A geometric entropy is defined in terms of the Riemannian volume of the parameter space of a statistical manifold associated with a given network. As such it can be a good candidate for measuring networks complexity. Here we investigate its ability to single out topological features of networks proceeding in a bottom-up manner: first we consider small size networks by analytical methods and then large size networks by numerical techniques. Two different classes of networks, the random graphs and the scale-free networks, are investigated computing their Betti numbers and then showing the capability of geometric entropy of detecting homologies.

Catching homologies by geometric entropy

Felice, Domenico;Mancini, Stefano;
2018-01-01

Abstract

A geometric entropy is defined in terms of the Riemannian volume of the parameter space of a statistical manifold associated with a given network. As such it can be a good candidate for measuring networks complexity. Here we investigate its ability to single out topological features of networks proceeding in a bottom-up manner: first we consider small size networks by analytical methods and then large size networks by numerical techniques. Two different classes of networks, the random graphs and the scale-free networks, are investigated computing their Betti numbers and then showing the capability of geometric entropy of detecting homologies.
2018
262
File in questo prodotto:
File Dimensione Formato  
physa2018.pdf

solo gestori di archivio

Descrizione: PDF
Tipologia: Versione Editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 575.53 kB
Formato Adobe PDF
575.53 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
1703.07369.pdf

accesso aperto

Tipologia: Documento in Pre-print
Licenza: DRM non definito
Dimensione 446.42 kB
Formato Adobe PDF
446.42 kB Adobe PDF Visualizza/Apri

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/11581/406292
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact