Onset of synchronization of Kuramoto oscillators in scale-free networks.
Summary (2 min read)
I. INTRODUCTION
- Synchronization processes are pervasively observed in a wide range of physical, chemical, technological, and biological systems [1] .
- Arguably, one of the most studied models in this context is the one proposed by Kuramoto [2] , which in the last decade was extensively investigated when the oscillators are placed on complex networks (see [3, 4] and references therein).
- One of these problems is whether the critical coupling strength for the onset of synchronization remains finite in the thermodynamic limit for scale-free (SF) networks characterized by a power-law degree distribution with an exponent 2 < γ.
- In Sec. III, the authors compare the estimations by mean-field theories with numerical simulations.
II. MEAN-FIELD THEORIES FOR PHASE OSCILLATORS IN HETEROGENEOUS NETWORKS
- The authors provide a brief review of the main analytical approximations used to deal with ensembles of phase oscillators in heterogeneous networks.
- In contrast to the case of globally connected populations, the original analytical treatment via a self-consistent analysis by Kuramoto [2] cannot be directly extended to the network case.
- Instead, an exact decoupling is only achieved by defining local order parameters as EQUATION which leads to EQUATION.
- Therefore, in this paper, the authors evaluate the onset synchronization numerically using the standard order parameter R in Eq. ( 2).
- The authors goal is to systematically investigate the behavior of the onset of synchronization as the size of SF networks increases, comparing the theoretical predictions provided by the current mean-field approaches.
IV. COUPLING NORMALIZATION
- The size dependence of the onset of synchronization on the system's size brings back to attention a topic intensively debated in early studies of network synchronization [3, 4] , namely, the choice for the normalization of the coupling function.
- The authors compare the impact of different prescriptions for the coupling function in large heterogeneous networks in the light of the latter points.
- Reasonable choices for N i would then be quantities that are related to the network topology.
- Curiously, this conclusion is not evident from early works [3, 4] . if the problem of finding the appropriate normalization has been solved: Nevertheless, while this choice leads to a finite onset of synchronization in the thermodynamic limit-and moreover sets the same K c for all heterogeneous networks-it imposes a vanishing coupling strength to low connected nodes.
V. CONCLUSION AND DISCUSSION
- The authors have analyzed the onset of synchronization of Kuramoto phase oscillators in scale-free networks.
- Specifically, both theories predicted a vanishing critical value for the onset of synchronization.
- The authors pointed out that this is a noticeable difference between the critical properties of synchronization of phase oscillators and the SIS dynamics.
- Nevertheless, in this regime of γ , the latter approximation estimates correctly secondary peaks in susceptibility curves associated with localization effects due to the epidemic activation of the largest hub in the network-a phenomenon for which the authors have not observed a counterpart in the synchronization dynamics of large SF networks.
- While this prescription could be appropriate in cases in which the focus of the analysis is not on the role played by the network topology in the dynamics (e.g., [36] ), it seems counterintuitive that large heterogeneous networks should synchronize similarly as homogeneous ones.
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"Onset of synchronization of Kuramot..." refers background or result in this paper
...In particular, we verify that HMF correctly predicts a finite critical threshold in the thermodynamic limit for γ > 3, in contrast to results obtained in the context of epidemic dynamics [16, 17]....
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...Similar dependences with the system size are found for epidemic thresholds in SF networks with 5/2 < γ < 3 [16, 17]....
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...This phenomenon causes a double-peaked shape in the susceptibility curve [16, 17] and the emergence of Griffiths effects [27]–in this case, QMF captures the peak associated to the activation of the largest hub in the network [21]....
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...[17] Angélica S Mata and Silvio C Ferreira, “Pair quenched mean-field theory for the susceptible-infected-susceptible model on complex networks,” EPL (Europhysics Letters) 103, 48003 (2013)....
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...2(c), epidemic thresholds of the SIS model are known to decay as N increases for γ > 3 [16, 17]....
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52 citations
"Onset of synchronization of Kuramot..." refers background in this paper
...This phenomenon causes a double-peaked shape in the susceptibility curve [16, 17] and the emergence of Griffiths effects [27]–in this case, QMF captures the peak associated to the activation of the largest hub in the network [21]....
[...]
...Nonetheless, analogous forms of χr have been shown to be better suited to detect transition points in epidemic spreading and contact processes in networks with diverging 〈k2〉 [16, 21, 22]....
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...[21] Angélica S Mata and Silvio C Ferreira, “Multiple transitions of the susceptible-infected-susceptible epidemic model on complex networks,” Physical Review E 91, 012816 (2015)....
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51 citations
"Onset of synchronization of Kuramot..." refers background in this paper
...Synchronization thresholds, on the other hand, present the same behavior as observed in most dynamical processes that exhibit a phase transition from active to inactive states, such as contact process and SIRS model [28, 29]....
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...However, with the aim of understanding the nature of the threshold in epidemic models on uncorrelated random networks, recent works [22, 28, 29] showed that different epidemic models such as, for instance, susceptible-infected-recovered-susceptibility [30], contact process [31], the generalized SIS model with weighted infection rates [32] and other alterations of the SIS model [29], have a finite threshold in the thermodynamic limit....
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Q2. What are the future works in "Onset of synchronization of kuramoto oscillators in scale-free networks" ?
Future research should, however, investigate the limits of the self-consistent approach in predicting the critical points of the second-order model in light of the recent results present in [ 42 ]. A systematic study about the dependence of the nature of the synchronization transition on N as well as on the distribution of connection weights for SF networks made up of secondorder Kuramoto oscillators is also an interesting topic for future research.