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Two-dimensional (2D) KPZ growth is usually investigated on substrates of lateral sizes $L_x=L_y$, so that $L_x$ and the correlation length ($\xi$) are the only relevant lengths determining the scaling behavior. However, in cylindrical…

Statistical Mechanics · Physics 2024-05-06 Ismael S. S. Carrasco , Tiago J. Oliveira

The ability to achieve coordinated behavior -- engineered or emergent -- on networked systems has attracted widespread interest over several fields. This interest has led to remarkable advances in developing a theoretical understanding of…

Systems and Control · Electrical Eng. & Systems 2022-03-29 Hancheng Min , Richard Pates , Enrique Mallada

This paper studies synchronization in coupled nonlinear dynamic networks with unknown parameters. Adaptation can be added to one or several elements in the network, while preserving the global synchronization conditions derived in…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Wei Wang , Jean-Jacques E. Slotine

We consider synchronization of chaotic systems coupled indirectly through a common environmnet where the environment has an intrinsic dynmics of its own modulated via feedback from the systems. We find that a rich vareity of synchronization…

Chaotic Dynamics · Physics 2010-05-05 V. Resmi , G. Ambika , R. E. Amritkar

We study the response of an ensemble of synchronized phase oscillators to an external harmonic perturbation applied to one of the oscillators. Our main goal is to relate the propagation of the perturbation signal to the structure of the…

Statistical Mechanics · Physics 2009-11-10 D. H. Zanette

We analyze the synchronization dynamics of phase oscillators far from the synchronization manifold, including the onset of synchronization on scale-free networks with low and high clustering coefficients. We use normal coordinates and…

Disordered Systems and Neural Networks · Physics 2015-06-25 Patrick McGraw , Michael Menzinger

We analyze the effect of synchronization on distributed stochastic gradient algorithms. By exploiting an analogy with dynamical models of biological quorum sensing - where synchronization between agents is induced through communication with…

Optimization and Control · Mathematics 2020-12-18 Nicholas M. Boffi , Jean-Jacques E. Slotine

By using the random interchanging algorithm, we investigate the relations between average distance, standard deviation of degree distribution and synchronizability of complex networks. We find that both increasing the average distance and…

Statistical Mechanics · Physics 2009-11-11 Ming Zhao , Tao Zhou , Bing-Hong Wang , Gang Yan , Hui-Jie Yang , Wen-Jie Bai

We study the relationship between synchronization and the rate with which information is exchanged between nodes in a spatio-temporal network that describes the dynamics of classical particles under a substrate Remoissenet-Peyrard…

Chaotic Dynamics · Physics 2009-11-13 F. M. Moukam Kakmeni , M. S. Baptista

We consider decentralized optimization problems in which a number of agents collaborate to minimize the average of their local functions by exchanging over an underlying communication graph. Specifically, we place ourselves in an…

Optimization and Control · Mathematics 2023-03-20 Yu-Guan Hsieh , Yassine Laguel , Franck Iutzeler , Jérôme Malick

We study the synchronization properties of a generic networked dynamical system, and show that, under a suitable approximation, the transition to synchronization can be predicted with the only help of eigenvalues and eigenvectors of the…

We investigate the emergence of synchronization in heterogeneous networks of chaotic maps. Our findings reveal that a small cluster of highly connected maps is responsible for triggering the spark of synchronization. After the spark, the…

Adaptation and Self-Organizing Systems · Physics 2024-02-01 Antonio Montalban , Rodrigo M. Corder

Distributed consensus has been widely studied for sensor network applications. Whereas the asymptotic convergence rate has been extensively explored in prior work, other important and practical issues, including energy efficiency and link…

Networking and Internet Architecture · Computer Science 2013-04-10 Lei Chen , Jeff Frolik

Activity or spin patterns on random scale-free network are studied by mean field analysis and computer simulations. These activity patterns evolve in time according to local majority-rule dynamics which is implemented using (i) parallel or…

Disordered Systems and Neural Networks · Physics 2007-05-23 Haijun Zhou , Reinhard Lipowsky

This work is concerned with the design and effects of the synchronization gains on the synchronization problem for a class of networked distributed parameter systems. The networked systems, assumed to be described by the same evolution…

Optimization and Control · Mathematics 2013-06-03 Michael A. Demetriou

The inevitable random frequency differences among semiconductor lasers present an obstacle to achieving their collective coherence, but previous worked showed that fully (all-to-all) coupled networks can still be synchronized even in the…

Optics · Physics 2025-11-06 Li-Li Ye , Nathan Vigne , Fan-Yi Lin , Hui Cao , Ying-Cheng Lai

This work addresses synchronization in transient, non-linear stochastic dynamics corresponding to accesses performed by self-avoiding walks originating at each node of a complex network. More specifically, the synchronizability of accesses…

Physics and Society · Physics 2008-01-17 Luciano da Fontoura Costa

A computer model is described which is used to assess the dynamical complexity of a class of networks of spiking neurons with small-world properties. Networks are constructed by forming an initially segregated set of highly intra-connected…

Biological Physics · Physics 2009-11-13 Murray Shanahan

Navigation process is studied on a variant of the Watts-Strogatz small world network model embedded on a square lattice. With probability $p$, each vertex sends out a long range link, and the probability of the other end of this link…

Disordered Systems and Neural Networks · Physics 2009-11-11 Jian-Zhen Chen , Wei Liu , Jian-Yang Zhu

Neural networks trained via gradient descent with random initialization and without any regularization enjoy good generalization performance in practice despite being highly overparametrized. A promising direction to explain this phenomenon…

Machine Learning · Computer Science 2022-05-17 Hancheng Min , Salma Tarmoun , Rene Vidal , Enrique Mallada
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