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We consider Gaussian fields of real symmetric, complex Hermitian or quaternionic Hermitian matrices over an electrical network, and describe how the isomorphisms between these fields and random walks give rise to topological expansions…

Probability · Mathematics 2022-08-31 Titus Lupu

The study of random graphs has become very popular for real-life network modeling such as social networks or financial networks. Inhomogeneous long-range percolation (or scale-free percolation) on the lattice $\mathbb Z^d$, $d\ge1$, is a…

Probability · Mathematics 2014-09-29 Philippe Deprez , Rajat Subhra Hazra , Mario V. Wüthrich

Random walks are studied on disordered cellular networks in 2-and 3-dimensional spaces with arbitrary curvature. The coefficients of the evolution equation are calculated in term of the structural properties of the cellular system. The…

Disordered Systems and Neural Networks · Physics 2009-10-28 Tomaso Aste

We investigate a network model based on an infinite regular square lattice embedded in the Euclidean plane where the node connection probability is given by the geometrical distance of nodes. We show that the degree distribution in the…

Physics and Society · Physics 2008-06-23 Matus Medo , Jan Smrek

Random geometric graphs are random graph models defined on metric spaces. Such a model is defined by first sampling points from a metric space and then connecting each pair of sampled points with probability that depends on their distance,…

Machine Learning · Computer Science 2026-04-10 Han Huang , Pakawut Jiradilok , Elchanan Mossel

The curse of dimensionality is a common phenomenon which affects analysis of datasets characterized by large numbers of variables associated with each point. Problematic scenarios of this type frequently arise in classification algorithms…

Probability · Mathematics 2015-08-11 Benjamin Thirey , Randal Hickman

The hyperbolic random graph model (HRG) has proven useful in the analysis of scale-free networks, which are ubiquitous in many fields, from social network analysis to biology. However, working with this model is algorithmically and…

Computational Geometry · Computer Science 2019-01-08 Eryk Kopczyński , Dorota Celińska-Kopczyńska

Phylogenetic inference-the derivation of a hypothesis for the common evolutionary history of a group of species- is an active area of research at the intersection of biology, computer science, mathematics, and statistics. One assumes the…

Populations and Evolution · Quantitative Biology 2016-06-21 Ruth Davidson , Joseph Rusinko , Zoe Vernon , Jing Xi

In this paper we obtain the density function and the distribution function of the distance between two uniformly and independently distributed random points in any right-angled triangle. The density function is derived from the chord length…

Probability · Mathematics 2012-09-18 Uwe Bäsel

We study random graph models for directed acyclic graphs, an important class of networks that includes citation networks, food webs, and feed-forward neural networks among others. We propose two specific models, roughly analogous to the…

Physics and Society · Physics 2009-10-16 Brian Karrer , M. E. J. Newman

We study the behavior of the random walk in a continuum independent long-range percolation model, in which two given vertices $x$ and $y$ are connected with probability that asymptotically behaves like $|x-y|^{-\alpha}$ with $\alpha>d$,…

Probability · Mathematics 2022-09-30 Ercan Sönmez , Arnaud Rousselle

This work addresses a modification of the random geometric graph (RGG) model by considering a set of points uniformly and independently distributed on the surface of a $(d-1)$-sphere with radius $r$ in a $d-$dimensional Euclidean space,…

Physics and Society · Physics 2018-10-03 Alfonso Allen-Perkins

The unit ball random geometric graph $G=G^d_p(\lambda,n)$ has as its vertices $n$ points distributed independently and uniformly in the $d$-dimensional unit ball, with two vertices adjacent if and only if their $l_p$-distance is at most…

Combinatorics · Mathematics 2011-10-05 Robert B. Ellis , Jeremy L. Martin , Catherine Yan

In this paper we consider a random partition of the plane into cells, the partition being based on the nodes and links of a {\it random planar geometric graph}. The resulting structure generalises the \emph{random \tes}\ hitherto studied in…

Probability · Mathematics 2016-06-07 Richard Cowan , Albert K. L. Tsang

Encoding the distance between locations in space is essential for accurate navigation. Grid cells, a functional class of neurons in medial entorhinal cortex, are believed to support this computation. However, existing theories of how…

Neurons and Cognition · Quantitative Biology 2025-11-12 Pritipriya Dasbehera , Akshunna S. Dogra , William T. Redman

We propose a method of characterizing radial networks based on a partition function associated with the structural triangulation of the network. The internal energy, Helmholtz free energy, and entropy derived from the partition function are…

Statistical Mechanics · Physics 2010-05-19 Rak-Kyeong Seong , Dimitri D. Vvedensky

In this paper, we consider a one-dimensional random geometric graph process with the inter-nodal gaps evolving according to an exponential AR(1) process, which may serve as a mobile wireless network model. The transition probability matrix…

Information Theory · Computer Science 2009-12-09 Yilun Shang

In applications such as wireless communication, it is important to study the statistical properties of $L_{2}$, the minimal arc distance between a random point (e.g., a cellphone user) uniformly distributed on a sphere to a set of…

Computation · Statistics 2021-02-03 Hongjun Li , Jiatong Sui , Shengpeng Mu , Xing Qiu

Given a Poisson process on a bounded interval, its random geometric graph is the graph whose vertices are the points of the Poisson process and edges exist between two points if and only if their distance is less than a fixed given…

Probability · Mathematics 2010-08-31 Laurent Decreusefond , Eduardo Ferraz

The hyperbolic random graph model (HRG) has proven useful in the analysis of scale-free networks, which are ubiquitous in many fields, from social network analysis to biology. However, working with this model is algorithmically and…

Social and Information Networks · Computer Science 2022-05-03 Dorota Celińska-Kopczyńska , Eryk Kopczyński