Synchrony-optimized networks of Kuramoto oscillators with inertia

Pinto, Rafael S.; Saa, Alberto

doi:10.1016/j.physa.2016.07.009

Cited by 28 publications

(21 citation statements)

References 33 publications

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“…For our purposes here, we will use L as a quantifier for the network synchronization capability, the larger value of L, the better synchronization properties of the network. This conclusion is totally compatible with the numerical works done before for the Kuramoto model [23][24][25] and also for the so-called Kuramoto model with inertia [26], which is particularly relevant to the study of power lines [27,28]. We have confirmed here, by exhaustive numerical simulations, the validity of this conclusion also for the SL case.…”

Section: A the Optimization Algorithmsupporting

confidence: 92%

Symmetries and synchronization in multilayer random networks

Saa

2018

Phys. Rev. E

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In the light of the recently proposed scenario of asymmetry-induced synchronization (AISync), in which dynamical uniformity and consensus in a distributed system would demand certain asymmetries in the underlying network, we investigate here the influence of some regularities in the interlayer connection patterns on the synchronization properties of multilayer random networks. More specifically, by considering a Stuart-Landau model of complex oscillators with random frequencies, we report for multilayer networks a dynamical behavior that could be also classified as a manifestation of AISync. We show, namely, that the presence of certain symmetries in the interlayer connection pattern tends to diminish the synchronization capability of the whole network or, in other words, asymmetries in the interlayer connections would enhance synchronization in such structured networks. Our results might help the understanding not only of the AISync mechanism itself but also its possible role in the determination of the interlayer connection pattern of multilayer and other structured networks with optimal synchronization properties.

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Section: A the Optimization Algorithmsupporting

confidence: 92%

Symmetries and synchronization in multilayer random networks

Saa

2018

Phys. Rev. E

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“…solar plants [361], on synchronization and stability remain open. A rewiring algorithm by implementing a simple hill-climb method on switching edges was proposed to enhance synchronization [368]. Actually, given even that the network topology is fixed, localization of natural frequencies could affect synchronization.…”

Section: Power-gridsmentioning

confidence: 99%

The Kuramoto model in complex networks

et al. 2016

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Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.

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“…In this paper, we discuss the repercussions of inclusion of time delay on ES in the multilayer networks. We represent the nodes in multiplex networks by second-order Kuramoto oscillators [34][35][36][37][38] with natural frequencies positively correlated with their respective degrees, and study impact of the time delay in one layer on synchronization in other layers. It is perceived that inclusion of time delay in any one layer of the multiplex network induces either ES or non-ES transition concurrently in all the layers, irrespective of whether the layers are delayed or un-delayed, depending on the value of the inducted time-delay.…”

Section: Introductionmentioning

confidence: 99%

Delay regulated explosive synchronization in multiplex networks

Kachhvah

Jalan

2019

New J. Phys.

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It is known that explosive synchronization (ES) in an isolated network of Kuramoto oscillators with inertia is significantly enhanced by the presence of time delay. Here we show that time delay in one layer of the multiplex network governs the transition to synchronization and ES in the other layers. We found that a single layer with time-delayed intra-layer coupling may experience a different type of transition to synchronization, e.g. ES or continuous, depending on the values of time delay. Importantly, the same type of transition is incorporated simultaneously in other layer(s) as well, irrespective of the intra-layer delay values. Hence, a suitable choice of time-delay in only one layer of a multiplex network can lead to a desired (either ES or continuous) transition simultaneously in the other layers, either directly or remotely connected to the delayed layer. These results offer a platform for a better understanding of the dynamics of those complex systems which are represented by the multilayered framework and contain time delays in the communication processes.

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Synchrony-optimized networks of Kuramoto oscillators with inertia

Cited by 28 publications

References 33 publications

Symmetries and synchronization in multilayer random networks

Symmetries and synchronization in multilayer random networks

The Kuramoto model in complex networks

Delay regulated explosive synchronization in multiplex networks

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