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‘Hubs-repelling’ Laplacian and related diffusion on graphs/networks. (English) Zbl 1435.05127

Summary: We define and study here a graph unsymmetric Laplacian matrix that operates a diffusive process biased towards low-degree nodes. We prove that this matrix is positive semidefine with all eigenvalues real. We also prove that the rate of convergence of a diffusive process controlled by the hubs-repelling Laplacian depends on the first nontrivial eigenvalue of this Laplacian. Such rate of convergence depends on the existence of low-degree nodes connected to high-degree ones. We find several bounds for the ‘algebraic connectivity’ based on this Laplacian. We then study two real-world scenarios with the hubs-repelling diffusion: the propagation of flight delays in the air transportation network of USA and the cost-efficient information diffusion across the human brain functional coactivation network. Finally, we find some conditions for the nodes of a network to be ‘good spreaders’ under the hubs-repelling dynamics.

MSC:

05C50 Graphs and linear algebra (matrices, eigenvalues, etc.)
05C82 Small world graphs, complex networks (graph-theoretic aspects)
15A18 Eigenvalues, singular values, and eigenvectors
47N50 Applications of operator theory in the physical sciences
Full Text: DOI

References:

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