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An analytical approach to network dynamics is used to show that when agents copy their state randomly the network arrives to a stationary status in which the distribution of states is independent of the agents degree. The effects of network…

Disordered Systems and Neural Networks · Physics 2009-11-10 Cesar A. Hidalgo , Francisco Claro , Pablo A. Marquet

The random walk process underlies the description of a large number of real world phenomena. Here we provide the study of random walk processes in time varying networks in the regime of time-scale mixing; i.e. when the network connectivity…

Detecting abrupt changes in streaming graph signals is relevant in a variety of applications ranging from energy and water supplies, to environmental monitoring. In this paper, we address this problem when anomalies activate localized…

Signal Processing · Electrical Eng. & Systems 2019-10-16 André Ferrari , Cédric Richard , Louis Verduci

We investigate a model for spatial epidemics explicitly taking into account bi-directional movements between base and destination locations on individual mobility networks. We provide a systematic analysis of generic dynamical features of…

Physics and Society · Physics 2012-03-07 Vitaly Belik , Theo Geisel , Dirk Brockmann

The availability of new data sources on human mobility is opening new avenues for investigating the interplay of social networks, human mobility and dynamical processes such as epidemic spreading. Here we analyze data on the time-resolved…

Consider a graph where the sites are distributed in space according to a Poisson point process on $\mathbb R^n$. We study a population evolving on this network, with individuals jumping between sites with a rate which decreases…

Probability · Mathematics 2023-04-05 Vincent Bansaye , Michele Salvi

Much recent research has dealt with the identifiability of a dynamical network in which the node signals are connected by causal linear transfer functions and are excited by known external excitation signals and/or unknown noise signals. A…

Optimization and Control · Mathematics 2018-03-18 Julien M. Hendrickx , Michel Gevers , Alexandre S. Bazanella

Understanding how complex behaviors, opinions, and innovations spread in online social networks remains a central challenge in computational social science. Existing models of complex contagion typically rely on stylized threshold…

Social and Information Networks · Computer Science 2026-03-20 Saurabh Sharma , Ambuj Singh

Can evolving networks be inferred and modeled without directly observing their nodes and edges? In many applications, the edges of a dynamic network might not be observed, but one can observe the dynamics of stochastic cascading processes…

Machine Learning · Computer Science 2019-02-26 Elahe Ghalebi , Baharan Mirzasoleiman , Radu Grosu , Jure Leskovec

Existence of Anderson localization is considered a manifestation of coherence of classical and quantum waves in disordered systems. Signatures of localization have been observed in condensed matter and cold atomic systems where the coupling…

Disordered Systems and Neural Networks · Physics 2023-08-22 Alejandro Cros Carrillo de Albornoz , Dominic C. Rose , Arijeet Pal

In the last two decades, network science has blossomed and influenced various fields, such as statistical physics, computer science, biology and sociology, from the perspective of the heterogeneous interaction patterns of components…

Physics and Society · Physics 2021-04-20 Ming Li , Run-Ran Liu , Linyuan Lü , Mao-Bin Hu , Shuqi Xu , Yi-Cheng Zhang

Time-limited states characterise many dynamical processes on networks: disease infected individuals recover after some time, people forget news spreading on social networks, or passengers may not wait forever for a connection. These…

Physics and Society · Physics 2023-06-13 Arash Badie-Modiri , Márton Karsai , Mikko Kivelä

Over the last two decades, network science has greatly advanced our understanding of how the collective behaviors of a complex system emerge from the interactions among its basic units. Multiplex networks, i.e. networks with many layers,…

We study the transition between layer-localized and delocalized regimes in a general contact-based contagion model on multiplex networks. Using the inverse participation ratio, we characterize how activity shifts from being confined to a…

Physics and Society · Physics 2025-10-21 Joan Hernàndez Tey , Emanuele Cozzo

Dynamical reaction-diffusion processes and meta-population models are standard modeling approaches for a wide variety of phenomena in which local quantities - such as density, potential and particles - diffuse and interact according to the…

Statistical Mechanics · Physics 2007-05-23 V. Colizza , R. Pastor-Satorras , A. Vespignani

Extreme events have low occurrence probabilities and display pronounced deviation from their average behaviour, such as earthquakes or power blackouts. Such extreme events occurring on the nodes of a complex network have been extensively…

Physics and Society · Physics 2022-02-09 Govind Gandhi , M. S. Santhanam

The analysis of multilayer networks is among the most active areas of network science, and there are now several methods to detect dense "communities" of nodes in multilayer networks. One way to define a community is as a set of nodes that…

Social and Information Networks · Computer Science 2016-05-24 Lucas G. S. Jeub , Michael W. Mahoney , Peter J. Mucha , Mason A. Porter

Different from most existing distributed localization approaches in static networks where the agents in a network are static, this paper addresses the distributed localization problem in dynamic networks where the positions of the agents…

Systems and Control · Electrical Eng. & Systems 2023-12-19 Xu Fang , Lihua Xie , Xiaolei Li

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization…

Physics and Society · Physics 2009-09-29 Alex Arenas , Albert Diaz-Guilera , Jurgen Kurths , Yamir Moreno , Changsong Zhou

The largest eigenvalue of the adjacency matrix of the networks is a key quantity determining several important dynamical processes on complex networks. Based on this fact, we present a quantitative, objective characterization of the…

Disordered Systems and Neural Networks · Physics 2009-11-11 J. G. Restrepo , E. Ott , B. R. Hunt
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