Random matrix analysis of multiplex networks

  title={Random matrix analysis of multiplex networks},
  author={Tanu Raghav and Sarika Jalan},
  journal={Physica A: Statistical Mechanics and its Applications},
  • Tanu RaghavS. Jalan
  • Published 20 July 2021
  • Computer Science
  • Physica A: Statistical Mechanics and its Applications



Universality in complex networks: random matrix analysis.

It is shown that nearest neighbor spacing distribution of the eigenvalues of the adjacency matrices of various model networks, namely scale-free, small-world, and random networks follow universal Gaussian orthogonal ensemble statistics of random matrix theory.

Random matrix analysis of complex networks.

This work analyzes the eigenvalues of the adjacency matrix of various model networks, namely, random, scale-free, and small-world networks, using nearest-neighbor and next-nearest-NEighbor spacing distributions to probe long-range correlations in the Eigenvalues.

Spectral analysis of deformed random networks.

  • S. Jalan
  • Computer Science
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2009
We study spectral behavior of sparsely connected random networks under the random matrix framework. Subnetworks without any connection among them form a network having perfect community structure. As

Universality in the spectral and eigenfunction properties of random networks.

The validity of the findings when relaxing the randomness of the network model is explored and it is shown that, in contrast to standard ER networks, ER networks with diagonal disorder also show universality.

Spectra of complex networks.

It is shown that spectra of locally treelike random graphs may serve as a starting point in the analysis of spectral properties of real-world networks, e.g., of the Internet.

Collective dynamics of ‘small-world’ networks

Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.

Evolution of correlated multiplexity through stability maximization.

This work evolves multiplex networks, comprising antisymmetric couplings in one layer depicting predator-prey relationship and symmetric coupling in the other depicting mutualistic (or competitive) relationship, based on stability maximization through the largest eigenvalue of the corresponding adjacency matrices.

Universality of eigenvector delocalization and the nature of the SIS phase transition in multiplex networks

Universal spectral properties of multiplex networks allow us to assess the nature of the transition between disease-free and endemic phases in the SIS epidemic spreading model. In a multiplex

Spectral analysis and the dynamic response of complex networks.

It is shown that the spectral density of hierarchical networks follows a very different pattern, which can be used as a fingerprint of modularity, related to the homeostatic response of the network.