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We deal with a random graph model where at each step, a vertex is chosen uniformly at random, and it is either duplicated or its edges are deleted. Duplication has a given probability. We analyse the limit distribution of the degree of a…

Probability · Mathematics 2014-09-19 Ágnes Backhausz , Tamás F. Móri

A simple random walk on a graph is a sequence of movements from one vertex to another where at each step an edge is chosen uniformly at random from the set of edges incident on the current vertex, and then transitioned to next vertex.…

Probability · Mathematics 2012-02-28 Mohammed Abdullah

Continuous-time branching processes (CTBPs) are powerful tools in random graph theory, but are not appropriate to describe real-world networks, since they produce trees rather than (multi)graphs. In this paper we analyze collapsed branching…

Probability · Mathematics 2017-11-10 Alessandro Garavaglia , Remco van der Hofstad

We study locally interacting processes in discrete time, often called probabilistic cellular automata, indexed by locally finite graphs. For infinite regular trees and certain generalized Galton-Watson trees, we show that the marginal…

Probability · Mathematics 2025-10-28 Daniel Lacker , Kavita Ramanan , Ruoyu Wu

Random geometric graphs consist of randomly distributed nodes (points), with pairs of nodes within a given mutual distance linked. In the usual model the distribution of nodes is uniform on a square, and in the limit of infinitely many…

Disordered Systems and Neural Networks · Physics 2018-09-27 Carl P. Dettmann

Suppose that $G_j$ is a sequence of finite connected planar graphs, and in each $G_j$ a special vertex, called the root, is chosen randomly-uniformly. We introduce the notion of a distributional limit $G$ of such graphs. Assume that the…

Probability · Mathematics 2008-11-26 Itai Benjamini , Oded Schramm

We present a general approach to study the flooding time (a measure of how fast information spreads) in dynamic graphs (graphs whose topology changes with time according to a random process). We consider arbitrary converging Markovian…

Discrete Mathematics · Computer Science 2015-03-19 Andrea Clementi , Riccardo Silvestri , Luca Trevisan

A random graph model with prescribed degree distribution and degree dependent edge weights is introduced. Each vertex is independently equipped with a random number of half-edges and each half-edge is assigned an integer valued weight…

Probability · Mathematics 2015-05-28 Tom Britton , Maria Deijfen , Fredrik Liljeros

We introduce a natural generalization of the Erd\H{o}s-R\'enyi random graph model in which random instances of a fixed motif are added independently. The binomial random motif graph $G(H,n,p)$ is the random (multi)graph obtained by adding…

Combinatorics · Mathematics 2019-07-30 Michael Anastos , Peleg Michaeli , Samantha Petti

Consider a finite inhomogeneous random graph running in continuous time, where each vertex has a mass, and the edge that links any pair of vertices appears with a rate equal to the product of their masses. The simultaneous…

Probability · Mathematics 2023-11-09 Josué Corujo , Vlada Limic

We study the random graph G_{n,\lambda/n} conditioned on the event that all vertex degrees lie in some given subset S of the non-negative integers. Subject to a certain hypothesis on S, the empirical distribution of the vertex degrees is…

Probability · Mathematics 2007-12-04 Geoffrey Grimmett , Svante Janson

In this paper, we analyze the dynamics of spreading processes taking place over time-varying networks. A common approach to model time-varying networks is via Markovian random graph processes. This modeling approach presents the following…

Social and Information Networks · Computer Science 2016-11-04 Masaki Ogura , Victor M. Preciado

We prove that the restriction of the vertex-reinforced jump process to a subset of the vertex set is a mixture of vertex-reinforced jump processes. A similar statement holds for the non-linear hyperbolic supersymmetric sigma model. This is…

Probability · Mathematics 2024-11-12 Margherita Disertori , Franz Merkl , Silke W. W. Rolles

In the stochastic network model of Britton and Lindholm [Dynamic random networks in dynamic populations. Journal of Statistical Physics, 2010], the number of individuals evolves according to a supercritical linear birth and death process,…

Probability · Mathematics 2018-07-05 Fabian Kück , Dominic Schuhmacher

We study a model of growing planar tree graphs where in each time step we separate the tree into two components by splitting a vertex and then connect the two pieces by inserting a new link between the daughter vertices. This model…

Statistical Mechanics · Physics 2009-11-13 Francois David , Mark Dukes , Thordur Jonsson , Sigurdur Orn Stefansson

Consider a 2-dimensional soft random geometric graph $G(\lambda,s,\phi)$, obtained by placing a Poisson($\lambda s^2$) number of vertices uniformly at random in a square of side $s$, with edges placed between each pair $x,y$ of vertices…

Probability · Mathematics 2022-04-25 Mathew D. Penrose

We consider the number of edge crossings in a random graph drawing generated by projecting a random geometric graph on some compact convex set $W\subset \mathbb{R}^d$, $d\geq 3$, onto a plane. The positions of these crossings form the…

Probability · Mathematics 2025-06-06 Hanna Döring , Lianne de Jonge

Consider a uniformly sampled random $d$-regular graph on $n$ vertices. If $d$ is fixed and $n$ goes to $\infty$ then we can relate typical (large probability) properties of such random graph to a family of invariant random processes (called…

Probability · Mathematics 2021-12-07 Ágnes Backhausz , Charles Bordenave , Balázs Szegedy

We describe a new method for the random sampling of connected networks with a specified degree sequence. We consider both the case of simple graphs and that of loopless multigraphs. The constraints of fixed degrees and of connectedness are…

Physics and Society · Physics 2020-12-03 Szabolcs Horvát , Carl D. Modes

Graph-limit theory focuses on the convergence of sequences of graphs when the number of nodes becomes arbitrarily large. This framework defines a continuous version of graphs allowing for the study of dynamical systems on very large graphs,…

Probability · Mathematics 2020-05-20 Julien Petit , Renaud Lambiotte , Timoteo Carletti
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