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Percolation theory characterizing the robustness of a network has applications ranging from biology, to epidemic spreading, and complex infrastructures. Percolation theory, however, only concern the typical response of a infinite network to…

Disordered Systems and Neural Networks · Physics 2018-02-28 Ginestra Bianconi

We address the problem of message transfer in a communication network. The network consists of nodes and links, with the nodes lying on a two dimensional lattice. Each node has connections with its nearest neighbours, whereas some special…

Statistical Mechanics · Physics 2007-05-23 Brajendra K. Singh , Neelima M. Gupte

We study three preferential attachment models where the parameters are such that the asymptotic degree distribution has infinite variance. Every edge is equipped with a non-negative i.i.d. weight. We study the weighted distance between two…

Probability · Mathematics 2021-12-16 Joost Jorritsma , Júlia Komjáthy

We consider first passage percolation (FPP) with passage times generated by a general class of models with long-range correlations on $\mathbb{Z}^d$, $d\geq 2$, including discrete Gaussian free fields, Ginzburg-Landau $\nabla \phi$…

Probability · Mathematics 2024-05-21 Sebastian Andres , Alexis Prévost

We examine the heterogeneous responses of individual nodes in sparse networks to the random removal of a fraction of edges. Using the message-passing formulation of percolation, we discover considerable variation across the network in the…

Statistical Mechanics · Physics 2017-09-13 Reimer Kuehn , Tim Rogers

We study the entanglement entropy of a random tensor network (RTN) using tools from free probability theory. Random tensor networks are simple toy models that help the understanding of the entanglement behavior of a boundary region in the…

Quantum Physics · Physics 2024-07-04 Khurshed Fitter , Faedi Loulidi , Ion Nechita

In this paper we study the impact of random exponential edge weights on the distances in a random graph and, in particular, on its diameter. Our main result consists of a precise asymptotic expression for the maximal weight of the shortest…

Probability · Mathematics 2015-04-17 Hamed Amini , Marc Lelarge

We review results on the scaling of the optimal path length in random networks with weighted links or nodes. In strong disorder we find that the length of the optimal path increases dramatically compared to the known small world result for…

Disordered Systems and Neural Networks · Physics 2015-06-25 L. A. Braunstein , Z. Wu , Y. Chen , S. V. Buldyrev , S. Sreenivasan , T. Kalisky , R. Cohen , E. Lopez , S. Havlin , H. E. Stanley

Let a random geometric graph be defined in the supercritical regime for the existence of a unique infinite connected component in Euclidean space. Consider the first-passage percolation model with independent and identically distributed…

We consider propagation models that describe the spreading of an attribute, called "damage", through the nodes of a random network. In some systems, the average fraction of nodes that remain undamaged vanishes in the large system limit, a…

Cellular Automata and Lattice Gases · Physics 2007-05-23 Björn Samuelsson , Joshua E. S. Socolar

We consider i.i.d. first-passage percolation (FPP) on the two-dimensional square lattice, in the critical case where edge-weights take the value zero with probability $\tfrac{1}{2}$. Critical FPP is unique in that the Euclidean lengths of…

Probability · Mathematics 2025-09-09 Erik Bates , David Harper , Xiao Shen , Evan Sorensen

The self averaging properties of conductance $g$ are explored in random resistor networks with a broad distribution of bond strengths $P(g)\simg^{\mu-1}$. Distributions of equivalent conductances are estimated numerically on hierarchical…

Condensed Matter · Physics 2009-10-22 R. F. Angulo , E. Medina

In this paper, we derive cumulant bounds for subgraph counts and power-weighted edge length in a class of spatial random networks known as weighted random connection models. This involves dealing with long-range spatial correlations induced…

Probability · Mathematics 2023-11-02 Nils Heerten , Christian Hirsch , Moritz Otto

Recently increasing attention has been addressed to the fluctuations observed in percolation defined in single and multiplex networks. These fluctuations are extremely important to characterize the robustness of real finite networks but…

Disordered Systems and Neural Networks · Physics 2019-08-21 Ginestra Bianconi

Random walks constitute a fundamental mechanism for a large set of dynamics taking place on networks. In this article, we study random walks on weighted networks with an arbitrary degree distribution, where the weight of an edge between two…

Statistical Mechanics · Physics 2013-01-17 Zhongzhi Zhang , Tong Shan , Guanrong Chen

The first passage time (FPT) distribution for random walk in complex networks is calculated through an asymptotic analysis. For network with size $N$ and short relaxation time $\tau\ll N$, the computed mean first passage time (MFPT), which…

Statistical Mechanics · Physics 2013-01-29 Hon Wai Lau , Kwok Yip Szeto

In this paper, we consider the random walk process on a kind of fractal (or transfractal) scale free networks, which also called as $(u,v)$ flowers, and we focus on the global first passage time (GFPT) and first return time (FRT). Here, we…

Statistical Mechanics · Physics 2016-10-27 Junhao Peng

The edges in networks are not only binary, either present or absent, but also take weighted values in many scenarios (e.g., the number of emails between two users). The covariate-$p_0$ model has been proposed to model binary directed…

Statistics Theory · Mathematics 2021-07-24 MengXu , Qiuping Wang

We present general methods to exactly calculate mean-first passage quantities on self-similar networks defined recursively. In particular, we calculate the mean first-passage time and the splitting probabilities associated to a source and…

Statistical Mechanics · Physics 2015-06-04 B. Meyer , E. Agliari , O. Bénichou , R. Voituriez

The Euclidean first-passage percolation (FPP) model of Howard and Newman is a rotationally invariant model of FPP which is built on a graph whose vertices are the points of homogeneous Poisson point process. It was shown that one has…

Probability · Mathematics 2016-11-01 Michael Damron , Xuan Wang