Normalized Sombor Indices as Complexity Measures of Random Networks

We perform a detailed computational study of the recently introduced Sombor indices on random networks. Specifically, we apply Sombor indices on three models of random networks: Erdös-Rényi networks, random geometric graphs, and bipartite random networks. Within a statistical random matrix theory ap...

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Bibliographic Details
Main Authors: R. Aguilar-Sánchez, J. A. Méndez-Bermúdez, José M. Rodríguez, José M. Sigarreta
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/23/8/976
Description
Summary:We perform a detailed computational study of the recently introduced Sombor indices on random networks. Specifically, we apply Sombor indices on three models of random networks: Erdös-Rényi networks, random geometric graphs, and bipartite random networks. Within a statistical random matrix theory approach, we show that the average values of Sombor indices, normalized to the order of the network, scale with the average degree. Moreover, we discuss the application of average Sombor indices as complexity measures of random networks and, as a consequence, we show that selected normalized Sombor indices are highly correlated with the Shannon entropy of the eigenvectors of the adjacency matrix.
ISSN:1099-4300