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Maxmin-$\omega$ is a new threshold model, where each node in a network waits for the arrival of states from a fraction $\omega$ of neighborhood nodes before processing its own state, and subsequently transmitting it to downstream nodes.…

Physics and Society · Physics 2021-09-24 Ebrahim L. Patel

Suppose that under the action of gravity, liquid drains through the unit $d$-cube via a minimal-length network of channels constrained to pass through random sites and to flow with nonnegative component in one of the canonical orthogonal…

Probability · Mathematics 2010-09-01 Mathew D. Penrose , Andrew R. Wade

In this paper, the relationship between the network synchronizability and the edge distribution of its associated graph is investigated. First, it is shown that adding one edge to a cycle definitely decreases the network sychronizability.…

Networking and Internet Architecture · Computer Science 2007-11-16 Zhisheng Duan , Wenxu Wang , Chao Liu , Guanrong Chen

In order to conduct analyses of networked systems where connections between individuals take on a range of values - counts, continuous strengths or ordinal rankings - a common technique is to dichotomize the data according to their…

Applications · Statistics 2015-03-17 Andrew C. Thomas , Joseph K. Blitzstein

We analyze analytically the effect of congestion costs within a physically relevant, yet exactly solvable network model featuring central hubs. These costs lead to a competition between centralized and decentralized transport pathways. In…

Disordered Systems and Neural Networks · Physics 2009-11-10 Douglas J. Ashton , Timothy C. Jarrett , Neil F. Johnson

The classical friendship paradox asserts that, on average, an individual's neighbors have a higher degree than the individual. This statement concerns network-level means and does not describe how often a typical node is locally dominated…

Physics and Society · Physics 2026-04-22 Sang Hoon Lee

Recurrence networks are complex networks, constructed from time series data, having several practical applications. Though their properties when constructed with the threshold value \epsilon chosen at or just above the percolation threshold…

Chaotic Dynamics · Physics 2016-07-19 Rinku Jacob , K. P. Harikrishnan , R. Misra , G. Ambika

The coexistence of sparsity and clustering (non-vanishing average fraction of triangles per node) is one of the few structural features that, irrespective of finer details, are ubiquitously observed across large real-world networks. This…

Probability · Mathematics 2026-03-17 Alessio Catanzaro , Remco van der Hofstad , Diego Garlaschelli

Many complex networks display strong heterogeneity in the degree (connectivity) distribution. Heterogeneity in the degree distribution often reduces the average distance between nodes but, paradoxically, may suppress synchronization in…

Disordered Systems and Neural Networks · Physics 2007-05-23 Adilson E. Motter , Changsong Zhou , Juergen Kurths

Knowing which parts of a complex system have identical roles simplifies computations and reveals patterns in its network structure. Group theory has been applied to study symmetries in unweighted networks. However, in real-world weighted…

Physics and Society · Physics 2025-06-16 Julia Korol , Mateusz Iskrzyński

The structure and design of optimal supply networks is an important topic in complex networks research. A fundamental trait of natural and man-made networks is the emergence of loops and the trade-off governing their formation: adding…

Physics and Society · Physics 2020-11-25 Franz Kaiser , Henrik Ronellenfitsch , Dirk Witthaut

Dependency networks (Heckerman et al., 2000) are potential probabilistic graphical models for systems comprising a large number of variables. Like Bayesian networks, the structure of a dependency network is represented by a directed graph,…

Machine Learning · Computer Science 2021-07-05 Kazuya Takabatake , Shotaro Akaho

A geodesic cycle in a graph is a cycle with no shortcuts, so that the shortest path between any two nodes in the cycle is the path along the cycle itself. A recently published paper used random graph models to investigate the geodesic cycle…

Social and Information Networks · Computer Science 2023-03-22 Alex Stivala

We study the growth of random networks under a constraint that the diameter, defined as the average shortest path length between all nodes, remains approximately constant. We show that if the graph maintains the form of its degree…

Statistical Mechanics · Physics 2007-05-23 Rajan M. Lukose , Lada A. Adamic

One abstract method for the study of network transportation is proposed in this paper. By interpolating the properties of the edges that constitute network into the two leading parameters of the nodes, this method can abstract the…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Chang Yun-Feng , Xu Cai

In the standard CONGEST model for distributed network computing, it is known that "global" tasks such as minimum spanning tree, diameter, and all-pairs shortest paths, consume large bandwidth, for their running-time is…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-06-14 Pierre Fraigniaud , Pedro Montealegre , Dennis Olivetti , Ivan Rapaport , Ioan Todinca

Complex networks are made up of vertices and edges. The latter connect the vertices. There are several ways to measure the importance of the vertices, e.g., by counting the number of edges that start or end at each vertex, or by using the…

Physics and Society · Physics 2024-07-08 Silvia Noschese , Lothar Reichel

Series-parallel network topologies generally exhibit simplified dynamical behavior and avoid high combinatorial complexity. A comprehensive analysis of how flow complexity emerges with a graph's deviation from series-parallel topology is…

Systems and Control · Electrical Eng. & Systems 2024-03-12 Shashank A Deshpande , Hamsa Balakrishnan

In this paper we study the small-world network model of Watts and Strogatz, which mimics some aspects of the structure of networks of social interactions. We argue that there is one non-trivial length-scale in the model, analogous to the…

Statistical Mechanics · Physics 2009-10-31 M. E. J. Newman , D. J. Watts

An important task in network analysis is the detection of anomalous events in a network time series. These events could merely be times of interest in the network timeline or they could be examples of malicious activity or network…

Machine Learning · Computer Science 2016-08-03 Timothy La Fond , Jennifer Neville , Brian Gallagher
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