The total communicability of a network (or graph) is defined as the sum of the entries in the exponential of the adjacency matrix of the network, possibly normalized by the number of nodes. This quantity offers a good measure of how easily information spreads across the network, and can be useful in the design of networks having certain desirable properties. The total communicability can be computed quickly even for large networks using techniques based on the Lanczos algorithm. In this work we introduce some heuristics that can be used to add, delete, or rewire a limited number of edges in a given sparse network so that the modified network has a large total communicability. To this end, we introduce new edge centrality measures, which can be used as a guide in the selection of edges to be added or removed. Moreover, we show experimentally that the total communicability provides an effective and easily computable measure of how "well-connected" a sparse network is.

Updating and downdating techniques for optimizing network communicability

Benzi, Michele
2016

Abstract

The total communicability of a network (or graph) is defined as the sum of the entries in the exponential of the adjacency matrix of the network, possibly normalized by the number of nodes. This quantity offers a good measure of how easily information spreads across the network, and can be useful in the design of networks having certain desirable properties. The total communicability can be computed quickly even for large networks using techniques based on the Lanczos algorithm. In this work we introduce some heuristics that can be used to add, delete, or rewire a limited number of edges in a given sparse network so that the modified network has a large total communicability. To this end, we introduce new edge centrality measures, which can be used as a guide in the selection of edges to be added or removed. Moreover, we show experimentally that the total communicability provides an effective and easily computable measure of how "well-connected" a sparse network is.
2016
Settore MAT/08 - Analisi Numerica
Edge centrality; Eigenvector centrality; Free energy; Natural connectivity; Network analysis; Subgraph centrality; Total communicability; Computational Mathematics; Applied Mathematics
File in questo prodotto:
File Dimensione Formato  
ab15.pdf

accesso aperto

Descrizione: Versione editoriale
Tipologia: Published version
Licenza: Solo Lettura
Dimensione 369.65 kB
Formato Adobe PDF
369.65 kB Adobe PDF
Arrigo_Benzi_SJSC2016_Updating_downdating_techniques_optimizing_network_communicability.pdf

accesso aperto

Descrizione: Versione accettata
Tipologia: Accepted version (post-print)
Licenza: Creative Commons
Dimensione 584.89 kB
Formato Adobe PDF
584.89 kB Adobe PDF

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/11384/75242
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 29
  • ???jsp.display-item.citation.isi??? 27
  • OpenAlex ND
social impact