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We demonstrate that graphs embedded on surfaces are a powerful and practical tool to generate, characterize and simulate networks with a broad range of properties. Remarkably, the study of topologically embedded graphs is non-restrictive…

Other Condensed Matter · Physics 2015-03-19 Tomaso Aste , Ruggero Gramatica , T. Di Matteo

This paper deals with dynamical networks for which the relations between node signals are described by proper transfer functions and external signals can influence each of the node signals. We are interested in graph-theoretic conditions…

Optimization and Control · Mathematics 2019-12-02 Henk J. van Waarde , Pietro Tesi , M. Kanat Camlibel

The function of a real network depends not only on the reliability of its own components, but is affected also by the simultaneous operation of other real networks coupled with it. Robustness of systems composed of interdependent network…

Physics and Society · Physics 2015-07-10 Filippo Radicchi

A fundamental problem in the study of complex networks is to provide quantitative measures of correlation and information flow between different parts of a system. To this end, several notions of communicability have been introduced and…

Physics and Society · Physics 2015-04-08 Ernesto Estrada , Naomichi Hatano , Michele Benzi

The fractal nature of graphs has traditionally been investigated by using the nodes of networks as the basic units. Here, instead, we propose to concentrate on the graph edges, and introduce a practical and computationally not demanding…

Physics and Society · Physics 2017-04-05 Sarika Jalan , Alok Yadav , Camellia Sarkar , Stefano Boccaletti

The behavior of complex systems is determined not only by the topological organization of their interconnections but also by the dynamical processes taking place among their constituents. A faithful modeling of the dynamics is essential…

Physics and Society · Physics 2015-05-20 R. Lambiotte , R. Sinatra , J. -C. Delvenne , T. S. Evans , M. Barahona , V. Latora

Graph neural networks (GNNs) have demonstrated significant promise in modelling relational data and have been widely applied in various fields of interest. The key mechanism behind GNNs is the so-called message passing where information is…

Machine Learning · Computer Science 2023-10-31 Andi Han , Dai Shi , Lequan Lin , Junbin Gao

The concept of communicability is introduced for complex socio-economic networks. The communicability function expresses how an impact propagates from one place to another in the network. This function is used to define unambiguously the…

Physics and Society · Physics 2015-04-24 Ernesto Estrada , Naomichi Hatano

In many systems consisting of interacting subsystems, the complex interactions between elements can be represented using multilayer networks. However percolation, key to understanding connectivity and robustness, is not trivially…

Disordered Systems and Neural Networks · Physics 2020-11-04 G. J. Baxter , R. A. da Costa , S. N. Dorogovtsev , J. F. F. Mendes

We analyze how the transient dynamics of large dynamical systems in the vicinity of a stationary point, modeled by a set of randomly coupled linear differential equations, depends on the network topology. We characterize the transient…

Adaptation and Self-Organizing Systems · Physics 2024-01-17 Wojciech Tarnowski , Izaak Neri , Pierpaolo Vivo

Many processes of spreading and diffusion take place on temporal networks, and their outcomes are influenced by correlations in the times of contact. These correlations have a particularly strong influence on processes where the spreading…

Physics and Society · Physics 2017-09-19 Mikko Kivelä , Jordan Cambe , Jari Saramäki , Márton Karsai

Percolation on complex networks is used both as a model for dynamics on networks, such as network robustness or epidemic spreading, and as a benchmark for our models of networks, where our ability to predict percolation measures our ability…

Physics and Society · Physics 2019-08-21 Laurent Hébert-Dufresne , Antoine Allard

We study information flow on a weighted graph whose topology evolves according to a spectral curvature measure $\mathcal{R}$. The model (FIU) defines $\mathcal{R}$ from the diagonal of the graph Green function, propagates energy with…

Statistical Mechanics · Physics 2026-03-17 Valerio Dolci

We numerically investigate jamming transitions in complex heterogeneous networks. Inspired by Internet routing protocols, we study a general model that incorporates local traffic information through a tunable parameter. The results show…

Statistical Mechanics · Physics 2007-05-23 Pablo Echenique , Jesus Gomez-Gardenes , Yamir Moreno

As a quantification of the main bottleneck to flow over a graph, the network property of conductance plays an important role in the process of synchronization of network-coupled dynamical systems. Diffusive coupling terms serve not only to…

Physics and Society · Physics 2025-10-29 C. Tyler Diggans

To provide a phenomenological theory for the various interesting transitions in restructuring networks we employ a statistical mechanical approach with detailed balance satisfied for the transitions between topological states. This enables…

Statistical Mechanics · Physics 2007-05-23 Imre Derenyi , Illes Farkas , Gergely Palla , Tamas Vicsek

We analyze critical phenomena on networks generated as the union of hidden variables models (networks with any desired degree sequence) with arbitrary graphs. The resulting networks are general small-worlds similar to those a` la Watts and…

Disordered Systems and Neural Networks · Physics 2011-06-29 M. Ostilli , A. L. Ferreira , J. F. F. Mendes

The congestion formation on a urban road network is one of the key issue for the development of a sustainable mobility in the future smart cities. In this work we propose a reductionist approach studying the stationary states of a simple…

Physics and Society · Physics 2024-05-28 Lorenzo Di Meco , Mirko Degli Esposti , Federico Bellisardi , Armando Bazzani

Effective information analysis generally boils down to properly identifying the structure or geometry of the data, which is often represented by a graph. In some applications, this structure may be partly determined by design constraints or…

Machine Learning · Computer Science 2016-11-07 Dorina Thanou , Xiaowen Dong , Daniel Kressner , Pascal Frossard

We study the urban-scale macroscopic traffic flow in city networks. Star graph is considered as traffic network. Star graphs with controlled traffic flow are transformed to various cell-transmission graphs by using the cell transmission…

Adaptation and Self-Organizing Systems · Physics 2019-12-10 Takashi Nagatani