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Random matrix analysis of multiplex networks

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  • Raghav, Tanu
  • Jalan, Sarika

Abstract

We investigate the spectra of adjacency matrices of multiplex networks under random matrix theory (RMT) framework. Through extensive numerical experiments, we demonstrate that upon multiplexing two random networks, the spectra of the combined multiplex network exhibit superposition of two Gaussian orthogonal ensemble (GOE)s for very small multiplexing strength followed by a smooth transition to the GOE statistics with an increase in the multiplexing strength. Interestingly, randomness in the connection architecture, introduced by random rewiring to 1D lattice, of at least one layer may govern nearest neighbor spacing distribution (NNSD) of the entire multiplex network, and in fact, can drive to a transition from the Poisson to the GOE statistics or vice versa. Notably, this transition transpires for a very small number of the random rewiring corresponding to the small-world transition. Ergo, only one layer being represented by the small-world network is enough to yield GOE statistics for the entire multiplex network. Spectra of adjacency matrices of underlying interaction networks have been contemplated to be related with dynamical behavior of the corresponding complex systems, the investigations presented here have implications in achieving better structural and dynamical control to the systems represented by multiplex networks against structural perturbation in only one of the layers.

Suggested Citation

  • Raghav, Tanu & Jalan, Sarika, 2022. "Random matrix analysis of multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
  • Handle: RePEc:eee:phsmap:v:586:y:2022:i:c:s0378437121007305
    DOI: 10.1016/j.physa.2021.126457
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    1. Torres-Vargas, G. & Fossion, R. & Méndez-Bermúdez, J.A., 2020. "Normal mode analysis of spectra of random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    2. Matharoo, Gurpreet S. & Hashmi, Javeria A., 2020. "Spontaneous back-pain alters randomness in functional connections in large scale brain networks: A random matrix perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    3. Paul T E Cusack, 2020. "On Pain," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 31(3), pages 24253-24254, October.
    4. S. Redner, 1998. "How popular is your paper? An empirical study of the citation distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 4(2), pages 131-134, July.
    5. Marvel, K. & Agvaanluvsan, U., 2010. "Random matrix theory models of electric grid topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5838-5851.
    6. H. Jeong & S. P. Mason & A.-L. Barabási & Z. N. Oltvai, 2001. "Lethality and centrality in protein networks," Nature, Nature, vol. 411(6833), pages 41-42, May.
    7. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
    Full references (including those not matched with items on IDEAS)

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