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 Raghav, S. Jalan
  • Published 2021
  • Physics
  • Physica A: Statistical Mechanics and its Applications
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… Expand


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. Expand
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. Expand
Spectral analysis of deformed random networks.
  • S. Jalan
  • Mathematics, Physics
  • 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. AsExpand
Normal mode analysis of spectra of random networks
Abstract Several spectral fluctuation measures of random matrix theory (RMT) have been applied in the study of spectral properties of networks. However, the calculation of those statistics requiresExpand
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. Expand
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. Expand
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. Expand
Structural measures for multiplex networks.
This paper presents a general framework to describe and study multiplex networks, whose links are either unweighted or weighted, and proposes a series of measures to characterize the multiplexicity of the systems in terms of basic node and link properties. Expand
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. Expand
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. Expand