English
Related papers

Related papers: Local limit theorem for joint subgraph counts

200 papers

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

A \emph{locally irregular graph} is a graph whose adjacent vertices have distinct degrees. We say that a graph $G$ can be decomposed into $k$ locally irregular subgraphs if its edge set may be partitioned into $k$ subsets each of which…

Combinatorics · Mathematics 2017-03-02 Jakub Przybyło

We study random digraphs on sequences of expanders with bounded average degree {which converge locally in probability}. We prove that the threshold for the existence of a giant strongly connected component, as well as the asymptotic…

Probability · Mathematics 2022-09-01 Yeganeh Alimohammadi , Christian Borgs , Amin Saberi

In the dense graph limit theory, the topology of the set of graphs is defined by the distribution of the subgraphs spanned by finite number of random vertices. Vera T. S\'os proposed a question that if we consider only the number of edges…

Combinatorics · Mathematics 2015-08-21 Endre Csóka

In this paper we consider a dynamic version of the Erd\H{o}s-R\'{e}nyi random graph, in which edges independently appear and disappear in time, with the on- and off times being exponentially distributed. The focus lies on the evolution of…

Probability · Mathematics 2024-07-04 Rajat Subhra Hazra , Nikolai Kriukov , Michel Mandjes

An additive functional of a rooted tree is a functional that can be calculated recursively as the sum of the values of the functional over the branches, plus a certain toll function. Janson recently proved a central limit theorem for…

Combinatorics · Mathematics 2019-11-12 Dimbinaina Ralaivaosaona , Matas Šileikis , Stephan Wagner

We get central limit type theorems for the total number of edges in the generalized random graphs with random vertex weights under different moment conditions on distributions of the weights.

Probability · Mathematics 2017-03-06 Zhi Shui Hu , Vladimir V. Ulyanov , Qun Qiang Feng

The local tree-width of a graph G=(V,E) is the function ltw^G: N -> N that associates with every natural number r the maximal tree-width of an r-neighborhood in G. Our main graph theoretic result is a decomposition theorem for graphs with…

Combinatorics · Mathematics 2007-05-23 Martin Grohe

We establish the (non-lattice) local limit theorem for products of i.i.d. random variables on an arbitrary simply connected nilpotent Lie group $G$, where the variables are allowed to be non-centered. Our result also improves on the known…

Probability · Mathematics 2023-12-14 Timothée Bénard , Emmanuel Breuillard

Given a probability measure on a finitely generated group, the local limit problem consists in finding asymptotics of $p_n(e,e)$, the probability that the random walk at time $n$ is at the origin. We give the classification of all possible…

Group Theory · Mathematics 2025-07-22 Matthieu Dussaule

The maximum likelihood threshold (MLT) of a graph $G$ is the minimum number of samples to almost surely guarantee existence of the maximum likelihood estimate in the corresponding Gaussian graphical model. We give a new characterization of…

A soft random graph $G(n,r,p)$ can be obtained from the random geometric graph $G(n,r)$ by keeping every edge in $G(n,r)$ with probability $p$. The soft random simplicial complexes is a model for random simplicial complexes built over the…

Probability · Mathematics 2025-07-15 Julián David Candela

The purpose of this paper is to study the limiting distribution of special {\it additive functionals} on random planar maps, namely the number of occurrences of a given {\it pattern}. The main result is a central limit theorem for these…

Combinatorics · Mathematics 2024-06-11 Michael Drmota , Eva-Maria Hainzl , Nick Wormald

Let $T(H, G_n)$ be the number of monochromatic copies of a fixed connected graph $H$ in a uniformly random coloring of the vertices of the graph $G_n$. In this paper we give a complete characterization of the limiting distribution of $T(H,…

Probability · Mathematics 2021-03-03 Bhaswar B. Bhattacharya , Sumit Mukherjee

Our main results are quantitative bounds in the multivariate normal approximation of centred subgraph counts in random graphs generated by a general graphon and independent vertex labels. We are interested in these statistics because they…

Probability · Mathematics 2021-06-17 Gursharn Kaur , Adrian Röllin

Consider the uniform random graph $G(n,M)$ with $n$ vertices and $M$ edges. Erd\H{o}s and R\'enyi (1960) conjectured that the limit $$ \lim_{n \to \infty} \Pr\{G(n,\textstyle{n\over 2}) is planar}} $$ exists and is a constant strictly…

Combinatorics · Mathematics 2012-05-01 Marc Noy , Vlady Ravelomanana , Juanjo Rué

Following a general program of studying limits of discrete structures, and motivated by the theory of limit objects of converge sequences of dense simple graphs, we study the limit of graph sequences such that every edge is labeled by an…

Combinatorics · Mathematics 2010-10-26 László Lovász , Balázs Szegedy

We establish an abstract local ergodic theorem, under suitable space-time scaling, for the (boundary-driven) symmetric exclusion process on an increasing sequence of balls covering an infinite weighted graph. The proofs are based on 1-block…

Probability · Mathematics 2017-08-25 Joe P. Chen

The objective of this study is to investigate the limiting behavior of a subgraph counting process. The subgraph counting process we consider counts the number of subgraphs having a specific shape that exist outside an expanding ball as the…

Probability · Mathematics 2016-02-12 Takashi Owada

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 2022-12-21 Madeline Navarro , Santiago Segarra