Examinando por Autor "Kovalenko, Kirill"

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The transition to synchronization of networked systems
(Springer, 2024-06-10) Bayani, Atiyeh; Nazarimehr, Fahimeh; Jafari, Sajad; Kovalenko, Kirill; Contreras-Aso, Gonzalo; Alfaro-Bittner, Karin; Sánchez-García, Rubén J; Boccaletti, Stefano
We study the synchronization properties of a generic networked dynamical system, and show that, under a suitable approximation, the transition to synchronization can be predicted with the only help of eigenvalues and eigenvectors of the graph Laplacian matrix. The transition comes out to be made of a well defined sequence of events, each of which corresponds to a specific clustered state. The network’s nodes involved in each of the clusters can be identified, and the value of the coupling strength at which the events are taking place can be approximately ascertained. Finally, we present largescale simulations which show the accuracy of the approximation made, and of our predictions in describing the synchronization transition of both synthetic and real-world large size networks, and we even report that the observed sequence of clusters is preserved in heterogeneous networks made of slightly non-identical systems.
Why are there six degrees of separation in a social network?
(American Physical Society, 2023-05-31) Samoylenko, Ivan; Aleja, David; Primo, Eva; Alfaro-Bittner, Karin; Vasilyeva, Ekaterina; Kovalenko, Kirill; Musatov, Daniil; Raigorodskii, Andreii M.; Criado, Regino; Romance, Miguel; Papo, David; Perc, Matjaz; Barzel, Baruch; Boccaletti, Stefano
A wealth of evidence shows that real-world networks are endowed with the small-world property, i.e., that the maximal distance between any two of their nodes scales logarithmically rather than linearly with their size. In addition, most social networks are organized so that no individual is more than six connections apart from any other, an empirical regularity known as the six degrees of separation. Why social networks have this ultrasmall-world organization, whereby the graph’s diameter is independent of the network size over several orders of magnitude, is still unknown. We show that the “six degrees of separation” is the property featured by the equilibrium state of any network where individuals weigh between their aspiration to improve their centrality and the costs incurred in forming and maintaining connections. We show, moreover, that the emergence of such a regularity is compatible with all other features, such as clustering and scale-freeness, that normally characterize the structure of social networks. Thus, our results show how simple evolutionary rules of the kind traditionally associated with human cooperation and altruism can also account for the emergence of one of the most intriguing attributes of social networks.