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The spectral density of random graphs with topological constraints is analysed using the replica method. We consider graph ensembles featuring generalised degree-degree correlations, as well as those with a community structure. In each case…

Disordered Systems and Neural Networks · Physics 2011-04-08 Tim Rogers , Conrad Pérez Vicente , Koujin Takeda , Isaac Pérez Castillo

Garbe, Hladk\'y, \v{S}ileikis and Skerman [Ann. Inst. Henri Poincar\'e Probab. Stat., 60 (2024), pp. 2878-2922] recently introduced a general class of random graph processes called flip processes and proved that the typical evolution of…

Combinatorics · Mathematics 2025-11-11 Eng Keat Hng

We study the automorphism group of graphons (graph limits). We prove that after an appropriate "standardization" of the graphon, the automorphism group is compact. Furthermore, we characterize the orbits of the automorphism group on…

Combinatorics · Mathematics 2021-02-17 László Lovász , Balázs Szegedy

We introduce a new class of countably infinite random geometric graphs, whose vertices are points in a metric space, and vertices are adjacent independently with probability p if the metric distance between the vertices is below a given…

Combinatorics · Mathematics 2012-08-28 Anthony Bonato , Jeannette Janssen

We analyze the convergence of the spectrum of large random graphs to the spectrum of a limit infinite graph. We apply these results to graphs converging locally to trees and derive a new formula for the Stieljes transform of the spectral…

Probability · Mathematics 2009-05-05 Charles Bordenave , Marc Lelarge

The emerging theory of graph limits exhibits an analytic perspective on graphs, showing that many important concepts and tools in graph theory and its applications can be described more naturally (and sometimes proved more easily) in…

Combinatorics · Mathematics 2023-08-01 Omri Ben-Eliezer , Eldar Fischer , Amit Levi , Yuichi Yoshida

The recent theory of graph limits gives a powerful framework for understanding the properties of suitable (convergent) sequences $(G_n)$ of graphs in terms of a limiting object which may be represented by a symmetric function $W$ on…

Combinatorics · Mathematics 2012-08-21 Bela Bollobas , Svante Janson , Oliver Riordan

The law of a finite graph is a probability measure induced by the orbits of the graph under its automorphism group. Every law satisfies the intrinsic mass transport principle, which is also known as unimodularity. We discuss the convergence…

Combinatorics · Mathematics 2011-03-30 Igor Artemenko

In this note, we show how to obtain a "characteristic power series" of graphons -- infinite limits of dense graphs -- as the limit of normalized reciprocal characteristic polynomials. This leads to a new characterization of graph…

Combinatorics · Mathematics 2022-09-20 Joshua N. Cooper

We consider large uniform labeled random graphs in different classes with few induced $P_4$ ($P_4$ is the graph consisting of a single line of $4$ vertices) which generalize the case of cographs. Our main result is the convergence to a…

Probability · Mathematics 2023-10-25 Théo Lenoir

We consider a class of growing random graphs obtained by creating vertices sequentially one by one: at each step, we choose uniformly the neighbours of the newly created vertex; its degree is a random variable with a fixed but arbitrary…

Combinatorics · Mathematics 2013-11-13 Svante Janson , Simone Severini

We define direct sums and a corresponding notion of connectedness for graph limits. Every graph limit has a unique decomposition as a direct sum of connected components. As is well-known, graph limits may be represented by symmetric…

Combinatorics · Mathematics 2008-04-10 Svante Janson

In this paper we describe a triple correspondence between graph limits, information theory and group theory. We put forward a new graph limit concept called log-convergence that is closely connected to dense graph limits but its main…

Combinatorics · Mathematics 2015-04-06 Balazs Szegedy

Let $G$ be a finite, simple connected graph. The average distance of a vertex $v$ of $G$ is the arithmetic mean of the distances from $v$ to all other vertices of $G$. The remoteness $\rho(G)$ of $G$ is the maximum of the average distances…

Combinatorics · Mathematics 2024-05-27 Peter Dankelmann , Sonwabile Mafunda , Sufiyan Mallu

Let $G=(V,E)$ be a finite, combinatorial graph. We define a notion of curvature on the vertices $V$ via the inverse of the resistance distance matrix. We prove that this notion of curvature has a number of desirable properties. Graphs with…

Combinatorics · Mathematics 2023-02-22 Karel Devriendt , Andrea Ottolini , Stefan Steinerberger

Graphons are analytic objects associated with convergent sequences of graphs. Problems from extremal combinatorics and theoretical computer science led to a study of graphons determined by finitely many subgraph densities, which are…

Combinatorics · Mathematics 2019-03-20 Roman Glebov , Daniel Kral , Jan Volec

Given a compact metric space $X$ and a probability measure in the $\sigma-$algebra of Borel subsets of $X$, we will establish a dominated convergence theorem for ultralimits of sequences of integrable maps and apply it to deduce a…

Dynamical Systems · Mathematics 2018-05-25 Maria Carvalho , Fernando Moreira

We give a cohomological criterion for certain decomposition of Borel graphs, which is an analog of Dunwoody's work on accessibility of groups. As an application, we prove that a Borel graph $(X,G)$ with uniformly bounded degrees of…

Group Theory · Mathematics 2026-03-12 Hiroki Ishikura

For a subset $ S $ of $ \mathbb R^d$, $ S$-graphs are the intersection graphs of specific transformations of $ S $. The class of Burling graphs is a class of triangle-free graphs with arbitrarily large chromatic number that has attracted…

Combinatorics · Mathematics 2023-08-30 Pegah Pournajafi

We consider the problem of estimating the topology of multiple networks from nodal observations, where these networks are assumed to be drawn from the same (unknown) random graph model. We adopt a graphon as our random graph model, which is…

Machine Learning · Statistics 2022-02-14 Madeline Navarro , Santiago Segarra