Effects of topological characteristics on rhythmic states of the D-dimensional Kuramoto model in complex networks

2022 ◽  
Vol 32 (1) ◽  
pp. 013118
Author(s):  
Xiang Ling ◽  
Wen-Bin Ju ◽  
Ning Guo ◽  
Kong-Jin Zhu ◽  
Chao-Yun Wu ◽  
...  
Keyword(s):  
Complex Networks ◽  
Kuramoto Model ◽  
Topological Characteristics

scholarly journals Modular synchronization in complex networks with a gauge Kuramoto model

2008 ◽  
Vol 83 (6) ◽  
pp. 68003 ◽  
Author(s):  
E. Oh ◽  
C. Choi ◽  
B. Kahng ◽  
D. Kim
Keyword(s):  
Complex Networks ◽  
Kuramoto Model

Dynamics of the Kuramoto Model with Bimodal Frequency Distribution on Complex Networks

2014 ◽  
Vol 31 (8) ◽  
pp. 080503
Author(s):  
Yue-E Feng ◽  
Hai-Hong Li ◽  
Jun-Zhong Yang
Keyword(s):  
Complex Networks ◽  
Frequency Distribution ◽  
Kuramoto Model ◽  
The Kuramoto Model

A new spectral coarse-graining algorithm based on K-means clustering in complex networks

2019 ◽  
Vol 33 (01) ◽  
pp. 1850421 ◽  
Author(s):  
Lang Zeng ◽  
Zhen Jia ◽  
Yingying Wang
Keyword(s):  
Complex Networks ◽  
Large Scale ◽  
Dynamic Properties ◽  
Coarse Graining ◽  
Kuramoto Model ◽  
Coarse Grained ◽  
Original Network ◽  
Topological Information ◽  
Real World Applications ◽  
Large Scale Networks

Coarse-graining of complex networks is one of the important algorithms to study large-scale networks, which is committed to reducing the size of networks while preserving some topological information or dynamic properties of the original networks. Spectral coarse-graining (SCG) is one of the typical coarse-graining algorithms, which can keep the synchronization ability of the original network well. However, the calculation of SCG is large, which limits its real-world applications. And it is difficult to accurately control the scale of the coarse-grained network. In this paper, a new SCG algorithm based on K-means clustering (KCSCG) is proposed, which cannot only reduce the amount of calculation, but also accurately control the size of coarse-grained network. At the same time, KCSCG algorithm has better effect in keeping the network synchronization ability than SCG algorithm. A large number of numerical simulations and Kuramoto-model example on several typical networks verify the feasibility and effectiveness of the proposed algorithm.

Extraction algorithm for optimal coarse-grained networks on complex networks

2019 ◽  
Vol 30 (11) ◽  
pp. 1950081
Author(s):  
Lang Zeng ◽  
Zhen Jia ◽  
Yingying Wang
Keyword(s):  
Complex Networks ◽  
Network Science ◽  
Dynamic Properties ◽  
Coarse Graining ◽  
Kuramoto Model ◽  
Coarse Grained ◽  
Urgent Problem ◽  
Original Network ◽  
Topological Information ◽  
Extraction Algorithm

Coarse-graining of complex networks is a hot topic in network science. Coarse-grained networks are required to preserve the topological information or dynamic properties of the original network. Some effective coarse-graining methods have been proposed, while an urgent problem is how to obtain coarse-grained network with optimal scale. In this paper, we propose an extraction algorithm (EA) for optimal coarse-grained networks. Numerical simulation for EA on four kinds of networks and performing Kuramoto model on optimal coarse-grained networks, we find our algorithm can effectively obtain the optimal coarse-grained network.

The Impact of Complex Network Models to EDAs

2014 ◽  
Vol 926-930 ◽  
pp. 3290-3293
Author(s):  
Cai Chang Ding ◽  
Wen Xiu Peng ◽  
Wei Ming Wang
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Optimization Problem ◽  
Wide Spectrum ◽  
Network Models ◽  
Problem Structure ◽  
Topological Characteristics ◽  
Complex Network Models ◽  
The Impact

The study conducted in this paper is mainly driven by the topological characteristics of the structures that the interactions among the variables of the problems provide. Taking as reference the emergent field of complex networks, we generate a wide spectrum of networks that will serve as problem structures. Then, the impact that the topological characteristics of those networks have, both in the hardness of the optimization problem and in the behavior of the EDA, is analyzed. This reveals a relationship among the topology of the problem structure, the difficulty of the problems and the dependences that the algorithm needs to learn in order to solve the problems.

scholarly journals The Kuramoto model in complex networks

2016 ◽  
Vol 610 ◽  
pp. 1-98 ◽  
Author(s):  
Francisco A. Rodrigues ◽  
Thomas K. DM. Peron ◽  
Peng Ji ◽  
Jürgen Kurths
Keyword(s):  
Complex Networks ◽  
Kuramoto Model ◽  
The Kuramoto Model

scholarly journals TOPOLOGICAL PROPERTIES OF THE CONTACT NETWORK OF GRANULAR MATERIALS

2009 ◽  
Vol 19 (02) ◽  
pp. 695-702 ◽  
Author(s):  
ROBERTO ARÉVALO ◽  
IKER ZURIGUEL ◽  
DIEGO MAZA
Keyword(s):  
Complex Networks ◽  
Granular Materials ◽  
Structural Features ◽  
Contact Network ◽  
Topological Properties ◽  
Physical Behavior ◽  
Topological Characteristics ◽  
Force Networks ◽  
Square Box

The force networks of different granular ensembles are defined and their topological properties studied using the tools of complex networks. In particular, for each set of grains compressed in a square box, a force threshold is introduced that determines which contacts conform the network. Hence, the topological characteristics of the network are analyzed as a function of this parameter. The characterization of the structural features thus obtained, may be useful in the understanding of the macroscopic physical behavior exhibited by this class of media.

scholarly journals Kuramoto model with frequency-degree correlations on complex networks

2013 ◽  
Vol 87 (3) ◽  
Author(s):  
B. C. Coutinho ◽  
A. V. Goltsev ◽  
S. N. Dorogovtsev ◽  
J. F. F. Mendes
Keyword(s):  
Complex Networks ◽  
Kuramoto Model ◽  
Degree Correlations
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