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We introduce a simple technique for proving the transience of certain processes defined on the random tree $\mathcal{G}$ generated by a supercritical branching process. We prove the transience for once-reinforced random walks on…

Probability · Mathematics 2007-05-23 Andrea Collevecchio

The field of molecular excitons and related supramolecular systems has largely focused on aggregates where nearest-neighbour couplings dominate. We propose that radically different states can be produced by moving beyond that paradigm. In…

Chemical Physics · Physics 2025-02-04 Gregory D. Scholes

We study the impact of the coupling topology on the ability of various networked dynamical systems to generate extreme events. By determining the coupling strength that is necessary to generate an extreme event in the collective dynamics of…

Chaotic Dynamics · Physics 2026-05-29 Christian Hechler , Timo Bröhl , Ulrike Feudel , Klaus Lehnertz

PageRank is a well-known algorithm for measuring centrality in networks. It was originally proposed by Google for ranking pages in the World-Wide Web. One of the intriguing empirical properties of PageRank is the so-called `power-law…

Probability · Mathematics 2018-03-19 Alessandro Garavaglia , Remco van der Hofstad , Nelly Litvak

We prove that a connected graph has linear rank-width 1 if and only if it is a distance-hereditary graph and its split decomposition tree is a path. An immediate consequence is that one can decide in linear time whether a graph has linear…

Discrete Mathematics · Computer Science 2014-07-09 Binh-Minh Bui-Xuan , Mamadou Moustapha Kanté , Vincent Limouzy

A coupling of random walkers on the same finite graph, who take turns sequentially, is said to be an avoidance coupling if the walkers never collide. Previous studies of these processes have focused almost exclusively on complete graphs, in…

Probability · Mathematics 2020-10-14 Erik Bates , Moumanti Podder

We consider the probability that a spanning tree chosen uniformly at random from a graph can be partitioned into a fixed number $k$ of trees of equal size by removing $k-1$ edges. In that case, the spanning tree is called {\em splittable}.…

Data Structures and Algorithms · Computer Science 2026-02-25 David Gillman , Jacob Platnick , Dana Randall

In this paper, we study a parallel version of Galton-Watson processes for the random generation of tree-shaped structures. Random trees are useful in many situations (testing, binary search, simulation of physics phenomena,...) as attests…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-06-22 Olivier Bodini , Camille Coti , Julien David

The property of spatial mixing and strong spatial mixing in spin systems has been of interest because of its implications on uniqueness of Gibbs measures on infinite graphs and efficient approximation of counting problems that are otherwise…

Probability · Mathematics 2012-07-06 David Gamarnik , Dmitry Katz , Sidhant Misra

The simple Galton--Watson process describes populations where individuals live one season and are then replaced by a random number of children. It can also be viewed as a way of generating random trees, each vertex being an individual of…

Statistics Theory · Mathematics 2008-11-17 Peter Jagers , Serik Sagitov

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

We investigate the threshold probability for connectivity of sparse graphs under weak assumptions. As a corollary this completely solve the problem for Cartesian powers of arbitrary graphs. In detail, let $G$ be a connected graph on $k$…

Combinatorics · Mathematics 2013-12-04 Felix Joos

We present a framework to define a large class of neural networks for which, by construction, training by gradient flow provably reaches arbitrarily low loss when the number of parameters grows. Distinct from the fixed-space global…

Optimization and Control · Mathematics 2025-01-13 David A. R. Robin , Kevin Scaman , Marc Lelarge

Random graphs are a central element of the study of complex dynamical networks such as the internet, the brain, or socioeconomic phenomena. New methods to generate random graphs can spawn new applications and give insights into more…

Quantum Physics · Physics 2020-04-06 Hamza Jnane , Giuseppe Di Molfetta , Filippo M. Miatto

We determine to within a constant factor the threshold for the property that two random k-uniform hypergraphs with edge probability p have an edge-disjoint packing into the same vertex set. More generally, we allow the hypergraphs to have…

Combinatorics · Mathematics 2016-03-01 Béla Bollobás , Svante Janson , Alex Scott

We study connected graphs with a fixed degree sequence, in the sparse setting where the number of edges grows linearly in the number of vertices. Using the relation to the configuration model, we identify the number of such connected graphs…

Combinatorics · Mathematics 2026-05-11 Sasha Bell , Serte Donderwinkel , Remco van der Hofstad

Recent progress in the study of the contact process [2] has verified that the extinction-survival threshold $\lambda_1$ on a Galton-Watson tree is strictly positive if and only if the offspring distribution $\xi$ has an exponential tail. In…

Probability · Mathematics 2019-10-31 Danny Nam , Oanh Nguyen , Allan Sly

We show that the local limit of unicellular maps whose genus is proportional to the number of edges is a supercritical geometric Galton-Watson tree conditioned to survive. The proof relies on enumeration results obtained via the recent…

Probability · Mathematics 2015-05-20 Omer Angel , Guillaume Chapuy , Nicolas Curien , Gourab Ray

This article introduces a model for interacting vertex-reinforced random walks, each taking values on a complete sub-graph of a locally finite undirected graph. The transition probability for a walk to a given vertex depends on the…

Probability · Mathematics 2025-08-25 Fernando P. A. Prado , Rafael A. Rosales

Node embeddings map graph vertices into low-dimensional Euclidean spaces while preserving structural information. They are central to tasks such as node classification, link prediction, and signal reconstruction. A key goal is to design…

Machine Learning · Computer Science 2026-02-18 Valentin de Bassompierre , Jean-Charles Delvenne , Laurent Jacques