Publication:
Normalized sombor indices as complexity measures of random networks

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URI: https://hdl.handle.net/10016/34401
ISSN: 1099-4300
DOI: https://doi.org/10.3390/e23080976
UXXI: AR/0000028931
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Normalized_ENTROPY_2021.pdf (650.59 KB)
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2021-08
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MDPI AG
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Abstract
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.
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Computational analysis of networks, Random networks, Sombor indices, Degree-based topological indices
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Aguilar-Sánchez, R., Méndez-Bermúdez, J. A., Rodríguez, J. M., & Sigarreta, J. M. (2021). Normalized Sombor Indices as Complexity Measures of Random Networks. In Entropy (Vol. 23, Issue 8, p. 976). MDPI AG.
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