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We find the asymptotic number of connected graphs with $k$ vertices and $k-1+l$ edges when $k,l$ approach infinity, reproving a result of Bender, Canfield and McKay. We use the {\em probabilistic method}, analyzing breadth-first search on…

Combinatorics · Mathematics 2007-05-23 Remco van der Hofstad , Joel Spencer

We study the graph constructed on a Poisson point process in $d$ dimensions by connecting each point to the $k$ points nearest to it. This graph a.s. has an infinite cluster if $k > k_c(d)$ where $k_c(d)$, known as the critical value,…

Networking and Internet Architecture · Computer Science 2008-07-18 Amitabha Bagchi , Sohit Bansal

The generalised random graph contains $n$ vertices with positive i.i.d. weights. The probability of adding an edge between two vertices is increasing in their weights. We require the weight distribution to have finite second moments and…

Probability · Mathematics 2026-04-01 Matthias Lienau

Subgraph counts - in particular the number of occurrences of small shapes such as triangles - characterize properties of random networks, and as a result have seen wide use as network summary statistics. However, subgraphs are typically…

Statistics Theory · Mathematics 2020-06-30 P-A. Maugis

The global clustering coefficient serves as a powerful metric for the structural analysis and comparison of complex networks. Random geometric graphs offer a realistic framework for representing the spatial constraints and geometry often…

Statistics Theory · Mathematics 2026-02-23 Mingao Yuan , Md. Niamul Islam Sium

Consider a bipartite random geometric graph on the union of two independent homogeneous Poisson point processes in $d$-space, with distance parameter $r$ and intensities $\lambda,\mu$. We show for $d \geq 2$ that if $\lambda$ is…

Probability · Mathematics 2014-05-13 Mathew D. Penrose

We investigate topological, combinatorial, statistical, and enumeration properties of finite graphs with high Kolmogorov complexity (almost all graphs) using the novel incompressibility method. Example results are: (i) the mean and variance…

Combinatorics · Mathematics 2007-05-23 Harry Buhrman , Ming Li , John Tromp , Paul Vitanyi

Sampling random graphs is essential in many applications, and often algorithms use Markov chain Monte Carlo methods to sample uniformly from the space of graphs. However, often there is a need to sample graphs with some property that we are…

Social and Information Networks · Computer Science 2018-10-29 Caitlin Gray , Lewis Mitchell , Matthew Roughan

We associate all small subgraph counting problems with a systematic graph encoding/representation system which makes a coherent use of graphlet structures. The system can serve as a unified foundation for studying and connecting many…

Discrete Mathematics · Computer Science 2021-03-22 Dimitris Floros , Nikos Pitsianis , Xiaobai Sun

We propose an algorithm for the closed-form recursive computation of joint moments and cumulants of all orders for k-hop counts in the 1D unit disk random graph model with Poisson distributed vertices. Our approach uses decompositions of…

Probability · Mathematics 2022-03-29 Nicolas Privault

Learning properties of large graphs from samples has been an important problem in statistical network analysis since the early work of Goodman \cite{Goodman1949} and Frank \cite{Frank1978}. We revisit a problem formulated by Frank…

Statistics Theory · Mathematics 2019-06-18 Jason M. Klusowski , Yihong Wu

We study the problem of deterministic approximate counting of matchings and independent sets in graphs of bounded connective constant. More generally, we consider the problem of evaluating the partition functions of the monomer-dimer model…

Data Structures and Algorithms · Computer Science 2014-10-10 Alistair Sinclair , Piyush Srivastava , Daniel Štefankovič , Yitong Yin

Upper bounds for the probabilities $\mathbb{P}(F\geq \mathbb{E} F + r)$ and $\mathbb{P}(F\leq \mathbb{E} F - r)$ are proved, where $F$ is a certain component count associated with a random geometric graph built over a Poisson point process…

Probability · Mathematics 2016-01-14 Sascha Bachmann

We introduce a general framework for studying anticoncentration and local limit theorems for random variables, including graph statistics. Our methods involve an interplay between Fourier analysis, decoupling, hypercontractivity of Boolean…

Probability · Mathematics 2022-03-09 Ashwin Sah , Mehtaab Sawhney

We use the combination of ideas and results from the theory of graph limits and nonlinear evolution equations to provide a rigorous mathematical justification for taking continuum limit for certain nonlocally coupled networks and to extend…

Adaptation and Self-Organizing Systems · Physics 2013-11-25 Georgi S. Medvedev

Let $X$ be either $Z^d$ or the points of a Poisson process in $R^d$ of intensity 1. Given parameters $r$ and $p$, join each pair of points of $X$ within distance $r$ independently with probability $p$. This is the simplest case of a…

Probability · Mathematics 2009-05-08 Bela Bollobas , Svante Janson , Oliver Riordan

Poissonian ensembles of Markov loops on a finite graph define a random graph process in which the addition of a loop can merge more than two connected components. We study Markov loops on the complete graph derived from a simple random walk…

Probability · Mathematics 2014-06-18 Sophie Lemaire

For a transitive infinite connected graph $G$, let $\mu(G)$ be its connective constant. Denote by $\mathbf{\cal G}$ the set of Cayley graphs for finitely generated infinite groups with an infinite-order generator which is independent of…

Probability · Mathematics 2014-10-10 He Song , Kai-Nan Xiang , Song-Chao-Hao Zhu

Consider a family $\mathcal{T}$ of 3-connected graphs of moderate growth, and let $\mathcal{G}$ be the class of graphs whose 3-connected components are graphs in $\mathcal{T}$. We present a general framework for analyzing such graphs…

Combinatorics · Mathematics 2009-07-03 Omer Gimenez , Marc Noy , Juanjo Rue

Network Models with couplings between link pairs are the simplest models for a class of networks with Higher Order interactions. In this paper we give an analytic, general solution to this family of Random Graph Models extending previous…

Statistical Mechanics · Physics 2025-03-28 Alessio Catanzaro , Subodh Patil , Diego Garlaschelli