The synchronized dynamics of time-varying networks

Ghosh, Dibakar; Frasca, Mattia; Rizzo, Alessandro; Majhi, Soumen; Rakshit, Sarbendu; Alfaro-Bittner, K.; Boccaletti, Stefano

doi:10.1016/j.physrep.2021.10.006

Cited by 112 publications

(56 citation statements)

References 287 publications

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“…Also, there exists another path of length three in the network, which is from the node 4 to 6. Hence, the 3-path network consists of only two links (1,6) and (4,6). The remaining three nodes 2, 3 and 5 are isolated in the 3-path network.…”

Section: Long-range Interaction In Networked Systemsmentioning

confidence: 99%

“…A major achievement of the study of networks is that it is capable of describing collective scenarios having strong applications in large complex systems. The study of dynamical evolution of networked systems leads to a better explanation of a variety of complex processes, ranging from different aspects of synchronization [3][4][5][6][7][8] and evolution of cooperation [9][10][11][12][13] to contagion processes [14][15][16][17]. Among all these phenomena, network robustness has been in the forefront as it explores the issue of networks' ability to stand against perturbations.…”

Section: Introductionmentioning

confidence: 99%

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Dynamical robustness of complex networks subject to long-range connectivity

Majhi

2022

Proc. R. Soc. A.

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In spite of a few attempts in understanding the dynamical robustness of complex networks, this extremely important subject of research is still in its dawn as compared to the other dynamical processes on networks. We hereby consider the concept of long-range interactions among the dynamical units of complex networks and demonstrate for the first time that such a characteristic can have noteworthy impacts on the dynamical robustness of networked systems, regardless of the underlying network topology. We present a comprehensive analysis of this phenomenon on top of diverse network architectures. Such dynamical damages being able to substantially affect the network performance, determining mechanisms that boost the robustness of networks becomes a fundamental question. In this work, we put forward a prescription based upon self-feedback that can efficiently resurrect global rhythmicity of complex networks composed of active and inactive dynamical units, and thus can enhance the network robustness. We have been able to delineate the whole proposition analytically while dealing with all d -path adjacency matrices, having an excellent agreement with the numerical results. For the numerical computations, we examine scale-free networks, Watts–Strogatz small-world model and also Erdös–Rényi random network, along with Landau–Stuart oscillators for casting the local dynamics.

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Section: Long-range Interaction In Networked Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamical robustness of complex networks subject to long-range connectivity

Majhi

2022

Proc. R. Soc. A.

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“…To illustrate, the necessity of considering the links of networks that are different in nature has led to the formulation and detailed analysis of multilayer networks [ 5 ]. Further, time-varying networks [ 6 , 7 ] are investigated in which interactions do not persist for all the course of time, rather they arise or vanish over time. It is unquestionably true that all these developments have helped us to perceive many scenarios better, but we have specifically assumed dyadic or pairwise interactions as the backbone for connections among the units of the system.…”

Section: Introductionmentioning

confidence: 99%

Dynamics on higher-order networks: a review

Majhi

Perc

Ghosh

2022

J. R. Soc. Interface.

244

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Network science has evolved into an indispensable platform for studying complex systems. But recent research has identified limits of classical networks, where links connect pairs of nodes, to comprehensively describe group interactions. Higher-order networks, where a link can connect more than two nodes, have therefore emerged as a new frontier in network science. Since group interactions are common in social, biological and technological systems, higher-order networks have recently led to important new discoveries across many fields of research. Here, we review these works, focusing in particular on the novel aspects of the dynamics that emerges on higher-order networks. We cover a variety of dynamical processes that have thus far been studied, including different synchronization phenomena, contagion processes, the evolution of cooperation and consensus formation. We also outline open challenges and promising directions for future research.

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“…To illustrate, the necessity of considering the links of networks that are different in nature has led to the formulation and detailed analysis of multilayer networks [5]. Further, time-varying networks [6,7] are investigated in which interactions do not persist for all the course of time, rather come up or vanish over time. It is unquestionably true that all these developments have helped us to perceive many scenarios better, but specifically assumed dyadic or pairwise interactions as the backbone for connections among the units of the system.…”

Section: Introductionmentioning

confidence: 99%

Dynamics on higher-order networks: A review

Majhi,

Perc,

Ghosh

2022

Preprint

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Network science has evolved into an indispensable platform for studying complex systems. But recent research has identified limits of classical networks, where links connect pairs of nodes, to comprehensively describe group interactions. Higher-order networks, where a link can connect more than two nodes, have therefore emerged as a new frontier in network science. Since group interactions are common in social, biological, and technological systems, higher-order networks have recently led to important new discoveries across many fields of research. We here review these works, focusing in particular on the novel aspects of the dynamics that emerges on higher-order networks. We cover a variety of dynamical processes that have thus far been studied, including different synchronization phenomena, contagion processes, the evolution of cooperation, and consensus formation. We also outline open challenges and promising directions for future research.

show abstract

The synchronized dynamics of time-varying networks

Cited by 112 publications

References 287 publications

Dynamical robustness of complex networks subject to long-range connectivity

Dynamical robustness of complex networks subject to long-range connectivity

Dynamics on higher-order networks: a review

Dynamics on higher-order networks: A review

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