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We introduce an unsupervised graph embedding that trades off local node similarity and connectivity, and global structure. The embedding is based on a generalized graph Laplacian, whose eigenvectors compactly capture both network structure…

Machine Learning · Computer Science 2020-10-01 Shay Deutsch , Stefano Soatto

We consider a stochastic model of clock synchronization in a wireless network consisting of N sensors interacting with one dedicated accurate time server. For large N we find an estimate of the final time sychronization error for global and…

Probability · Mathematics 2013-03-04 Anatoly Manita

Full synchronization of dynamical elements coupled via hypergraphs can be analyzed with the hypergraph projection onto dyadic matrices, but this is not sufficient for analyzing cluster synchronization. Here we develop the necessary…

Adaptation and Self-Organizing Systems · Physics 2022-03-21 Anastasiya Salova , Raissa M. D'Souza

Centrality measures, quantifying the importance of vertices or edges, play a fundamental role in network analysis. To date, triggered by some positive approximability results, a large body of work has been devoted to studying centrality…

Social and Information Networks · Computer Science 2024-02-13 Atsushi Miyauchi , Lorenzo Severini , Francesco Bonchi

In this article, we revisit and expand our prior work on graph similarity. As with our earlier work, we focus on a view of similarity which does not require node correspondence between graphs under comparison. Our work is suited to the…

Discrete Mathematics · Computer Science 2025-12-10 Pierre Miasnikof , Alexander Y. Shetopaloff

In this paper, we studied the strategies to enhance synchronization on directed networks by manipulating a fixed number of links. We proposed a centrality-based reconstructing (CBR) method, where the node centrality is measured by the…

Physics and Society · Physics 2012-08-09 An Zeng , Linyuan Lü , Tao Zhou

We introduce a new centrality measure that characterizes the participation of each node in all subgraphs in a network. Smaller subgraphs are given more weight than larger ones, which makes this measure appropriate for characterizing network…

Statistical Mechanics · Physics 2009-11-11 Ernesto Estrada , Juan A. Rodriguez-Velazquez

While symmetry has been exploited to analyze synchronization patterns in complex networks, the identification of symmetries in large-size network remains as a challenge. We present in the present work a new method, namely the method of…

Adaptation and Self-Organizing Systems · Physics 2023-08-04 Huwei Fan , Xingang Wang

Maximally synchronizable networks (MSNs) are acyclic directed networks that maximize synchronizability. In this paper, we investigate the feasibility of transforming networks of coupled oscillators into their corresponding MSNs. By tuning…

It is common knowledge that a key dynamical characteristic of a network is its spectrum (the collection of all eigenvalues of the network's weighted adjacency matrix). In \cite{BW10} we demonstrated that it is possible to reduce a network,…

Dynamical Systems · Mathematics 2015-06-05 Leonid Bunimovich , Benjamin Webb

Extracting a proper dynamic network for modelling a time-dependent complex system is an important issue. Building a correct model is related to finding out critical time points where a system exhibits considerable change. In this work, we…

Social and Information Networks · Computer Science 2022-06-28 Günce Keziban Orman , Nadir Türe , Selim Balcisoy , Hasan Alp Boz

We present a computer-assisted approach to coarse-graining the evolutionary dynamics of a system of nonidentical oscillators coupled through a (fixed) network structure. The existence of a spectral gap for the coupling network graph…

Statistical Mechanics · Physics 2015-05-28 Karthikeyan Rajendran , Ioannis G. Kevrekidis

We modify the Kuramoto model for synchronization on complex networks by introducing a gauge term that depends on the edge betweenness centrality (BC). The gauge term introduces additional phase difference between two vertices from 0 to…

Disordered Systems and Neural Networks · Physics 2009-11-13 E. OH , C. Choi , B. Kahng , D. Kim

We present a new fully dynamic algorithm for maintaining betweenness centrality (BC) of vertices in a directed graph $G=(V,E)$ with positive edge weights. BC is a widely used parameter in the analysis of large complex networks. We achieve…

Data Structures and Algorithms · Computer Science 2022-04-21 Matteo Pontecorvi , Vijaya Ramachandran

This paper introduces a simple measure of a concordance pattern among observed outcomes along a network, i.e., the pattern in which adjacent outcomes tend to be more strongly correlated than non-adjacent outcomes. The graph concordance…

Methodology · Statistics 2017-09-04 Kyungchul Song

We have simulated the non-linear dynamics of networks of spin-transfer oscillators. The oscillators are magnetically uncoupled but electrically connected in series. We use a modified Landau-Lifschitz- Gilbert equation to describe the motion…

Materials Science · Physics 2009-11-11 J. Grollier , V. Cros , A. Fert

Systems that synchronize in nature are intrinsically different from one another, with possibly large differences from system to system. While a vast part of the literature has investigated the emergence of network synchronization for the…

Systems and Control · Electrical Eng. & Systems 2023-09-01 Amirhossein Nazerian , Shirin Panahi , Francesco Sorrentino

Dynamics on networks are often characterized by the second smallest eigenvalue of the Laplacian matrix of the network, which is called the spectral gap. Examples include the threshold coupling strength for synchronization and the relaxation…

Disordered Systems and Neural Networks · Physics 2010-11-01 Takamitsu Watanabe , Naoki Masuda

The dynamics of power-grid networks is becoming an increasingly active area of research within the physics and network science communities. The results from such studies are typically insightful and illustrative, but are often based on…

Physics and Society · Physics 2021-09-24 Takashi Nishikawa , Adilson E. Motter

Longitudinal binary relational data can be better understood by implementing a latent space model for dynamic networks. This approach can be broadly extended to many types of weighted edges by using a link function to model the mean of the…

Methodology · Statistics 2020-05-19 Daniel K. Sewell , Yuguo Chen
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