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We construct a compound Poisson process conditioned on its random summation that represents the sizes of the connected components in the sparse Erd\H{o}s-R\'enyi random graph $G(n,c/n)$. This new representation depicts a connection between…

Probability · Mathematics 2023-10-23 Wen Sun

Let $G=G(d)$ be a random graph with a given degree sequence $d$, such as a random $r$-regular graph where $r\ge 3$ is fixed and $n=|G|\to\infty$. We study the percolation phase transition on such graphs $G$, i.e., the emergence as $p$…

Probability · Mathematics 2012-03-26 Oliver Riordan

We introduce a variant of the Erd\"os--R\'enyi random graph where the number of vertices is random and follows a Poisson law. A very simple Markov property of the model entails that the Lukasiewicz exploration is made of…

Probability · Mathematics 2022-11-14 Nicolas Curien

We consider a dynamic Erd\H{o}s-R\'enyi random graph (ERRG) on $n$ vertices in which each edge switches on at rate $\lambda$ and switches off at rate $\mu$, independently of other edges. The focus is on the analysis of the evolution of the…

Probability · Mathematics 2020-09-29 Peter Braunsteins , Frank den Hollander , Michel Mandjes

As suggested by Itai Benjamini, we introduced a variant of the Erd\"os- R\'enyi random graph process with a forbidden degree $k$, in which every edge adjacent to a vertex $v$ is removed when the degree of $v$ reaches $k$ (but the removed…

Probability · Mathematics 2016-02-29 Lucas Mercier

In this paper, we consider the problem of learning an unknown graph via queries on groups of nodes, with the result indicating whether or not at least one edge is present among those nodes. While learning arbitrary graphs with $n$ nodes and…

Information Theory · Computer Science 2020-01-07 Zihan Li , Matthias Fresacher , Jonathan Scarlett

A wide variety of complex networks (social, biological, information etc.) exhibit local clustering with substantial variation in the clustering coefficient (the probability of neighbors being connected). Existing models of large graphs…

Discrete Mathematics · Computer Science 2017-09-28 Samantha Petti , Santosh Vempala

The phenomenology from the time of the quench to the asymptotic behavior in the phase-ordering kinetics of a system with conserved order parameter is investigated in the Bray-Humayun model and in the Cahn-Hilliard-Cook model. From the…

Statistical Mechanics · Physics 2009-10-31 Claudio Castellano , Marco Zannetti

We study the problem of learning an unknown graph via group queries on node subsets, where each query reports whether at least one edge is present among the queried nodes. In general, learning arbitrary graphs with $n$ nodes and $k$ edges…

Information Theory · Computer Science 2025-11-25 Hoang Ta , Jonathan Scarlett

This paper focuses on the problem of the degree sequence for a mixed random graph process which continuously combines the {\it classical} model and the BA model. Note that the number of step added edges for the mixed model is random and…

Probability · Mathematics 2009-01-13 Xian-Yuan Wu , Zhao Dong , Ke Liu , Kai-Yuan Cai

Explosive percolation in the Achlioptas process, which has attracted much research attention, is known to exhibit a rich variety of critical phenomena that are anomalous from the perspective of continuous phase transitions. Hereby, we show…

Statistical Mechanics · Physics 2023-04-06 Ming Li , Junfeng Wang , Youjin Deng

It has been established under very general conditions that the ergodic properties of Markov processes are inherited by their conditional distributions given partial information. While the existing theory provides a rather complete picture…

Probability · Mathematics 2015-02-04 Patrick Rebeschini , Ramon van Handel

We study scale-free networks constructed via a cooperative Achlioptas growth process. Links between nodes are introduced in the network in order to produce a scale-free graph with given exponent lambda for the degree distribution, but the…

Physics and Society · Physics 2009-10-13 Filippo Radicchi , Santo Fortunato

We study the spectral properties of the adjacency matrix in the giant connected component of Erd\"os-R\'enyi random graphs, with average connectivity $p$ and randomly distributed hopping amplitudes. By solving the self-consistent cavity…

Disordered Systems and Neural Networks · Physics 2024-11-14 Leticia F. Cugliandolo , Grégory Schehr , Marco Tarzia , Davide Venturelli

A phase transition, like the one already found on Boolean satisfiability problem by Kirkpatrick and Selman, is found on max clique problem on ER graphs. Although number of the datapoints is limited, the transition seems to obey finite size…

Statistical Mechanics · Physics 2008-01-12 Kazuhito Shida

We show, that the standard model of phase transition can be unified with the gradient model of phase transitions using the description in terms of the gradient of order parameter. The generalization of the gradient theory of phase…

Statistical Mechanics · Physics 2012-06-21 B. I. Lev , A. G. Zagorodny

We study the phase transition of the random degree constrained process (RDCP), a time-evolving random graph model introduced by Ruci\'nski and Wormald that generalizes the random $d$-process to the non-regular setting: each vertex of the…

Probability · Mathematics 2026-01-16 Balázs Ráth , Márton Szőke

We develop a quantitative large deviations theory for random hypergraphs, which rests on tensor decomposition and counting lemmas under a novel family of cut-type norms. As our main application, we obtain sharp asymptotics for joint upper…

Probability · Mathematics 2023-05-10 Nicholas A. Cook , Amir Dembo , Huy Tuan Pham

This paper investigate the sparse multi-type Erd\H{o}s R\'enyi random graphs studied in S\"{o}derberg~\cite{soderberg2002general} and also Bollob\'as et al.~\cite{bollobas2007phase}. Although the corresponding central limit results are…

Probability · Mathematics 2025-12-17 Rui Yu , Wen Sun

We investigate two types of dynamical quantum phase transitions (DQPTs) in the transverse field Ising model on ensembles of Erd\H{o}s-R\'enyi networks of size $N$. These networks consist of vertices connected randomly with probability $p$…

Quantum Physics · Physics 2025-06-24 Tomohiro Hashizume , Felix Herbort , Joseph Tindall , Dieter Jaksch
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