The Kuramoto model in complex networks

被引:705
作者
Rodrigues, Francisco A. [1 ]
Peron, Thomas K. D. M. [2 ,3 ]
Ji, Peng [3 ,4 ]
Kurths, Juergen [3 ,4 ,5 ,6 ]
机构
[1] Univ Sao Paulo, Inst Ciencias Matemat & Comp, Dept Matemat Aplicada & Estat, Caixa Postal 668, BR-13560970 Sao Paulo, Brazil
[2] Univ Sao Paulo, Inst Fis Sao Carlos, Caixa Postal 369, BR-13560970 Sao Paulo, Brazil
[3] Potsdam Inst Climate Impact Res PIK, D-14473 Potsdam, Germany
[4] Humboldt Univ, Dept Phys, D-12489 Berlin, Germany
[5] Univ Aberdeen, Inst Complex Syst & Math Biol, Aberdeen AB24 3UE, Scotland
[6] Nizhnii Novgorod State Univ, Dept Control Theory, Gagarin Ave 23, Nizhnii Novgorod 606950, Russia
来源
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS | 2016年 / 610卷
基金
巴西圣保罗研究基金会;
关键词
GLOBALLY COUPLED OSCILLATORS; LIMIT-CYCLE OSCILLATORS; SYNCHRONIZATION TRANSITION; PHASE OSCILLATORS; CHIMERA STATES; EXPLOSIVE SYNCHRONIZATION; HIERARCHICAL ORGANIZATION; FUNCTIONAL CONNECTIVITY; COLLECTIVE DYNAMICS; MUTUAL ENTRAINMENT;
D O I
10.1016/j.physrep.2015.10.008
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
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. (c) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 98
页数:98
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