Examinando por Autor "Boccaletti, S."

Mostrando 1 - 4 de 4

Regulating synchronous states of complex networks by pinning interaction with an external node
(Physical Review E, 2009-12-14) Almendral, J.A.; Sendiña-Nadal, I.; Yu, D.; Leyva, I.; Boccaletti, S.
An initial ensemble of networking dynamical systems is regulated towards a desired synchronized behavior by means of a pinning interaction with an external node. We rigorously demonstrate that there are two classes of networks susceptible of being regulated into a synchronous motion, and practically demonstrate, for each one of them, how to design a proper minimal, optimal, and maximal pinning sequence to achieve synchrony regulation. A series of numerical examples are offered to support our analytical claims. We also discuss how the obtained sequences can be compared with a topological ranking of the network nodes, such as centrality, and the practical applications of our study in the understanding of how networking systems can adjust their architecture in order to establish (or maintain) a synchronous functioning.
Synchronization waves in geometric networks
(Physical Review E, 2011-12-06) Leyva, I.; Navas, A.; Sendiña-Nadal, I.; Buldú, J.M.; Almendral, J.A.; Boccaletti, S.
We report synchronization of networked excitable nodes embedded in a metric space, where the connectivity properties are mostly determined by the distance between units. Such a high clustered structure, combined with the lack of long-range connections, prevents full synchronization, and yields, instead, the emergence of synchronization waves. We show that this regime is optimal for information transmission through the system, as it enhances the options of reconstructing the topology from the dynamics. Measurements of topological and functional centralities reveal, indeed, that the wave synchronization state allows to detect the most structurally relevant nodes from a single observation of the dynamics, without any a-priori information on the model equations ruling the evolution of the ensemble.
The dynamics of overlapping structures in modular networks
(Physical Review E, 2010-07-23) Almendral, J.A.; Lyeva, I.; Li, D.; Sendiña-Nadal, I.; Havlin, S.; Boccaletti, S.
Modularity is a fundamental feature of real networks, being intimately bounded to their function- ality, i.e. to their capability of performing parallel tasks in a coordinated way. Although the modular structure of real graphs has been intensively studied, very little is known on the interactions be- tween functional modules of a graph. Here we present a general method based on synchronization of networking oscillators, that is able to detect overlapping structures in multi-modular environments. We furthermore report the full analytical and theoretical description on the relationship between the overlapping dynamics and the underlying network topology. The method is illustrated by means of a series of applications.
The structure and dynamics of networks with higher order interactions
(Elsevier, 2023) Boccaletti, S.; Lellis, P. De; Genio, C.I. del; Alfaro-Bittner, K.; Criado, R.; Jalan, S.; Romance, M.
All beauty, richness and harmony in the emergent dynamics of a complex system largely depend on the specific way in which its elementary components interact. The last twenty-five years have seen the birth and development of the multidisciplinary field of Network Science, wherein a variety of distributed systems in physics, biology, social sciences and engineering have been modeled as networks of coupled units, in the attempt to unveil the mechanisms underneath their observed functionality. There is, however, a fundamental limit to such a representation: networks capture only pairwise interactions, whereas the functioning of many real-world systems not only involves dyadic connections, but rather is the outcome of collective actions at the level of groups of nodes. For instance, in ecological systems, three or more species may compete for food or territory, and similar multi-component interactions appear in functional and structural brain networks, protein interaction networks, semantic networks, multi-authors scientific collaborations, offline and online social networks, gene regulatory networks and spreading of consensus or contagious diseases due to multiple, simultaneous, contacts. Such multi-component interactions can only be grasped through either hypergraphs or simplicial complexes, which indeed have recently found a huge number of applications. In this report, we cover the extensive literature of the past years on this subject, and we focus on the structure and dynamics of hypergraphs and simplicial complexes. These are indeed becoming increasingly relevant, thanks to the enhanced resolution of data sets and the recent advances in data analysis techniques, which (concurrently and definitely) have shown that such structures play a pivotal role in the complex organization and functioning of real-world distributed systems.