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We discuss several limiting degree distributions for a class of random threshold graphs in the many node regime. This analysis is carried out under a weak assumption on the distribution of the underlying fitness variable. This assumption,…

Probability · Mathematics 2019-08-21 Armand M. Makowski , Siddharth Pal

We count the asymptotic number of triangles in uniform random graphs where the degree distribution follows a power law with degree exponent $\tau\in(2,3)$. We also analyze the local clustering coefficient $c(k)$, the probability that two…

Probability · Mathematics 2018-12-12 Pu Gao , Remco van der Hofstad , Angus Southwell , Clara Stegehuis

We discuss three related models of scale-free networks with the same degree distribution but different correlation properties. Starting from the Barabasi-Albert construction based on growth and preferential attachment we discuss two other…

Statistical Mechanics · Physics 2009-11-10 R. Xulvi-Brunet , W. Pietsch , I. M. Sokolov

Given a set D of nonnegative integers, we derive the asymptotic number of graphs with a givenvnumber of vertices, edges, and such that the degree of every vertex is in D. This generalizes existing results, such as the enumeration of graphs…

Combinatorics · Mathematics 2015-07-22 Élie de Panafieu , Lander Ramos

We extend the previously observed scaling equation connecting the internode distances and nodes' degrees onto the case of weighted networks. We show that the scaling takes a similar form in the empirical data obtained from networks…

Physics and Society · Physics 2010-08-25 Julian Sienkiewicz , Janusz A. Holyst

Complex networks in different areas exhibit degree distributions with heavy upper tail. A preferential attachment mechanism in a growth process produces a graph with this feature. We herein investigate a variant of the simple preferential…

Probability · Mathematics 2018-04-18 Angelica Pachon , Laura Sacerdote , Shuyi Yang

We propose a geometric growth model for weighted scale-free networks, which is controlled by two tunable parameters. We derive exactly the main characteristics of the networks, which are partially determined by the parameters. Analytical…

Physics and Society · Physics 2011-11-09 Zhongzhi Zhang , Shuigeng Zhou , Lichao Chen , Jihong Guan , Lujun Fang , Yichao Zhang

Random graphs with power-law degrees can model scale-free networks as sparse topologies with strong degree heterogeneity. Mathematical analysis of such random graphs proved successful in explaining scale-free network properties such as…

Physics and Society · Physics 2019-05-24 Clara Stegehuis , Remco van der Hofstad , Johan S. H. van Leeuwaarden

Maximum entropy models, motivated by applications in neuron science, are natural generalizations of the $\beta$-model to weighted graphs. Similar to the $\beta$-model, each vertex in maximum entropy models is assigned a potential parameter,…

Statistics Theory · Mathematics 2014-10-28 Ting Yan , Yunpeng Zhao , Hong Qin

We derive the sampling properties of random networks based on weights whose pairwise products parameterize independent Bernoulli trials. This enables an understanding of many degree-based network models, in which the structure of realized…

Statistics Theory · Mathematics 2013-06-07 Sofia C. Olhede , Patrick J. Wolfe

In this paper, we introduce a novel model for random hypergraphs based on weighted random connection models. In accordance with the standard theory for hypergraphs, this model is constructed from a bipartite graph. In our stochastic model,…

Probability · Mathematics 2025-10-01 Morten Brun , Christian Hirsch , Peter Juhasz , Moritz Otto

We derive the finite size dependence of the clustering coefficient of scale-free random graphs generated by the configuration model with degree distribution exponent $2<\gamma<3$. Degree heterogeneity increases the presence of triangles in…

Disordered Systems and Neural Networks · Physics 2015-06-05 Pol Colomer-de-Simon , Marian Boguna

We consider the following question. We have a dense regular graph $G$ with degree $\alpha n$, where $\alpha>0$ is a constant. We add $m=o(n^2)$ random edges. The edges of the augmented graph $G(m)$ are given independent edge weights $X(e)$,…

Combinatorics · Mathematics 2026-04-06 Alan Frieze

In this paper, we study the task of detecting the edge dependency between two weighted random graphs. We formulate this task as a simple hypothesis testing problem, where under the null hypothesis, the two observed graphs are statistically…

Machine Learning · Computer Science 2024-09-25 Mor Oren , Vered Paslev , Wasim Huleihel

In this paper, we study some important statistics of the random graph in the directed preferential attachment model introduced by B. Bollob\'as, C. Borgs, J. Chayes and O. Riordan. First, we find a new asymptotic formula for the expectation…

Probability · Mathematics 2014-08-12 E. A. Grechnikov

The on-line nearest-neighbour graph on a sequence of $n$ uniform random points in $(0,1)^d$ ($d \in \N$) joins each point after the first to its nearest neighbour amongst its predecessors. For the total power-weighted edge-length of this…

Probability · Mathematics 2009-05-07 Andrew R. Wade

In this paper we introduce the optimal control of a kinetic model describing agents who migrate on a graph and interact within its nodes exchanging a physical quantity. As a prototype model, we consider the spread of an infectious disease…

Optimization and Control · Mathematics 2026-01-15 Jonathan Franceschi , Nadia Loy

In this paper we study weighted distances in scale-free spatial network models: hyperbolic random graphs (HRG), geometric inhomogeneous random graphs (GIRG) and scale-free percolation (SFP). In HRGs, $n=\Theta(\mathrm{e}^{R/2})$ vertices…

Probability · Mathematics 2019-11-21 Júlia Komjáthy , Bas Lodewijks

We offer an alternative proof, using the Stein-Chen method, of Bollob\'{a}s' theorem concerning the distribution of the extreme degrees of a random graph. Our proof also provides a rate of convergence of the extreme degree to its asymptotic…

Combinatorics · Mathematics 2023-11-20 Yaakov Malinovsky

We prove an asymptotic formula for the number of orientations with given out-degree (score) sequence for a graph $G$. The graph $G$ is assumed to have average degrees at least $n^{1/3 + \varepsilon}$ for some $\varepsilon > 0$, and to have…

Combinatorics · Mathematics 2020-01-14 Mikhail Isaev , Tejas Iyer , Brendan D. McKay
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