2015
DOI: 10.1038/srep18091
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One node driving synchronisation

Abstract: Abrupt changes of behaviour in complex networks can be triggered by a single node. This work describes the dynamical fundamentals of how the behaviour of one node affects the whole network formed by coupled phase-oscillators with heterogeneous coupling strengths. The synchronisation of phase-oscillators is independent of the distribution of the natural frequencies, weakly depends on the network size, but highly depends on only one key oscillator whose ratio between its natural frequency in a rotating frame and… Show more

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Cited by 5 publications
(5 citation statements)
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“…The scheme has been exhaustively tested with numerical simulations and it has always resulted in an enhancement in the global synchronization properties of the system. Our main conclusion is that the optimal subset C, in the sense that will be properly define in Section III, should consist in the nodes i such that |Ω−ω i | is maximal, a result which is indeed in agreement with some recent related works 13,14,34 , and that might shed some light on the evolution and structure of natural systems for which global synchronization is a desired property. Despite our analysis is explicitly done for the Ω > 0 case with symmetric distributions g(ω), we will show that the optimization criterion of maximizing |Ω − ω i | for choosing the subset C of forced nodes is valid for more general cases as well.…”
Section: Introductionsupporting
confidence: 83%
“…The scheme has been exhaustively tested with numerical simulations and it has always resulted in an enhancement in the global synchronization properties of the system. Our main conclusion is that the optimal subset C, in the sense that will be properly define in Section III, should consist in the nodes i such that |Ω−ω i | is maximal, a result which is indeed in agreement with some recent related works 13,14,34 , and that might shed some light on the evolution and structure of natural systems for which global synchronization is a desired property. Despite our analysis is explicitly done for the Ω > 0 case with symmetric distributions g(ω), we will show that the optimization criterion of maximizing |Ω − ω i | for choosing the subset C of forced nodes is valid for more general cases as well.…”
Section: Introductionsupporting
confidence: 83%
“…In order to get insight into the general behavior of the system we present a set of simulations for the following networks: For the fully connected networks the critical value λ c for the onset of synchronization can be estimated when N → ∞ as λ c = 2a 2/π ≈ 1.6. For finite networks the calculation of λ c can be performed numerically (see, for example, [31]) and we have checked that λ c = 1.6 is a good approximation even for N = 100 and for the other topologies we used. Full synchronization occurs only for larger values of λ and we define λ f as the value where r = 0.95 andψ < 10 −2 .…”
Section: Numerical Resultsmentioning
confidence: 99%
“…Another interesting choice would be to pick them according to their natural frequencies ω i . For finite systems the oscillator with the largest frequency determines the spontaneous synchronization of the system [31] and forcing the fastest nodes might also result in interesting dynamics.…”
Section: Discussionmentioning
confidence: 99%
“…One of the most prominent and extensively studied network models for analyzing the stability of synchronization in complex networks is the Kuramoto network model [41][42][43][44] , which has also been generalized to higher order. Through linearization, the stability of the complete synchronous mode in the higherorder Kuramoto network is associated with the properties of the generalized Laplacian 40,45 .…”
Section: Introductionmentioning
confidence: 99%