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We consider random walk on a mildly random environment on finite transitive d- regular graphs of increasing girth. After scaling and centering, the analytic spectrum of the transition matrix converges in distribution to a Gaussian noise. An…

Probability · Mathematics 2011-11-10 Dimitrios Cheliotis , Balint Virag

Latent space geometry provides a rigorous and empirically valuable framework for interacting with the latent variables of deep generative models. This approach reinterprets Euclidean latent spaces as Riemannian through a pull-back metric,…

Machine Learning · Statistics 2024-08-15 Stas Syrota , Pablo Moreno-Muñoz , Søren Hauberg

We study the number of isolated nodes in a soft random geometric graph whose vertices constitute a Poisson process on the torus of length L (the line segment [0,L] with periodic boundary conditions), and where an edge is present between two…

Probability · Mathematics 2022-10-21 Michael Wilsher , Carl Dettmann , Ayalvadi Ganesh

Network complexity has been studied for over half a century and has found a wide range of applications. Many methods have been developed to characterize and estimate the complexity of networks. However, there has been little research with…

Machine Learning · Statistics 2021-01-13 Yann Issartel

We give a quantum algorithm for a novel type of black-box problem: identifying a hidden $d$-regular base graph $G$ on $n$ vertices from oracle access to an obfuscated version of it, rather than traversing it. From $G$ we build the spired…

Quantum Physics · Physics 2026-05-13 Pawel Wocjan

Over the past decade, many works on the modeling of wireless networks using stochastic geometry have been proposed. Results about probability of coverage, throughput or mean interference, have been provided for a wide variety of networks…

Networking and Internet Architecture · Computer Science 2016-02-08 Alexandre Mouradian

We study the geometric phase (GP) of a two-level atom coupled to an environment composed of free space and a dielectric nanosphere in thermal and out of thermal equilibrium. We analytically and numerically analyze the optical properties and…

Quantum Physics · Physics 2024-04-24 Ehsan Amooghorban , Sareh Shahidani , Somaye Mohamadi Abdhvand

We present a new method for learning Soft Random Geometric Graphs (SRGGs), drawn in probabilistic metric spaces, with the connection function of the graph defined as the marginal posterior probability of an edge random variable, given the…

Methodology · Statistics 2020-02-05 Kangrui Wang , Dalia Chakrabarty

A geometric graph is a graph embedded in the plane with vertices at points and edges drawn as curves (which are usually straight line segments) between those points. The average transversal complexity of a geometric graph is the number of…

Computational Geometry · Computer Science 2009-09-17 David Eppstein , Michael T. Goodrich , Lowell Trott

A random geometric digraph $G_n$ is constructed by taking $\{X_1,X_2,... X_n\}$ in $\mathbb{R}^2$ independently at random with a common bounded density function. Each vertex $X_i$ is assigned at random a sector $S_i$ of central angle…

Combinatorics · Mathematics 2019-09-18 Yilun Shang

This paper studies the problem of detecting the presence of a small dense community planted in a large Erd\H{o}s-R\'enyi random graph $\mathcal{G}(N,q)$, where the edge probability within the community exceeds $q$ by a constant factor.…

Statistics Theory · Mathematics 2015-03-13 Bruce Hajek , Yihong Wu , Jiaming Xu

A soft random graph $G(n,r,p)$ can be obtained from the random geometric graph $G(n,r)$ by keeping every edge in $G(n,r)$ with probability $p$. This random graph is a particular case of the soft random graph model introduced by Penrose, in…

Algebraic Topology · Mathematics 2025-07-15 Julián David Candela

We propose the following model of a random graph on n vertices. Let F be a distribution in R_+^{n(n-1)/2} with a coordinate for every pair i$ with 1 \le i,j \le n. Then G_{F,p} is the distribution on graphs with n vertices obtained by…

Combinatorics · Mathematics 2011-08-09 Alan Frieze , Santosh Vempala , Juan Vera

Consider a stationary Poisson point process in $\mathbb{R}^d$ and connect any two points whenever their distance is less than or equal to a prescribed distance parameter. This construction gives rise to the well known random geometric…

Probability · Mathematics 2017-01-04 Jens Grygierek , Christoph Thaele

The query complexity of graph properties is well-studied when queries are on edges. We investigate the same when queries are on nodes. In this setting a graph $G = (V, E)$ on $n$ vertices and a property $\mathcal{P}$ are given. A black-box…

Computational Complexity · Computer Science 2015-10-29 Nikhil Balaji , Samir Datta , Raghav Kulkarni , Supartha Podder

Using a generalized random recurrent neural network model, and by extending our recently developed mean-field approach [J. Aljadeff, M. Stern, T. Sharpee, Phys. Rev. Lett. 114, 088101 (2015)], we study the relationship between the network…

Disordered Systems and Neural Networks · Physics 2016-02-09 Johnatan Aljadeff , David Renfrew , Marina Vegué , Tatyana O. Sharpee

Given independent random points $X_1,...,X_n\in\eR^d$ with common probability distribution $\nu$, and a positive distance $r=r(n)>0$, we construct a random geometric graph $G_n$ with vertex set $\{1,...,n\}$ where distinct $i$ and $j$ are…

Combinatorics · Mathematics 2012-01-04 Colin McDiarmid , Tobias Müller

We consider random graphs on the set of $N^2$ vertices placed on the discrete $2$-dimensional torus. The edges between pairs of vertices are independent, and their probabilities decay with the distance $\rho$ between these vertices as…

Probability · Mathematics 2023-08-16 Vasilii Goriachkin , Tatyana Turova

We find conditions for the connectivity of inhomogeneous random graphs with intermediate density. Our results generalize the classical result for G(n, p), when p = c log n/n. We draw n independent points X_i from a general distribution on a…

Probability · Mathematics 2012-10-25 Luc Devroye , Nicolas Fraiman

Graphs and network data are ubiquitous across a wide spectrum of scientific and application domains. Often in practice, an input graph can be considered as an observed snapshot of a (potentially continuous) hidden domain or process.…

Computational Geometry · Computer Science 2018-10-24 Srinivasan Parthasarathy , David Sivakoff , Minghao Tian , Yusu Wang