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A temporal graph is a graph whose edges appear only at certain points in time. Recently, the second and the last three authors proposed a natural temporal analog of the Erd\H{o}s-R\'enyi random graph model. The proposed model is obtained by…

Discrete Mathematics · Computer Science 2023-08-21 Ruben Becker , Arnaud Casteigts , Pierluigi Crescenzi , Bojana Kodric , Malte Renken , Michael Raskin , Viktor Zamaraev

We study the critical behavior of the component sizes for the configuration model when the tail of the degree distribution of a randomly chosen vertex is a regularly-varying function with exponent $\tau-1$, where $\tau\in (3,4)$. The…

Probability · Mathematics 2020-12-22 Souvik Dhara , Remco van der Hofstad , Johan S. H. van Leeuwaarden , Sanchayan Sen

On a large finite connected graph let edges $e$ become "open" at independent random Exponential times of arbitrary rates $w_e$. Under minimal assumptions, the time at which a giant component starts to emerge is weakly concentrated around…

Probability · Mathematics 2016-04-25 David J. Aldous

We introduce a class of random graphs with a community structure, which we call the hierarchical configuration model. On the inter-community level, the graph is a configuration model, and on the intra-community level, every vertex in the…

Probability · Mathematics 2016-12-16 Remco van der Hofstad , Johan S. H. van Leeuwaarden , Clara Stegehuis

For a fixed degree sequence $\mathcal{D}=(d_1,...,d_n)$, let $G(\mathcal{D})$ be a uniformly chosen (simple) graph on $\{1,...,n\}$ where the vertex $i$ has degree $d_i$. In this paper we determine whether $G(\mathcal{D})$ has a giant…

Combinatorics · Mathematics 2017-02-01 Felix Joos , Guillem Perarnau , Dieter Rautenbach , Bruce Reed

The largest connected component in duplication-divergence growing graphs with symmetric coupled divergence is studied. Finite-size scaling reveals a phase transition occurring at a divergence rate $\delta_c$. The $\delta_c$ found stands…

Statistical Mechanics · Physics 2026-01-27 Dario Borrelli

Let $A(n,m)$ be a graph chosen uniformly at random from the class of all vertex-labelled outerplanar graphs with $n$ vertices and $m$ edges. We consider $A(n,m)$ in the sparse regime when $m=n/2+s$ for $s=o(n)$. We show that with high…

Combinatorics · Mathematics 2020-04-29 Mihyun Kang , Michael Missethan

We study the emergence of a giant component in a spatial network where the distribution of the metric distances between the nodes is scale-invariant, and the interaction between the nodes has a long-range power-law behavior. The nodes are…

Statistical Mechanics · Physics 2022-07-29 Guy Amit , Dana Ben Porath , Sergey V. Buldyrev , Amir Bashan

We study the following preferential attachment variant of the classical Erdos-Renyi random graph process. Starting with an empty graph on n vertices, new edges are added one-by-one, and each time an edge is chosen with probability roughly…

Probability · Mathematics 2022-06-01 Svante Janson , Lutz Warnke

Limiting distributions are derived for the sparse connected components that are present when a random graph on $n$ vertices has approximately $\half n$ edges. In particular, we show that such a graph consists entirely of trees, unicyclic…

Probability · Mathematics 2008-02-03 Svante Janson , Donald E. Knuth , Tomasz Łuczak , Boris Pittel

We study the critical behavior for percolation on inhomogeneous random networks on $n$ vertices, where the weights of the vertices follow a power-law distribution with exponent $\tau \in (2,3)$. Such networks, often referred to as…

Probability · Mathematics 2021-07-12 Shankar Bhamidi , Souvik Dhara , Remco van der Hofstad

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 analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network…

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 a special case of the configuration model, in which almost all the vertices of the graph have degree $2$. We show that the graph has a very peculiar and interesting behaviour, in particular when the graph is made up by a vast…

Probability · Mathematics 2020-01-17 Lorenzo Federico

We consider vertex percolation on pseudo-random $d-$regular graphs. The previous study by the second author established the existence of phase transition from small components to a linear (in $\frac{n}{d}$) sized component, at…

Combinatorics · Mathematics 2022-11-30 Sahar Diskin , Michael Krivelevich

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

Let d \geq d_0 be a sufficiently large constant. A (n,d,c \sqrt{d}) graph G is a d-regular graph over n vertices whose second largest (in absolute value) eigenvalue is at most c \sqrt{d}. For any 0 < p < 1, G_p is the graph induced by…

Probability · Mathematics 2007-05-23 Eran Ofek

We study large deviations of the size of the largest connected component in a general class of inhomogeneous random graphs with iid weights, parametrized so that the degree distribution is regularly varying. We derive a large-deviation…

Probability · Mathematics 2024-07-02 Joost Jorritsma , Bert Zwart

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