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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 study logical limit laws for preferential attachment random graphs. In this random graph model, vertices and edges are introduced recursively: at time $1$, we start with vertices $0,1$ and $m$ edges between them. At step $n+1$ the vertex…

Probability · Mathematics 2021-08-19 Yury Malyshkin

Since the paper of Kleinberg and Kleinberg, SODA'05, where it was proven that the preferential attachment random graph with degeneracy at least 3 does not obey the first order 0-1 law, no general methods were developed to study logical…

Probability · Mathematics 2023-11-01 Yury Malyshkin , Maksim Zhukovskii

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

For many standard models of random structure, first-order logic sentences exhibit a convergence phenomenon on random inputs. The most well-known example is for random graphs with constant edge probability, where the probabilities of…

Logic in Computer Science · Computer Science 2025-04-24 Sam Adam-Day , Michael Benedikt , Alberto Larrauri

We consider limit probabilities of first order properties in random graphs with a given degree sequence. Under mild conditions on the degree sequence, we show that the closure set of limit probabilities is a finite union of closed…

Combinatorics · Mathematics 2024-05-24 Alberto Larrauri , Guillem Perarnau

We investigate the degree distribution resulting from graph generation models based on rank-based attachment. In rank-based attachment, all vertices are ranked according to a ranking scheme. The link probability of a given vertex is…

Combinatorics · Mathematics 2012-08-28 Jeannette Janssen , Pawel Pralat

We consider first order expressible properties of random perfect graphs. That is, we pick a graph $G_n$ uniformly at random from all (labelled) perfect graphs on $n$ vertices and consider the probability that it satisfies some graph…

Combinatorics · Mathematics 2018-10-02 Tobias Müller , Marc Noy

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

Let $\mathcal G$ be an addable, minor-closed class of graphs. We prove that the zero-one law holds in monadic second-order logic (MSO) for the random graph drawn uniformly at random from all {\em connected} graphs in $\mathcal G$ on $n$…

Combinatorics · Mathematics 2018-01-10 Peter Heinig , Tobias Muller , Marc Noy , Anusch Taraz

We study preferential attachment mechanisms in random graphs that are parameterized by (i) a constant bias affecting the degree-biased distribution on the vertex set and (ii) the distribution of times at which new vertices are created by…

Probability · Mathematics 2017-10-09 Benjamin Bloem-Reddy , Peter Orbanz

In this paper, a random graph process ${G(t)}_{t\geq 1}$ is studied and its degree sequence is analyzed. Let $(W_t)_{t\geq 1}$ be an i.i.d. sequence. The graph process is defined so that, at each integer time $t$, a new vertex, with $W_t$…

Probability · Mathematics 2020-06-05 Maria Deijfen , Henri van den Esker , Remco van der Hofstad , Gerard Hooghiemstra

We consider an evolving preferential attachment random graph model where at discrete times a new node is attached to an old node, selected with probability proportional to a superlinear function of its degree. For such schemes, it is known…

Probability · Mathematics 2017-04-20 Sunder Sethuraman , Shankar C. Venkataramani

We study the joint degree counts in proportional attachment random graphs and find a simple representation for the limit distribution in infinite sequence space. We show weak convergence with respect to the p-norm topology for appropriate p…

Probability · Mathematics 2016-12-09 Erol A. Peköz , Adrian Röllin , Nathan Ross

Nesetril and Ossona de Mendez introduced the notion of first order convergence, which unifies the notions of convergence for sparse and dense graphs. They asked whether if G_i is a sequence of graphs with M being their first order limit and…

Combinatorics · Mathematics 2019-02-20 Demetres Christofides , Daniel Kral

We prove almost sure convergence of the maximum degree in an evolving graph model combining a growing number of local choices with sublinear preferential attachment. At each step in the growth of the graph, a new vertex is introduced. Then…

Probability · Mathematics 2019-11-19 Yury Malyshkin

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

We consider a simple Preferential Attachment graph process, which begins with a finite graph, and in which a new $(t+1)$st vertex is added at each subsequent time step $t$, and connected to each previous vertex $u \leq t$ with probability…

Combinatorics · Mathematics 2020-04-22 Richard Elwes

We propose a random graph model with preferential attachment rule and \emph{edge-step functions} that govern the growth rate of the vertex set. We study the effect of these functions on the empirical degree distribution of these random…

Probability · Mathematics 2019-01-09 Caio Alves , Rodrigo Ribeiro , Remy Sanchis

In this paper we focus on the problem of the degree sequence for the following random graph process. At any time-step $t$, one of the following three substeps is executed: with probability $\alpha_1$, a new vertex $x_t$ and $m$ edges…

Probability · Mathematics 2008-07-01 Xian-Yuan Wu , Zhao Dong , Ke Liu , Kai-Yuan Cai
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