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We introduce a one-parametric family of tree growth models, in which branching probabilities decrease with branch age $\tau$ as $\tau^{-\alpha}$. Depending on the exponent $\alpha$, the scaling of tree depth with tree size $n$ displays a…

Populations and Evolution · Quantitative Biology 2015-02-04 Stephanie Keller-Schmidt , Murat Tugrul , Victor M. Eguiluz , Emilio Hernandez-Garcia , Konstantin Klemm

We study the uniform random graph $\mathsf{C}_n$ with $n$ vertices drawn from a subcritical class of connected graphs. Our main result is that the rescaled graph $\mathsf{C}_n / \sqrt{n}$ converges to the Brownian Continuum Random Tree…

Probability · Mathematics 2014-11-17 Konstantinos Panagiotou , Benedikt Stufler , Kerstin Weller

We study non-compact scaling limits of uniform random planar quadrangulations with a boundary when their size tends to infinity. Depending on the asymptotic behavior of the boundary size and the choice of the scaling factor, we observe…

Probability · Mathematics 2016-08-04 Erich Baur , Grégory Miermont , Gourab Ray

We study a random fragmentation process and its associated random tree. The process has earlier been studied by Dean and Majumdar (J. Phys. A: Math. Gen., vol. 35, L501--L507), who found a phase transition: the number of fragmentations is…

Probability · Mathematics 2007-05-23 S. Janson , R. Neininger

We prove a scaling limit theorem for the simple random walk on critical lattice trees in $\mathbb{Z}^d$, for $d\geq 8$. The scaling limit is the Brownian motion on the Integrated Super-Brownian Excursion (BISE) which is the same one that we…

Probability · Mathematics 2025-03-31 Gérard Ben Arous , Manuel Cabezas , Alexander Fribergh

We consider a variant of the radial spanning tree introduced by Baccelli and Bordenave. Like the original model, our model is a tree rooted at the origin, built on the realization of a planar Poisson point process. Unlike it, the paths of…

Probability · Mathematics 2014-03-24 Luiz Renato Fontes , Leon Valencia , Glauco Valle

In the critical beta-splitting model of a random $n$-leaf rooted tree, clades are recursively split into sub-clades, and a clade of $m$ leaves is split into sub-clades containing $i$ and $m-i$ leaves with probabilities $\propto 1/(i(m-i))$.…

Probability · Mathematics 2024-12-18 David Aldous , Svante Janson

We introduce a general model of trapping for random walks on graphs. We give the possible scaling limits of these Randomly Trapped Random Walks on $\mathbb {Z}$. These scaling limits include the well-known fractional kinetics process, the…

Probability · Mathematics 2015-10-30 Gérard Ben Arous , Manuel Cabezas , Jiří Černý , Roman Royfman

We present a new finite-size scaling method for the random walks (RW) superseeding a previously widely used renormalization group approach, which is shown here to be inconsistent. The method is valid in any dimension and is based on the…

Condensed Matter · Physics 2009-10-22 Achille Giacometti , Hisao Nakanishi

We show that the Gromov-Hausdorff-Prohorov scaling limit of a critical percolation cluster on a random hyperbolic triangulation of the half-plane is the Brownian continuum random tree. As a corollary, we obtain that a simple random walk on…

Probability · Mathematics 2023-11-21 Eleanor Archer , David A. Croydon

We study both numerically and analytically what happens to a random graph of average connectivity "alpha" when its leaves and their neighbors are removed iteratively up to the point when no leaf remains. The remnant is made of isolated…

Statistical Mechanics · Physics 2009-11-07 M. Bauer , O. Golinelli

We consider the random directed graph $\vec{G}(n,p)$ with vertex set $\{1,2,\ldots,n\}$ in which each of the $n(n-1)$ possible directed edges is present independently with probability $p$. We are interested in the strongly connected…

Probability · Mathematics 2021-08-05 Christina Goldschmidt , Robin Stephenson

We apply the theory of markov random fields on trees to derive a phase transition in the number of samples needed in order to reconstruct phylogenies. We consider the Cavender-Farris-Neyman model of evolution on trees, where all the inner…

Probability · Mathematics 2007-05-23 Elchanan Mossel

This paper studies the critical and near-critical regimes of the planar random-cluster model on $\mathbb Z^2$ with cluster-weight $q\in[1,4]$ using novel coupling techniques. More precisely, we derive the scaling relations between the…

Probability · Mathematics 2020-12-01 Hugo Duminil-Copin , Ioan Manolescu

We consider the genealogy tree for a critical branching process conditioned on non-extinction. We enumerate vertices in each generation of the tree so that for each two generations one can define a monotone map describing the…

Probability · Mathematics 2010-08-27 Yuri Bakhtin

Let $F(N,m)$ denote a random forest on a set of $N$ vertices, chosen uniformly from all forests with $m$ edges. Let $F(N,p)$ denote the forest obtained by conditioning the Erdos-Renyi graph $G(N,p)$ to be acyclic. We describe scaling limits…

Probability · Mathematics 2018-07-04 James Martin , Dominic Yeo

We show that the Brownian continuum random tree is the Gromov-Hausdorff-Prohorov scaling limit of the uniform spanning tree on high-dimensional graphs including the $d$-dimensional torus $\mathbb{Z}_n^d$ with $d>4$, the hypercube…

Probability · Mathematics 2022-04-14 Eleanor Archer , Asaf Nachmias , Matan Shalev

Scaling regression to large datasets is a common problem in many application areas. We propose a two step approach to scaling regression to large datasets. Using a regression tree (CART) to segment the large dataset constitutes the first…

Machine Learning · Statistics 2017-07-26 Rajiv Sambasivan , Sourish Das

We investigate the phase structure of non-commutative scalar field theories and find evidence for ordered phases which break translation invariance. A self-consistent one-loop analysis indicates that the transition into these ordered phases…

High Energy Physics - Theory · Physics 2009-10-31 Steven S. Gubser , Shivaji L. Sondhi

In recent years, non-parametric methods utilizing random walks on graphs have been used to solve a wide range of machine learning problems, but in their simplest form they do not scale well due to the quadratic complexity. In this paper, a…

Machine Learning · Computer Science 2012-10-19 Saeed Amizadeh , Bo Thiesson , Milos Hauskrecht