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In many real, directed networks, the strongly connected component of nodes which are mutually reachable is very small. This does not fit with current theory, based on random graphs, according to which strong connectivity depends on mean…

Disordered Systems and Neural Networks · Physics 2023-04-12 Niall Rodgers , Peter Tino , Samuel Johnson

It is well established that the phase transition between survival and extinction in spreading models with short-range interactions is generically associated with the directed percolation (DP) universality class. In many realistic spreading…

Statistical Mechanics · Physics 2009-11-13 Hans-Karl Janssen , Olaf Stenull

Biased (degree-dependent) percolation was recently shown to provide new strategies for turning robust networks fragile and vice versa. Here we present more detailed results for biased edge percolation on scale-free networks. We assume a…

We introduce a percolation model on $\mathbb{Z}^d$, $d \geq 3$, in which the discrete lines of vertices that are parallel to the coordinate axis are entirely removed at random and independently of each other. In this way a vertex belongs to…

Probability · Mathematics 2015-09-22 Marcelo R. Hilário , Vladas Sidoravicius

We study the contact process on spatially embedded networks, consisting of a regular square lattice with long-range connections. To generate the networks, a long-range connection is randomly added to each node $i$ of a square lattice,…

Statistical Mechanics · Physics 2018-09-26 T. B. dos Santos , C. I. N. Sampaio Filho , N. A. M. Araújo , C. L. N. Oliveira , A. A. Moreira

Boolean networks, widely used to model gene regulation, exhibit a phase transition between regimes in which small perturbations either die out or grow exponentially. We show and numerically verify that this phase transition in the dynamics…

Statistical Mechanics · Physics 2013-05-30 Shane Squires , Edward Ott , Michelle Girvan

The micro-structure of the giant component of the Erd{\H o}s-R\'enyi network and other configuration model networks is analyzed using generating function methods. While configuration model networks are uncorrelated, the giant component…

Statistical Mechanics · Physics 2018-04-30 Ido Tishby , Ofer Biham , Eytan Katzav , Reimer Kühn

Percolation on networks is a common framework to model a wide range of processes, from cascading failures to epidemic spreading. Standard percolation assumes short-range interactions, implying that nodes can merge into clusters only if they…

Statistical Mechanics · Physics 2024-05-01 Lorenzo Cirigliano , Giulio Cimini , Romualdo Pastor-Satorras , Claudio Castellano

Understanding the resilience of infrastructures such as transportation network has significant importance for our daily life. Recently, a homogeneous spatial network model was developed for studying spatial embedded networks with…

Physics and Society · Physics 2020-06-24 Bnaya Gross , Dana Vaknin , Sergey V. Buldyrev , Shlomo Havlin

Networks are fundamental for our understanding of complex systems. Interactions between individual nodes in networks generate network motifs - small recurrent patterns that can be considered the network's building-block components,…

Dynamical Systems · Mathematics 2022-09-14 Miri Adler , Ruslan Medzhitov

We study a general class of percolation models in Euclidean space including long-range percolation, scale-free percolation, the weight-dependent random connection model and several other previously investigated models. Our focus is on the…

Probability · Mathematics 2023-03-08 Christian Mönch

We propose a continuum model of percolation in two dimensions for overlapping disks with spin. In this model the existence of bonds is determined by the distance between the centers of the disks, and by the scalar product of the (randomly)…

Statistical Mechanics · Physics 2016-06-01 Francesco Caravelli , Marco Bardoscia , Fabio Caccioli

Many real-world networks exhibit the so-called small-world phenomenon: their typical distances are much smaller than their sizes. One mathematical model for this phenomenon is a long-range percolation graph on a $d$-dimensional box $\{0, 1,…

Probability · Mathematics 2022-11-30 Tianqi Wu

The voter model is a classical interacting particle system, modelling how global consensus is formed by local imitation. We analyse the time to consensus for a particular family of voter models when the underlying structure is a scale-free…

Probability · Mathematics 2024-01-11 John Fernley

Percolation refers to the emergence of a giant connected cluster in a disordered system when the number of connections between nodes exceeds a critical value. The percolation phase transitions were believed to be continuous until recently…

Disordered Systems and Neural Networks · Physics 2015-02-13 R. A. da Costa , S. N. Dorogovtsev , A. V. Goltsev , J. F. F. Mendes

Large-deviations theory deals with tails of probability distributions and the rare events of random processes, for example spreading packets of particles. Mathematically, it concerns the exponential fall-of of the density of thin-tailed…

Statistical Mechanics · Physics 2017-07-04 Erez Aghion , David A. Kessler , Eli Barkai

The ability to achieve coordinated behavior --engineered or emergent-- on networked systems has attracted widespread interest over several fields. This has led to remarkable advances on the development of a theoretical understanding of the…

Systems and Control · Computer Science 2019-09-16 Hancheng Min , Enrique Mallada

A fundamental premise of statistical physics is that the particles in a physical system are interchangeable, and hence the state of each specific component is representative of the system as a whole. This assumption breaks down for complex…

Physics and Society · Physics 2025-12-16 Neil G. MacLaren , Baruch Barzel , Naoki Masuda

Bond percolation on infinite heavy-tailed power-law random networks lacks a proper phase transition; or one may say, there is a phase transition at {\em zero percolation probability}. Nevertheless, a finite size percolation threshold…

Disordered Systems and Neural Networks · Physics 2007-05-23 Nima Sarshar , Patrick Oscar Boykin , Vwani P. Roychowdhury

We apply a variant of the explosive percolation procedure to large real-world networks, and show with finite-size scaling that the university class, ordinary or explosive, of the resulting percolation transition depends on the structural…

Disordered Systems and Neural Networks · Physics 2011-04-19 Raj Kumar Pan , Mikko Kivelä , Jari Saramäki , Kimmo Kaski , János Kertész