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A graph is weakly $2$-colored if the nodes are labeled with colors black and white such that each black node is adjacent to at least one white node and vice versa. In this work we study the distributed computational complexity of weak…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-19 Alkida Balliu , Juho Hirvonen , Dennis Olivetti , Jukka Suomela

Weak and strong coloring numbers are generalizations of the degeneracy of a graph, where for each natural number $k$, we seek a vertex ordering such every vertex can (weakly respectively strongly) reach in $k$ steps only few vertices with…

Combinatorics · Mathematics 2021-04-08 Zdeněk Dvořák , Jakub Pekárek , Torsten Ueckerdt , Yelena Yuditsky

Local convergence has emerged as a fundamental tool for analyzing sparse random graph models. We introduce a new notion of local convergence, color convergence, based on the Weisfeiler-Leman algorithm. Color convergence fully characterizes…

Discrete Mathematics · Computer Science 2025-10-27 Alexander Pluska , Sagar Malhotra

We consider the problem of detecting a tight community in a sparse random network. This is formalized as testing for the existence of a dense random subgraph in a random graph. Under the null hypothesis, the graph is a realization of an…

Statistics Theory · Mathematics 2014-09-26 Ery Arias-Castro , Nicolas Verzelen

We prove measurable analogues of Whitney's classical theorems on weak isomorphisms of finite graphs. In the setting of locally finite graphings, we introduce a notion of weak isomorphism as an edge-measure-preserving Borel bijection that…

Combinatorics · Mathematics 2026-05-18 Márton Borbényi , Grigory Terlov , László Márton Tóth

Two landmark results in combinatorial random matrix theory, due to Koml\'os and Costello-Tao-Vu, show that discrete random matrices and symmetric discrete random matrices are typically nonsingular. In particular, in the language of graph…

Combinatorics · Mathematics 2023-03-10 Margalit Glasgow , Matthew Kwan , Ashwin Sah , Mehtaab Sawhney

This paper investigates properties of the class of graphs based on exchangeable point processes. We provide asymptotic expressions for the number of edges, number of nodes and degree distributions, identifying four regimes: (i) a dense…

Statistics Theory · Mathematics 2025-02-06 François Caron , Francesca Panero , Judith Rousseau

We consider a Galton-Watson tree where each node is marked independently of each others with a probability depending on its outdegree. We give a complete picture of the local convergence of critical or sub-critical marked Galton-Watson…

Probability · Mathematics 2025-09-29 Romain Abraham , Sonia Boulal , Pierre Debs

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

Local Irregularity Conjecture states that every simple connected graph, except special cacti, can be decomposed into at most three locally irregular graphs, i.e., graphs in which adjacent vertices have different degrees. The connected…

Combinatorics · Mathematics 2025-02-13 Igor Grzelec , Alfréd Onderko , Mariusz Woźniak

We prove inequalities between the densities of various bipartite subgraphs in signed graphs and graphons. One of the main inequalities is that the density of any bipartite graph with girth r cannot exceed the density of the r-cycle. This…

Combinatorics · Mathematics 2010-04-20 László Lovász

Local algorithms on graphs are algorithms that run in parallel on the nodes of a graph to compute some global structural feature of the graph. Such algorithms use only local information available at nodes to determine local aspects of the…

Probability · Mathematics 2013-04-09 David Gamarnik , Madhu Sudan

Sidorenko's conjecture states that the number of copies of a bipartite graph $H$ in a graph $G$ is asymptotically minimised when $G$ is a quasirandom graph. A notorious example where this conjecture remains open is when $H=K_{5,5}\setminus…

Combinatorics · Mathematics 2020-01-17 Joonkyung Lee , Bjarne Schülke

A graph $G$ is weakly $\gamma$-closed if every induced subgraph of $G$ contains one vertex $v$ such that for each non-neighbor $u$ of $v$ it holds that $|N(u)\cap N(v)|<\gamma$. The weak closure $\gamma(G)$ of a graph, recently introduced…

Discrete Mathematics · Computer Science 2022-11-04 Tomohiro Koana , Christian Komusiewicz , Frank Sommer

For a given homogeneous Poisson point process in $\mathbb{R}^d$ two points are connected by an edge if their distance is bounded by a prescribed distance parameter. The behaviour of the resulting random graph, the Gilbert graph or random…

Probability · Mathematics 2017-11-06 Matthias Reitzner , Matthias Schulte , Christoph Thaele

Under the assumption that sequences of graphs equipped with resistances, associated measures, walks and local times converge in a suitable Gromov-Hausdorff topology, we establish asymptotic bounds on the distribution of the…

Probability · Mathematics 2025-09-30 George Andriopoulos

In this paper we consider the Erd\H{o}s-R\'enyi random graph in the sparse regime in the limit as the number of vertices $n$ tends to infinity. We are interested in what this graph looks like when it contains many triangles, in two…

Probability · Mathematics 2026-01-27 Suman Chakraborty , Remco van der Hofstad , Frank den Hollander

In this paper, we derive the asymptotic distribution of the number of copies of a fixed graph $H$ in a random graph $G_n$ sampled from a sparse graphon model. Specifically, we provide a refined analysis that separates the contributions of…

Generalised degrees provide a natural bridge between local and global topological properties of networks. We define the generalised degree to be the number of neighbours of a node within one and two steps respectively. Tailored random graph…

Disordered Systems and Neural Networks · Physics 2013-09-17 Ekaterina S. Roberts , Anthonius C. C. Coolen

Local graph clustering is an important algorithmic technique for analysing massive graphs, and has been widely applied in many research fields of data science. While the objective of most (local) graph clustering algorithms is to find a…

Data Structures and Algorithms · Computer Science 2021-06-10 Peter Macgregor , He Sun