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The edge betweenness centrality of an edge is loosely defined as the fraction of shortest paths between all pairs of vertices passing through that edge. In this paper, we investigate graphs where the edge betweenness centrality of edges is…

Combinatorics · Mathematics 2017-09-15 Heather A. Newman , Hector Miranda , Rigoberto Florez , Darren A. Narayan

An old problem in mathematical physics deals with the structure of the dispersion relation of the Schr\"odinger operator $-\Delta+V(x)$ in $R^n$ with periodic potential near the edges of the spectrum. A well known conjecture says that…

Mathematical Physics · Physics 2020-10-28 Ngoc T. Do , Peter Kuchment , Frank Sottile

We observe that the technique of Markov contraction can be used to establish measure concentration for a broad class of non-contracting chains. In particular, geometric ergodicity provides a simple and versatile framework. This leads to a…

Probability · Mathematics 2013-12-06 Aryeh Kontorovich , Roi Weiss

Conventionally used exponential random graphs cannot directly model weighted networks as the underlying probability space consists of simple graphs only. Since many substantively important networks are weighted, this limitation is…

Probability · Mathematics 2019-06-10 Ryan DeMuse , Danielle Larcomb , Mei Yin

In statistical network analysis, models for binary adjacency matrices satisfying vertex exchangeability are commonly used. However, such models may fail to capture key features of the data-generating process when interactions, rather than…

Methodology · Statistics 2025-09-03 Ayoushman Bhattacharya , Nilanjan Chakraborty , Robert Lunde

We characterize some asymptotic properties of edge exchangeable random graphs in terms of the measure used to generate them. In particular, we give a necessary and sufficient condition for eventual forever connectedness, a sufficient…

Probability · Mathematics 2026-05-07 Edward Eriksson

We consider the number of crossings in a random embedding of a graph, $G$, with vertices in convex position. We give explicit formulas for the mean and variance of the number of crossings as a function of various subgraph counts of $G$.…

Probability · Mathematics 2024-10-14 Santiago Arenas-Velilla , Octavio Arizmendi , J. E. Paguyo

We study the asymptotics of large directed graphs, constrained to have certain densities of edges and/or outward $p$-stars. Our models are close cousins of exponential random graph models (ERGMs), in which edges and certain other subgraph…

Probability · Mathematics 2015-08-24 David Aristoff , Lingjiong Zhu

We show that if a graph contains few induced copies of a given graph then its edges are distribited unevenly.

Combinatorics · Mathematics 2007-05-23 Vladimir Nikiforov

Consider a `dense' Erd\H{o}s--R\'enyi random graph model $G=G_{n,M}$ with $n$ vertices and $M$ edges, where we assume the edge density $M/\binom{n}{2}$ is bounded away from 0 and 1. Fix $k=k(n)$ with $k/n$ bounded away from 0 and~1, and let…

Combinatorics · Mathematics 2025-04-01 Paul Balister , Emil Powierski , Alex Scott , Jane Tan

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

In this work we study the dynamics of systems composed of numerous interacting elements interconnected through a random weighted directed graph, such as models of random neural networks. We develop an original theoretical approach based on…

Chaotic Dynamics · Physics 2015-09-30 Gilles Wainrib , Mathieu Galtier

We present simple randomized and exchangeable improvements of Markov's inequality, as well as Chebyshev's inequality and Chernoff bounds. Our variants are never worse and typically strictly more powerful than the original inequalities. The…

Statistics Theory · Mathematics 2023-05-10 Aaditya Ramdas , Tudor Manole

Rank 1 inhomogeneous random graphs are a natural generalization of Erd\H{o}s R\'enyi random graphs. In this generalization each node is given a weight. Then the probability that an edge is present depends on the product of the weights of…

Probability · Mathematics 2021-07-28 Othmane Safsafi

Exchangeable random graphs serve as an important probabilistic framework for the statistical analysis of network data. In this work we develop an alternative parameterization for a large class of exchangeable random graphs, where the nodes…

Statistics Theory · Mathematics 2020-05-01 Jing Lei

A new, constructive proof with a small explicit constant is given to the Erd\H{o}s-Pyber theorem which says that the edges of a graph on $n$ vertices can be partitioned into complete bipartite subgraphs so that every vertex is covered at…

Combinatorics · Mathematics 2013-11-21 László Csirmaz , Péter Ligeti , Gábor Tardos

A random walk on a directed graph gives a Markov chain on the vertices of the graph. An important question that arises often in the context of Markov chain is whether the uniform distribution on the vertices of the graph is a stationary…

Data Structures and Algorithms · Computer Science 2016-03-11 Sourav Chakraborty , Akshay Kamath , Rameshwar Pratap

Let $D(n,r)$ be a random $r$-out regular directed multigraph on the set of vertices $\{1,\ldots,n\}$. In this work, we establish that for every $r \ge 2$, there exists $\eta_r>0$ such that $\text{diam}(D(n,r))=(1+\eta_r+o(1))\log_r{n}$. Our…

Probability · Mathematics 2015-04-28 Louigi Addario-Berry , Borja Balle , Guillem Perarnau

The pairwise comparisons method is a convenient tool used when the relative order of preferences among different concepts (alternatives) needs to be determined. There are several popular implementations of this method, including the…

Discrete Mathematics · Computer Science 2018-02-08 Konrad Kułakowski

The methods of non-homogeneous random graphs calibration are developed for social networks simulation. The graphs are calibrated by the degree distributions of the vertices and the edges. The mathematical foundation of the methods is formed…

Social and Information Networks · Computer Science 2019-04-05 V. N. Zadorozhnyi , E. B. Yudin
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