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We study phase transition and percolation at criticality for three random graph models on the plane, viz., the homogeneous and inhomogeneous enhanced random connection models (RCM) and the Poisson stick model. These models are built on a…

Probability · Mathematics 2020-04-03 Srikanth K. Iyer , Sanjoy Kr. Jhawar

We consider percolation on high-dimensional product graphs, where the base graphs are regular and of bounded order. In the subcritical regime, we show that typically the largest component is of order logarithmic in the number of vertices.…

Combinatorics · Mathematics 2024-04-11 Sahar Diskin , Joshua Erde , Mihyun Kang , Michael Krivelevich

Due to their conceptual and mathematical simplicity, Erd\"os-R\'enyi or classical random graphs remain as a fundamental paradigm to model complex interacting systems in several areas. Although condensation phenomena have been widely…

Disordered Systems and Neural Networks · Physics 2019-07-16 Fernando L. Metz , Isaac Pérez Castillo

We consider random graphs on the set of $N^2$ vertices placed on the discrete $2$-dimensional torus. The edges between pairs of vertices are independent, and their probabilities decay with the distance $\rho$ between these vertices as…

Probability · Mathematics 2023-08-16 Vasilii Goriachkin , Tatyana Turova

We analyze a minimal model of a growing network. At each time step, a new vertex is added; then, with probability delta, two vertices are chosen uniformly at random and joined by an undirected edge. This process is repeated for t time…

Statistical Mechanics · Physics 2009-11-07 Duncan S. Callaway , John E. Hopcroft , Jon M. Kleinberg , M. E. J. Newman , Steven H. Strogatz

Random geometric graphs (RGG) can be formalized as hidden-variables models where the hidden variables are the coordinates of the nodes. Here we develop a general approach to extract the typical configurations of a generic hidden-variables…

Disordered Systems and Neural Networks · Physics 2015-04-28 Massimo Ostilli , Ginestra Bianconi

We provide sufficient conditions for a regular graph $G$ of growing degree $d$, guaranteeing a phase transition in its random subgraph $G_p$ similar to that of $G(n,p)$ when $p\cdot d\approx 1$. These conditions capture several well-studied…

Combinatorics · Mathematics 2025-11-17 Sahar Diskin , Michael Krivelevich

We introduce a model for a growing random graph based on simultaneous reproduction of the vertices. The model can be thought of as a generalisation of the reproducing graphs of Southwell and Cannings and Bonato et al to allow for a random…

Probability · Mathematics 2011-04-20 Jonathan Jordan

In this paper we study the component structure of random graphs with independence between the edges. Under mild assumptions, we determine whether there is a giant component, and find its asymptotic size when it exists. We assume that the…

Probability · Mathematics 2010-06-29 Bela Bollobas , Svante Janson , Oliver Riordan

The classical result of Erdos and Renyi shows that the random graph G(n,p) experiences sharp phase transition around p=1/n - for any \epsilon>0 and p=(1-\epsilon)/n, all connected components of G(n,p) are typically of size O(log n), while…

Combinatorics · Mathematics 2012-09-25 Michael Krivelevich , Benny Sudakov

We investigate the dynamic formation of regular random graphs. In our model, we pick a pair of nodes at random and connect them with a link if both of their degrees are smaller than d. Starting with a set of isolated nodes, we repeat this…

Statistical Mechanics · Physics 2011-11-16 E. Ben-Naim , P. L. Krapivsky

In this paper, we study the order of the largest connected component of a random graph having two sources of randomness: first, the graph is chosen randomly from all graphs with a given degree sequence, and then bond percolation is applied.…

Probability · Mathematics 2024-02-20 Lyuben Lichev , Dieter Mitsche , Guillem Perarnau

This is a (long) survey about applications of percolation theory in equilibrium statistical mechanics. The chapters are as follows: 1. Introduction 2. Equilibrium phases 3. Some models 4. Coupling and stochastic domination 5. Percolation 6.…

Probability · Mathematics 2016-09-07 H. -O. Georgii , O. Häggström , C. Maes

We consider a version of continuum long-range percolation on finite boxes of $\mathbb{R}^d$ in which the vertex set is given by the points of a Poisson point process and each pair of two vertices at distance $r$ is connected with…

Probability · Mathematics 2023-11-21 Ercan Sönmez

Uniform random intersection graphs have received much interest and been used in diverse applications. A uniform random intersection graph with $n$ nodes is constructed as follows: each node selects a set of $K_n$ different items uniformly…

Physics and Society · Physics 2015-02-03 Jun Zhao , Osman Yağan , Virgil Gligor

We study the susceptibility, i.e., the mean size of the component containing a random vertex, in a general model of inhomogeneous random graphs. This is one of the fundamental quantities associated to (percolation) phase transitions; in…

Probability · Mathematics 2012-03-27 Svante Janson , Oliver Riordan

Consider the complete graph \(K_n\) on \(n\) vertices where each edge \(e\) is independently open with probability \(p_n(e)\) or closed otherwise. Here \(\frac{C-\alpha_n}{n} \leq p_n(e) \leq \frac{C+\alpha_n}{n}\) where \(C > 0\) is a…

Probability · Mathematics 2017-04-04 Ghurumuruhan Ganesan

We consider bond percolation on random graphs with given degrees and bounded average degree. In particular, we consider the order of the largest component after the random deletion of the edges of such a random graph. We give a rough…

Combinatorics · Mathematics 2022-01-12 Nikolaos Fountoulakis , Felix Joos , Guillem Perarnau

We consider site (vertex) percolation on $d$-regular graphs, for both constant-degree and growing-degree cases. We give sufficient, and relatively tight, conditions for the emergence of the ``Erd\H{o}s-R\'enyi component phenomenon" in the…

Combinatorics · Mathematics 2026-03-20 Sahar Diskin , Michael Krivelevich , Itay Markbreit

It is well-known that the $G(n,p)$ model of random graphs undergoes a dramatic change around $p=\frac 1n$. It is here that the random graph is, almost surely, no longer a forest, and here it first acquires a giant (i.e., order $\Omega(n)$)…

Probability · Mathematics 2016-09-20 Nathan Linial , Yuval Peled