Modeling complex systems that consist of different types of objects leads to mul- tilayer networks, where nodes in the different layers represent different kinds of objects. Nodes are connected by edges, which have positive weights. A multilayer network is associated with a supra-adjacency matrix. This paper investigates the sensitivity of the communicability in a multilayer network to perturbations of the network by studying the sensitivity of the Perron root of the supra-adjacency matrix. Our analysis sheds light on which edge weights to make larger to increase the com- municability of the network, and which edge weights can be made smaller or set to zero without affecting the communicability significantly.

Perron communicability and sensitivity of multilayer networks

Silvia Noschese
;
2022

Abstract

Modeling complex systems that consist of different types of objects leads to mul- tilayer networks, where nodes in the different layers represent different kinds of objects. Nodes are connected by edges, which have positive weights. A multilayer network is associated with a supra-adjacency matrix. This paper investigates the sensitivity of the communicability in a multilayer network to perturbations of the network by studying the sensitivity of the Perron root of the supra-adjacency matrix. Our analysis sheds light on which edge weights to make larger to increase the com- municability of the network, and which edge weights can be made smaller or set to zero without affecting the communicability significantly.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1655887
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