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Random graph matching refers to recovering the underlying vertex correspondence between two random graphs with correlated edges; a prominent example is when the two random graphs are given by Erd\H{o}s-R\'{e}nyi graphs $G(n,\frac{d}{n})$.…

Machine Learning · Statistics 2020-07-21 Jian Ding , Zongming Ma , Yihong Wu , Jiaming Xu

The random reversal graph offers new perspectives, allowing to study the connectivity of genomes as well as their most likely distance as a function of the reversal rate. Our main result shows that the structure of the random reversal graph…

Combinatorics · Mathematics 2010-03-04 Emma Y. Jin , Christian M. Reidys

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

We survey recent results on some one- and two-dimensional patterns generated by random permutations of natural numbers. In the first part, we discuss properties of random walks, evolving on a one-dimensional regular lattice in discrete time…

Statistical Mechanics · Physics 2009-11-11 G. Oshanin , R. Voituriez , S. Nechaev , O. Vasilyev , F. Hivert

We study a random graph $G_n$, which combines aspects of geometric random graphs and preferential attachment. The resulting random graphs have power-law degree sequences with finite mean and possibly infinite variance. In particular, the…

Combinatorics · Mathematics 2008-01-11 H. van den Esker

Many real-world networks of interest are embedded in physical space. We present a new random graph model aiming to reflect the interplay between the geometries of the graph and of the underlying space. The model favors configurations with…

Probability · Mathematics 2017-06-14 Jean-Christophe Mourrat , Daniel Valesin

Consider the random process that starts with $n$ vertices and no edges, where the edges of $K_n$ are added one at a time in a uniformly chosen random order $e_1, e_2,\ldots, e_{\binom{n}{2}}$. Let $T$ be the earliest time at which $e_1$…

Combinatorics · Mathematics 2025-12-16 Nir Lavee , Nati Linial

We study a new kind of proximity graphs called proportional-edge proximity catch digraphs (PCDs)in a randomized setting. PCDs are a special kind of random catch digraphs that have been developed recently and have applications in statistical…

Combinatorics · Mathematics 2010-03-30 Elvan Ceyhan

A $d$-regular graph on $n$ nodes has at most $T_{\max} = \frac{n}{3} \tbinom{d}{2}$ triangles. We compute the leading asymptotics of the probability that a large random $d$-regular graph has at least $c \cdot T_{\max}$ triangles, and…

Combinatorics · Mathematics 2021-04-16 Pim van der Hoorn , Gabor Lippner , Elchanan Mossel

We consider random graphs sampled uniformly from a structured class of graphs, such as the class of graphs embeddable in a given surface. We sharpen and extend earlier results on pendant appearances, concerning for example numbers of…

Combinatorics · Mathematics 2024-05-07 Colin McDiarmid

We develop random graph models where graphs are generated by connecting not only pairs of vertices by edges but also larger subsets of vertices by copies of small atomic subgraphs of arbitrary topology. This allows the for the generation of…

Statistics Theory · Mathematics 2021-04-21 Anatol E. Wegner , Sofia Olhede

Degree distribution, or equivalently called degree sequence, has been commonly used to be one of most significant measures for studying a large number of complex networks with which some well-known results have been obtained. By contrast,…

Physics and Society · Physics 2020-02-19 Fei Ma , Xiaoming Wang , Ping Wang

In this paper we propose a model of random compositions of cylinder maps, which in the simplified form is as follows: $(\theta,r)\in \mathbb T\times \mathbb R=\mathbb A$ and \begin{eqnarray} \nonumber f_{\pm 1}:…

Dynamical Systems · Mathematics 2015-01-26 O. Castejón , V. Kaloshin

We present fast and efficient randomized distributed algorithms to find Hamiltonian cycles in random graphs. In particular, we present a randomized distributed algorithm for the $G(n,p)$ random graph model, with number of nodes $n$ and…

Data Structures and Algorithms · Computer Science 2018-04-25 Soumyottam Chatterjee , Reza Fathi , Gopal Pandurangan , Nguyen Dinh Pham

Directed acyclic graphs are the basic representation of the structure underlying Bayesian networks, which represent multivariate probability distributions. In many practical applications, such as the reverse engineering of gene regulatory…

Computation · Statistics 2013-11-15 Jack Kuipers , Giusi Moffa

We consider the geometric random (GR) graph on the $d-$dimensional torus with the $L_\sigma$ distance measure ($1 \leq \sigma \leq \infty$). Our main result is an exact characterization of the probability that a particular labeled cycle…

Combinatorics · Mathematics 2010-10-01 Madhav P. Desai

Let $T(H, G_n)$ be the number of monochromatic copies of a fixed connected graph $H$ in a uniformly random coloring of the vertices of the graph $G_n$. In this paper we give a complete characterization of the limiting distribution of $T(H,…

Probability · Mathematics 2021-03-03 Bhaswar B. Bhattacharya , Sumit Mukherjee

Each connected component of a mapping $\{1,2,...,n\}\rightarrow\{1,2,...,n\}$ contains a unique cycle. The largest such component can be studied probabilistically via either a delay differential equation or an inverse Laplace transform. The…

Combinatorics · Mathematics 2022-05-12 Steven Finch

We study the largest component of a random (multi)graph on n vertices with a given degree sequence. We let n tend to infinity. Then, under some regularity conditions on the degree sequences, we give conditions on the asymptotic shape of the…

Combinatorics · Mathematics 2007-07-13 Svante Janson , Malwina Luczak

We consider two classes of random graphs: $(a)$ Poissonian random graphs in which the $n$ vertices in the graph have i.i.d.\ weights distributed as $X$, where $\mathbb{E}(X) = \mu$. Edges are added according to a product measure and the…

Probability · Mathematics 2010-10-05 Tom Britton , Pieter Trapman