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Large random matrices appear in different fields of mathematics and physics such as combinatorics, probability theory, statistics, operator theory, number theory, quantum field theory, string theory etc... In the last ten years, they…

Probability · Mathematics 2007-05-23 Alice Guionnet

A method is introduced for studying large deviations in the context of statistical physics of disordered systems. The approach, based on an extension of the cavity method to atypical realizations of the quenched disorder, allows us to…

Disordered Systems and Neural Networks · Physics 2009-11-11 Olivier Rivoire

In recent years there has been much progress in graph theory on questions of the following type. What is the threshold for a certain large substructure to appear in a random graph? When does a random graph contain all structures from a…

Combinatorics · Mathematics 2017-02-10 Julia Böttcher

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

This paper investigate the sparse multi-type Erd\H{o}s R\'enyi random graphs studied in S\"{o}derberg~\cite{soderberg2002general} and also Bollob\'as et al.~\cite{bollobas2007phase}. Although the corresponding central limit results are…

Probability · Mathematics 2025-12-17 Rui Yu , Wen Sun

We introduce a correspondence principle (analogous to the Furstenberg correspondence principle) that allows one to extract an infinite random graph or hypergraph from a sequence of increasingly large deterministic graphs or hypergraphs. As…

Combinatorics · Mathematics 2007-06-13 Terence Tao

We present a large-deviations/thermodynamic approach to the classic problem of percolation on the complete graph. Specifically, we determine the large-deviation rate function for the probability that the giant component occupies a fixed…

Probability · Mathematics 2011-11-10 Marek Biskup , Lincoln Chayes , S. Alex Smith

This survey on graphs of large girth consists of two parts. The first deals with some aspects of algebraic and extremal graph theory loosely related to the Moore bound. Our point of departure for the second, Ramsey theoretic, part are some…

Combinatorics · Mathematics 2024-03-21 Christian Reiher

We identify the upper large deviation probability for the number of edges in scale-free geometric random graph models as the space volume goes to infinity. Our result covers the models of scale-free percolation, the Boolean model with…

We establish a so-called counting lemma that allows embeddings of certain linear uniform hypergraphs into sparse pseudorandom hypergraphs, generalizing a result for graphs [Embedding graphs with bounded degree in sparse pseudorandom graphs,…

Combinatorics · Mathematics 2017-11-01 Yoshiharu Kohayakawa , Guilherme O. Mota , Mathias Schacht , Anusch Taraz

We introduce and develop a theory of limits for sequences of sparse graphs based on $L^p$ graphons, which generalizes both the existing $L^\infty$ theory of dense graph limits and its extension by Bollob\'as and Riordan to sparse graphs…

Combinatorics · Mathematics 2019-08-19 Christian Borgs , Jennifer T. Chayes , Henry Cohn , Yufei Zhao

We prove a version of Szemeredi's regularity lemma for subsets of a typical random set in F_p^n. As an application, a result on the distribution of three-term arithmetic progressions in sparse sets is discussed.

Combinatorics · Mathematics 2010-04-23 Hoi H. Nguyen

The upper tail problem in a random graph asks to estimate the probability that the number of copies of some fixed subgraph in an Erd\H{o}s--R\'enyi random graph exceeds its expectation by some constant factor. There has been much exciting…

Combinatorics · Mathematics 2020-10-27 Yang P. Liu , Yufei Zhao

We prove algorithmic weak and \Szemeredi{} regularity lemmas for several classes of sparse graphs in the literature, for which only weak regularity lemmas were previously known. These include core-dense graphs, low threshold rank graphs,…

Data Structures and Algorithms · Computer Science 2025-05-30 Greg Bodwin , Santosh Vempala

We develop a theory to measure the variance and covariance of probability distributions defined on the nodes of a graph, which takes into account the distance between nodes. Our approach generalizes the usual (co)variance to the setting of…

Physics and Society · Physics 2021-08-19 Karel Devriendt , Samuel Martin-Gutierrez , Renaud Lambiotte

For any finite colored graph we define the empirical neighborhood measure, which counts the number of vertices of a given color connected to a given number of vertices of each color, and the empirical pair measure, which counts the number…

Probability · Mathematics 2016-08-16 Kwabena Doku-Amponsah , Peter Mörters

We prove general nonlinear large deviation estimates similar to Chatterjee-Dembo's original bounds except that we do not require any second order smoothness. Our approach relies on convex analysis arguments and is valid for a broad class of…

Probability · Mathematics 2020-04-21 Fanny Augeri

We prove a variant of the abstract probabilistic version of Szemer\'edi's regularity lemma, due to Tao, which applies to a number of structures (including graphs, hypergraphs, hypercubes, graphons, and many more) and works for random…

Combinatorics · Mathematics 2016-07-26 Pandelis Dodos , Vassilis Kanellopoulos , Thodoris Karageorgos

In this paper we introduce a general framework for the study of limits of relational structures in general and graphs in particular, which is based on a combination of model theory and (functional) analysis. We show how the various…

Combinatorics · Mathematics 2021-04-23 Jaroslav Nesetril , Patrice Ossona De Mendez

Recent work on the structure of social networks and the internet has focussed attention on graphs with distributions of vertex degree that are significantly different from the Poisson degree distributions that have been widely studied in…

Statistical Mechanics · Physics 2009-10-31 M. E. J. Newman , S. H. Strogatz , D. J. Watts