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We prove a central limit theorem applicable to one dimensional stochastic approximation algorithms that converge to a point where the error terms of the algorithm do not vanish. We show how this applies to a certain class of these…

Probability · Mathematics 2011-02-24 Henrik Renlund

We consider subgraph counts in general preferential attachment models with power-law degree exponent $\tau>2$. For all subgraphs $H$, we find the scaling of the expected number of subgraphs as a power of the number of vertices. We prove our…

Probability · Mathematics 2026-01-14 Alessandro Garavaglia , Clara Stegehuis

We consider large uniform labeled random graphs in different classes with prescribed decorations in their modular decomposition. Our main result is the estimation of the number of copies of every graph as an induced subgraph. As a…

Combinatorics · Mathematics 2023-10-25 Théo Lenoir

A graph is said to be $\mathcal{H}(n, \Delta)$-universal if it contains every graph on $n$ vertices with maximum degree at most $\Delta$. Using a `matching-based' embedding technique introduced by Alon and F\"uredi, Dellamonica, Kohayakawa,…

Combinatorics · Mathematics 2017-07-26 Asaf Ferber , Rajko Nenadov

We consider random geometric graphs on the plane characterized by a non-uniform density of vertices. In particular, we introduce a graph model where $n$ vertices are independently distributed in the unit disc with positions, in polar…

Disordered Systems and Neural Networks · Physics 2022-04-06 C. T. Martinez-Martinez , J. A. Mendez-Bermudez , Francisco A. Rodrigues , Ernesto Estrada

We introduce and study a novel semi-random multigraph process, described as follows. The process starts with an empty graph on $n$ vertices. In every round of the process, one vertex $v$ of the graph is picked uniformly at random and…

A metric probability space $M$ admits thresholds if the random geometric graph on $M$ has a threshold for every monotone graph property. We connect the existence of thresholds to the uniform expansion of $M$ and prove that all standard…

Combinatorics · Mathematics 2026-05-21 Bhargav Narayanan

We propose the following model of a random graph on n vertices. Let F be a distribution in R_+^{n(n-1)/2} with a coordinate for every pair i$ with 1 \le i,j \le n. Then G_{F,p} is the distribution on graphs with n vertices obtained by…

Combinatorics · Mathematics 2011-08-09 Alan Frieze , Santosh Vempala , Juan Vera

Threshold graphs are graphs that can be characterized in a number of different ways. For example, they are graphs that are $P_4,\ C_4,\ 2K_2$--free. They may also be characterized by a finite sequence of positive integers $a_1, \ldots,…

Combinatorics · Mathematics 2026-05-07 James L. Borg , Irene Sciriha , Zoia Sherman

We present and study in this paper a simple algorithm that produces so called growing Parallel Random Apollonian Networks (P-RAN) in any dimension d. Analytical derivations show that these networks still exhibit small-word and scale-free…

Discrete Mathematics · Computer Science 2009-04-30 Nicolas Bonnel , Pierre-François Marteau , Gildas G. Ménier

Graphs with diverse structural characteristics play a central role in modelling and optimization tasks. The ability to generate different types of graphs that exhibit shared properties is likewise essential for algorithm selection and…

Neural and Evolutionary Computing · Computer Science 2026-03-31 Hendrik Richter , Frank Neumann

In this manuscript we consider the set of Dyck paths equipped with the uniform measure, and we study the statistical properties of a deformation of the observable "area below the Dyck path" as the size $N$ of the path goes to infinity. The…

Combinatorics · Mathematics 2020-10-29 Sergio Caracciolo , Vittorio Erba , Andrea Sportiello

The H-free process, for some fixed graph H, is the random graph process defined by starting with an empty graph on n vertices and then adding edges one at a time, chosen uniformly at random subject to the constraint that no H subgraph is…

Combinatorics · Mathematics 2015-05-13 Tom Bohman , Peter Keevash

Random graphs have played an instrumental role in modelling real-world networks arising from the internet topology, social networks, or even protein-interaction networks within cells. Percolation, on the other hand, has been the fundamental…

Probability · Mathematics 2018-09-12 Souvik Dhara

In this thesis, which is supervised by Dr. David Penman, we examine random interval graphs. Recall that such a graph is defined by letting $X_{1},\ldots X_{n},Y_{1},\ldots Y_{n}$ be $2n$ independent random variables, with uniform…

Combinatorics · Mathematics 2019-05-27 Vasileios Iliopoulos

This work will appear as a chapter in a forthcoming volume titled "Topics in Probabilistic Graph Theory". A theory of scaling limits for random graphs has been developed in recent years. This theory gives access to the large-scale geometric…

Probability · Mathematics 2024-10-18 Louigi Addario-Berry , Christina Goldschmidt

Graphs are used in many disciplines to model the relationships that exist between objects in a complex discrete system. Researchers may wish to compare a network of interest to a "typical" graph from a family (or ensemble) of graphs which…

Combinatorics · Mathematics 2025-08-08 Catherine Greenhill

Symmetric matrices with zero row sums occur in many theoretical settings and in real-life applications. When the offdiagonal elements of such matrices are i.i.d. random variables and the matrices are large, the eigenvalue distributions…

Disordered Systems and Neural Networks · Physics 2023-06-27 Pawat Akara-pipattana , Oleg Evnin

Using a maximum entropy principle to assign a statistical weight to any graph, we introduce a model of random graphs with arbitrary degree distribution in the framework of standard statistical mechanics. We compute the free energy and the…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. Bauer , D. Bernard

We establish tightness of graph-based stochastic processes in the space $D[0+\epsilon,1-\epsilon]$ with $\epsilon >0$ that allows for discontinuities of the first kind. The graph-based stochastic processes are based on statistics…

Probability · Mathematics 2023-03-02 Lynna Chu , Hao Chen
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