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Percolation is a model for random damage to a network. It is one of the simplest models that displays a phase transition: when the network is severely damaged, it falls apart in many small connected components, while if the damage is light,…

Probability · Mathematics 2025-12-18 Remco van der Hofstad

We introduce models of generic rigidity percolation in two dimensions on hierarchical networks, and solve them exactly by means of a renormalization transformation. We then study how the possibility for the network to self organize in order…

Statistical Mechanics · Physics 2015-05-13 J. Barré

Networked structures arise in a wide array of different contexts such as technological and transportation infrastructures, social phenomena, and biological systems. These highly interconnected systems have recently been the focus of a great…

Statistical Mechanics · Physics 2009-11-10 Alain Barrat , Marc Barthelemy , Romualdo Pastor-Satorras , Alessandro Vespignani

Networks embedded in space can display all sorts of transitions when their structure is modified. The nature of these transitions (and in some cases crossovers) can differ from the usual appearance of a giant component as observed for the…

Statistical Mechanics · Physics 2018-12-19 Marc Barthelemy

We study a minimal model of traffic flows in complex networks, simple enough to get analytical results, but with a very rich phenomenology, presenting continuous, discontinuous as well as hybrid phase transitions between a free-flow phase…

Statistical Mechanics · Physics 2015-05-13 Daniele De Martino , Luca Dall'Asta , Ginestra Bianconi , Matteo Marsili

The study of random graphs has become very popular for real-life network modeling such as social networks or financial networks. Inhomogeneous long-range percolation (or scale-free percolation) on the lattice $\mathbb Z^d$, $d\ge1$, is a…

Probability · Mathematics 2014-09-29 Philippe Deprez , Rajat Subhra Hazra , Mario V. Wüthrich

We introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the…

Disordered Systems and Neural Networks · Physics 2015-05-13 Roni Parshani , Mark Dickison , Reuven Cohen , H. Eugene Stanley , Shlomo Havlin

The critical infrastructures of the nation such as the power grid and the communication network are highly interdependent. Also, it has been observed that there exists complex interdependent relationships between individual entities of the…

Physics and Society · Physics 2017-02-20 Joydeep Banerjee , Arun Das , Arunabha Sen

Higher order interactions are increasingly recognised as a fundamental aspect of complex systems ranging from the brain to social contact networks. Hypergraph as well as simplicial complexes capture the higher-order interactions of complex…

Physics and Society · Physics 2021-09-23 Hanlin Sun , Ginestra Bianconi

Understanding how biological constraints shape neural computation is a central goal of computational neuroscience. Spatially embedded recurrent neural networks provide a promising avenue to study how modelled constraints shape the combined…

Neural and Evolutionary Computing · Computer Science 2024-09-27 Cornelia Sheeran , Andrew S. Ham , Duncan E. Astle , Jascha Achterberg , Danyal Akarca

Recently much attention has been paid to the study of the robustness of interdependent and multiplex networks and, in particular, networks of networks. The robustness of interdependent networks can be evaluated by the size of a mutually…

Statistical Mechanics · Physics 2015-06-18 Ginestra Bianconi , Sergey N. Dorogovtsev

Road networks are characterised by several structural and geometric properties. Their topological structure determines partially its hierarchical arrangement, but since these are networks that are spatially situated and, therefore,…

Physics and Society · Physics 2017-01-30 Carlos Molinero , Roberto Murcio , Elsa Arcaute

Real data show that interdependent networks usually involve inter-similarity. Intersimilarity means that a pair of interdependent nodes have neighbors in both networks that are also interdependent (Parshani et al \cite{PAR10B}). For…

Physics and Society · Physics 2015-06-16 Yanqing Hu , Dong Zhou , Rui Zhang , Zhangang Han , Shlomo Havlin

A major challenge in flow through porous media is to better understand the link between microstructure and macroscale flow and transport. For idealised microstructures, the mathematical framework of homogenisation theory can be used for…

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 consider robustness and percolation properties of the networks of networks, in which random nodes in different individual networks (layers) can be interdependent. We explore the emergence of the giant mutually connected component,…

Disordered Systems and Neural Networks · Physics 2014-11-18 Ginestra Bianconi , Sergey N. Dorogovtsev

Models of street networks underlie research in urban travel behavior, accessibility, design patterns, and morphology. These models are commonly defined as planar, meaning they can be represented in two dimensions without any underpasses or…

Physics and Society · Physics 2018-11-21 Geoff Boeing

Communication networks, power grids, and transportation networks are all examples of networks whose performance depends on reliable connectivity of their underlying network components even in the presence of usual network dynamics due to…

Physics and Society · Physics 2020-06-26 Arman Mohseni-Kabir , Mihir Pant , Don Towsley , Saikat Guha , Ananthram Swami

Experimental results for covalent glasses have highlighted the existence of a new self-organized phase due to the tendency of glass networks to minimize internal stress. Recently, we have shown that an equilibrated self-organized…

Disordered Systems and Neural Networks · Physics 2009-11-11 M. -A. Briere , M. V. Chubynsky , Normand Mousseau

We present an analytical approach for bond percolation on multiplex networks and use it to determine the expected size of the giant connected component and the value of the critical bond occupation probability in these networks. We advocate…

Physics and Society · Physics 2016-04-13 A. Hackett , D. Cellai , S. Gómez , A. Arenas , J. P. Gleeson