Complex systems that consist of diverse kinds of entities that interact in different ways can be modeled by multilayer networks. This paper uses the tensor formalism with the Einstein product to model this type of networks. Several centrality measures, that are well known for single-layer networks, are extended to multilayer networks using tensors and their properties are investigated. In particular, subgraph centrality based on the exponential and resolvent of a tensor are considered. Krylov subspace methods based on the tensor format are introduced for computing approximations of different measures for large multilayer networks.

A tensor formalism for multilayer network centrality measures using the Einstein product / El-Halouy, S.; Noschese, S.; Reichel, L.. - In: APPLIED NUMERICAL MATHEMATICS. - ISSN 0168-9274. - (2023). [10.1016/j.apnum.2023.06.013]

A tensor formalism for multilayer network centrality measures using the Einstein product

Noschese S.
;
2023

Abstract

Complex systems that consist of diverse kinds of entities that interact in different ways can be modeled by multilayer networks. This paper uses the tensor formalism with the Einstein product to model this type of networks. Several centrality measures, that are well known for single-layer networks, are extended to multilayer networks using tensors and their properties are investigated. In particular, subgraph centrality based on the exponential and resolvent of a tensor are considered. Krylov subspace methods based on the tensor format are introduced for computing approximations of different measures for large multilayer networks.
2023
Adjacency tensor; centrality measures; Einstein product; Krylov subspace method; multilayer networks; tensor functions
01 Pubblicazione su rivista::01a Articolo in rivista
A tensor formalism for multilayer network centrality measures using the Einstein product / El-Halouy, S.; Noschese, S.; Reichel, L.. - In: APPLIED NUMERICAL MATHEMATICS. - ISSN 0168-9274. - (2023). [10.1016/j.apnum.2023.06.013]
File allegati a questo prodotto
File Dimensione Formato  
El-Halouy_preprint_A-tensor_2023.pdf

accesso aperto

Tipologia: Documento in Pre-print (manoscritto inviato all'editore, precedente alla peer review)
Licenza: Creative commons
Dimensione 658.66 kB
Formato Adobe PDF
658.66 kB Adobe PDF
El-Halouy_A-tensor_2023.pdf

embargo fino al 22/06/2025

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 845.66 kB
Formato Adobe PDF
845.66 kB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1686046
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 1
social impact