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Consider the d-dimensional lattice Z^d where each vertex is ``open'' or ``closed'' with probability p or 1-p, respectively. An open vertex v is connected by an edge to the closest open vertex w such that the dth co-ordinates of v and w…

Probability · Mathematics 2016-09-07 Sreela Gangopadhyay , Rahul Roy , Anish Sarkar

In the on-line nearest-neighbour graph (ONG), each point after the first in a sequence of points in R^d is joined by an edge to its nearest-neighbour amongst those points that precede it in the sequence. We study the large-sample asymptotic…

Probability · Mathematics 2008-05-13 Mathew D. Penrose , Andrew R. Wade

We study the growth of random networks under a constraint that the diameter, defined as the average shortest path length between all nodes, remains approximately constant. We show that if the graph maintains the form of its degree…

Statistical Mechanics · Physics 2007-05-23 Rajan M. Lukose , Lada A. Adamic

We study a system of coalescing random walks on the integer lattice $\mathbb{Z}^{d}$ in which the walk is oriented in the $d$-th direction and follows certain specified rules. We first study the geometry of the paths and show that, almost…

Probability · Mathematics 2022-08-23 Azadeh Parvaneh , Afshin Parvardeh , Rahul Roy

For real world systems, nonuniform medium is ubiquitous. Therefore, we investigate the diffusion-limited-aggregation process on a two dimensional directed small-world network instead of regular lattice. The network structure is established…

Computational Physics · Physics 2007-05-23 Jie Ren , Wen-Xu Wang , Gang Yan , Bing-Hong Wang

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

In Bhatt and Roy's minimal directed spanning tree (MDST) construction for a random partially ordered set of points in the unit square,all edges must respect the ``coordinatewise'' partial order and there must be a directed path from each…

Probability · Mathematics 2008-08-30 Mathew D. Penrose , Andrew R. Wade

Vascular networks are used across the kingdoms of life to transport fluids, nutrients and cellular material. A popular unifying idea for understanding the diversity and constraints of these networks is that the conduits making up the…

Optimization and Control · Mathematics 2017-09-13 Shyr-Shea Chang , Marcus Roper

The multicast capacity of a directed network is closely related to the $s$-$t$ maximum flow, which is equal to the $s$-$t$ minimum cut capacity due to the max-flow min-cut theorem. If the topology of a network (or link capacities) is…

Information Theory · Computer Science 2012-02-07 Tadashi Wadayama , Yuki Fujii

We study spatial networks constructed by randomly placing nodes on a manifold and joining two nodes with an edge whenever their distance is less than a certain cutoff. We derive the general expression for the connectivity distribution of…

Disordered Systems and Neural Networks · Physics 2009-11-10 Carl Herrmann , Marc Barthelemy , Paolo Provero

Many physical systems -- such as optical waveguide lattices and dense neuronal or vascular networks -- can be modeled by metric graphs, where slender "wires" (edges) support wave or diffusion equations subject to Kirchhoff conditions at the…

Mathematical Physics · Physics 2025-08-26 Sidney Holden , Geoffrey Vasil

In this article, we explicitly derive the limiting degree distribution of the shortest path tree from a single source on various random network models with edge weights. We determine the asymptotics of the degree distribution for large…

Probability · Mathematics 2016-08-11 Shankar Bhamidi , Jesse Goodman , Remco van der Hofstad , Júlia Komjáthy

We consider navigation schemes on planar diluted lattices and semi lattices with one discrete and one continuous component. More precisely, nodes that survive inhomogeneous Bernoulli site percolation, or are placed as inhomogeneous Poisson…

Probability · Mathematics 2025-06-24 Partha Pratim Ghosh , Benedikt Jahnel , Yannic Steenbeck

Confining an answer to the question whether and how the coherent operation of network elements is determined by the the network structure is the topic of our work. We map the structure of signal flow in directed networks by analysing the…

Data Analysis, Statistics and Probability · Physics 2011-06-22 M. Bányai , L. Négyessy , F. Bazsó

In this paper, we study two examples of minimum weight random graphs with edge constraints. First we consider the complete graph on ${n}$ vertices equipped with uniformly heavy edge weights and use iteration methods to obtain deviation…

Probability · Mathematics 2023-01-13 Ghurumuruhan Ganesan

We consider the infinite directed graph with vertices the set of integers ...,-2,-1,0,1,2,... . Let v be a random variable taking either finite values or value "minus infinity". Consider random weights v(j,k), indexed by pairs (j,k) of…

Probability · Mathematics 2021-10-01 S. Foss , T. Konstantopoulos , A. Logachev , A. Mogulski

We consider the tributary structure of Howard's drainage model studied by Gangopadhyay et. al. Conditional on the event that the tributary survives up to time $n$, we show that, as a sequence of random metric spaces, scaled tributary…

Probability · Mathematics 2020-08-11 Kumarjit Saha

Motivated by low energy consumption in geographic routing in wireless networks, there has been recent interest in determining bounds on the length of edges in the Delaunay graph of randomly distributed points. Asymptotic results are known…

Computational Geometry · Computer Science 2011-08-23 Esther M. Arkin , Antonio Fernandez Anta , Joseph S. B. Mitchell , Miguel A. Mosteiro

Spatial networks are networks where nodes are located in a space equipped with a metric. Typically, the space is two-dimensional and until recently and traditionally, the metric that was usually considered was the Euclidean distance. In…

Combinatorics · Mathematics 2022-11-29 Ramon Ferrer-i-Cancho

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
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