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We generalize the random graph evolution process of Bohman, Frieze, and Wormald [T. Bohman, A. Frieze, and N. C. Wormald, Random Struct. Algorithms, 25, 432 (2004)]. Potential edges, sampled uniformly at random from the complete graph, are…

Disordered Systems and Neural Networks · Physics 2011-03-31 Wei Chen , Raissa M. D'Souza

We study the percolation transition in growing networks under an Achlioptas process (AP). At each time step, a node is added in the network and, with the probability $\delta$, a link is formed between two nodes chosen by an AP. We find that…

Statistical Mechanics · Physics 2013-08-07 Su Do Yi , Woo Seong Jo , Beom Jun Kim , Seung-Woo Son

Explosive percolation in the Achlioptas process has recently attracted much research attention. From extensive simulations in an event-based ensemble, we find that, in dimensions from $2$ to $6$ and on random graphs, the Achlioptas…

Statistical Mechanics · Physics 2022-08-23 Ming Li , Junfeng Wang , Youjin Deng

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

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

The evolution of the usual Erd\H{o}s-R\'{e}nyi random graph model on n vertices can be described as follows: At time 0 start with the empty graph, with n vertices and no edges. Now at each time k, choose 2 vertices uniformly at random and…

Probability · Mathematics 2011-06-09 Shankar Bhamidi , Amarjit Budhiraja , Xuan Wang

Random graph models with limited choice have been studied extensively with the goal of understanding the mechanism of the emergence of the giant component. One of the standard models are the Achlioptas random graph processes on a fixed set…

Probability · Mathematics 2012-12-24 Shankar Bhamidi , Amarjit Budhiraja , Xuan Wang

Understanding what types of phenomena lead to discontinuous phase transitions in the connectivity of random networks is an outstanding challenge. Here we show that a simple stochastic model of graph evolution leads to a discontinuous…

Disordered Systems and Neural Networks · Physics 2015-05-28 Wei Chen , Zhiming Zheng , Raissa M. D'Souza

The random geometric graph is obtained by sampling $n$ points from the unit square (uniformly at random and independently), and connecting two points whenever their distance is at most $r$, for some given $r=r(n)$. We consider the following…

Probability · Mathematics 2015-10-27 Tobias Müller , Reto Spöhel

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 study a one parameter family of random graph models that spans a continuum between traditional random graphs of the Erd\H{o}s-R\'enyi type, where there is no underlying structure, and percolation models, where the possible edges are…

Probability · Mathematics 2008-04-02 Oskar Sandberg

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

The biased link occupation rule in the Achlioptas process (AP) discourages the large clusters to grow much ahead of others and encourages faster growth of clusters which lag behind. In this paper we propose a model where this tendency is…

Disordered Systems and Neural Networks · Physics 2011-01-04 S. S. Manna , Arnab Chatterjee

In a new type of percolation phase transition, which was observed in a set of non-equilibrium models, each new connection between vertices is chosen from a number of possibilities by an Achlioptas-like algorithm. This causes preferential…

Disordered Systems and Neural Networks · Physics 2015-06-18 R. A. da Costa , S. N. Dorogovtsev , A. V. Goltsev , J. F. F. Mendes

The existence of explosive phase transitions in random (Erd\H os R\'enyi-type) networks has been recently documented by Achlioptas et al.\ [Science {\bf 323}, 1453 (2009)] via simulations. In this Letter we describe the underlying mechanism…

Statistical Mechanics · Physics 2015-05-14 Eric J. Friedman , Adam S. Landsberg

The basic notion of percolation in physics assumes the emergence of a giant connected (percolation) cluster in a large disordered system when the density of connections exceeds some critical value. Until recently, the percolation phase…

Disordered Systems and Neural Networks · Physics 2015-05-19 R. A. da Costa , S. N. Dorogovtsev , A. V. Goltsev , J. F. F. Mendes

After the Achlioptas process (AP), which yields the so-called explosive percolation, was introduced, the number of papers on percolation phenomena has been literally exploding. Most of the existing studies, however, have focused only on the…

Disordered Systems and Neural Networks · Physics 2015-01-16 Woo Seong Jo , Su Do Yi , Beom Jun Kim , Seung-Woo Son

The finite-size scaling (FSS) theory for continuous phase transitions has been useful in determining the critical behavior from the size dependent behaviors of thermodynamic quantities. When the phase transition is discontinuous, however,…

Statistical Mechanics · Physics 2015-05-19 Y. S. Cho , S. -W. Kim , J. D. Noh , B. Kahng , D. Kim

We introduce a new oriented evolving graph model inspired by biological networks. A node is added at each time step and is connected to the rest of the graph by random oriented edges emerging from older nodes. This leads to a statistical…

Disordered Systems and Neural Networks · Physics 2023-04-10 Michel Bauer , Denis Bernard

Bootstrap percolation on a graph iteratively enlarges a set of occupied sites by adjoining points with at least $\theta$ occupied neighbors. The initially occupied set is random, given by a uniform product measure, and we say that spanning…

Probability · Mathematics 2015-05-14 Janko Gravner , David Sivakoff