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We develop a theory of limits for sequences of dense abstract simplicial complexes, where a sequence is considered convergent if its homomorphism densities converge. The limiting objects are represented by stacks of measurable [0,1]-valued…

Combinatorics · Mathematics 2022-07-19 T. Mitchell Roddenberry , Santiago Segarra

We study a recent model for edge exchangeable random graphs introduced by Crane and Dempsey; in particular we study asymptotic properties of the random simple graph obtained by merging multiple edges. We study a number of examples, and show…

Probability · Mathematics 2017-08-02 Svante Janson

The theory of dense graph limits comes with a natural sampling process which yields an inhomogeneous variant G(n,W) of the Erdos-Renyi random graph. Here we study the clique number of these random graphs. We establish the concentration of…

Combinatorics · Mathematics 2018-12-04 Martin Doležal , Jan Hladký , András Máthé

We establish the conditions under which several algorithmically exploitable structural features hold for random intersection graphs, a natural model for many real-world networks where edges correspond to shared attributes. Specifically, we…

Social and Information Networks · Computer Science 2017-02-10 Matthew Farrell , Timothy Goodrich , Nathan Lemons , Felix Reidl , Fernando Sánchez Villaamil , Blair D. Sullivan

Local convergence of bounded degree graphs was introduced by Benjamini and Schramm. This result was extended further by Lyons to bounded average degree graphs. In this paper we study the convergence of random tree sequences with given…

Probability · Mathematics 2014-08-07 Attila Deák

We define the edge reconnecting model, a random multigraph evolving in time. At each time step we change one endpoint of a uniformly chosen edge: the new endpoint is chosen by linear preferential attachment. We consider a sequence of edge…

Probability · Mathematics 2012-04-27 Balazs Rath

We view hyper-graphs as incidence graphs, i.e. bipartite graphs with a set of nodes representing vertices and a set of nodes representing hyper-edges, with two nodes being adjacent if the corresponding vertex belongs to the corresponding…

Logic in Computer Science · Computer Science 2015-05-08 Nans Lefebvre

In the dense graph limit theory, the topology of the set of graphs is defined by the distribution of the subgraphs spanned by finite number of random vertices. Vera T. S\'os proposed a question that if we consider only the number of edges…

Combinatorics · Mathematics 2015-08-21 Endre Csóka

In this paper we determine the percolation threshold for an arbitrary sequence of dense graphs $(G_n)$. Let $\lambda_n$ be the largest eigenvalue of the adjacency matrix of $G_n$, and let $G_n(p_n)$ be the random subgraph of $G_n$ obtained…

Probability · Mathematics 2010-02-04 Béla Bollobás , Christian Borgs , Jennifer Chayes , Oliver Riordan

The theory of graph limits represents large graphs by analytic objects called graphons. Graph limits determined by finitely many graph densities, which are represented by finitely forcible graphons, arise in various scenarios, particularly…

Combinatorics · Mathematics 2018-10-10 Jacob W. Cooper , Daniel Kral , Taisa L. Martins

We determine the sharp threshold for the containment of all $n$-vertex trees of bounded degree in random geometric graphs with $n$ vertices. This provides a geometric counterpart of Montgomery's threshold result for binomial random graphs,…

Combinatorics · Mathematics 2025-05-23 Michael Anastos , Sahar Diskin , Dawid Ignasiak , Lyuben Lichev , Yetong Sha

Let $G$ be a large (simple, unlabeled) dense graph on $n$ vertices. Suppose that we only know, or can estimate, the empirical distribution of the number of subgraphs $F$ that each vertex in $G$ participates in, for some fixed small graph…

Information Theory · Computer Science 2023-08-08 Shahar Stein Ioushua , Ofer Shayevitz

We introduce a method for the theoretical analysis of exponential random graph models. The method is based on a large-deviations approximation to the normalizing constant shown to be consistent using theory developed by Chatterjee and…

Probability · Mathematics 2013-11-21 Sourav Chatterjee , Persi Diaconis

We study logical limit laws for uniform attachment random graphs. In this random graph model, vertices and edges are introduced recursively: at time $n+1$, the vertex $n+1$ is introduced together with $m$ edges joining the new vertex with…

Probability · Mathematics 2022-01-03 Yury Malyshkin , Maksim Zhukovskii

We consider exploration algorithms of the random sequential adsorption type both for homogeneous random graphs and random geometric graphs based on spatial Poisson processes. At each step, a vertex of the graph becomes active and its…

Probability · Mathematics 2017-11-22 Paola Bermolen , Matthieu Jonckheere , Jaron Sanders

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

Preferential attachment graphs are random graphs designed to mimic properties of typical real world networks. They are constructed by a random process that iteratively adds vertices and attaches them preferentially to vertices that already…

Discrete Mathematics · Computer Science 2018-03-30 Jan Dreier , Philipp Kuinke , Peter Rossmanith

For any fixed integer $R \geq 2$ we characterise the typical structure of undirected graphs with vertices $1, ..., n$ and maximum degree $R$, as $n$ tends to infinity. The information is used to prove that such graphs satisfy a labelled…

Combinatorics · Mathematics 2012-12-18 Vera Koponen

In two recent papers by Veitch and Roy and by Borgs, Chayes, Cohn, and Holden, a new class of sparse random graph processes based on the concept of graphexes over $\sigma$-finite measure spaces has been introduced. In this paper, we…

Probability · Mathematics 2018-04-11 Christian Borgs , Jennifer T. Chayes , Henry Cohn , László Miklós Lovász

We study models of weighted exponential random graphs in the large network limit. These models have recently been proposed to model weighted network data arising from a host of applications including socio-econometric data such as migration…

Probability · Mathematics 2018-07-12 Shankar Bhamidi , Suman Chakraborty , Skyler Cranmer , Bruce Desmarais