:v:199:y:2025:i:p3:s0960077925009105. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.