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In this article, we obtain, for the total variance distance, the error bounds between Poisson and convolution of power series distributions via Stein's method. This provides a unified approach to many known discrete distributions. Several…

Probability · Mathematics 2020-06-26 A. N. Kumar , P. Vellaisamy , F. Viens

We use simple sub-Riemannian techniques to prove that an arbitrary geometric p-rough path in the sense of Lyons (98) is the limit in sup-norm of a sequence of canonically lifted smooth paths, which are uniformly bounded in p-variation,…

Functional Analysis · Mathematics 2007-05-23 Peter Friz , Nicolas Victoir

Random networks are increasingly used to analyse complex transportation networks, such as airline routes, roads and rail networks. So far, this research has been focused on describing the properties of the networks with the help of random…

Physics and Society · Physics 2017-09-19 Jürgen Hackl , Bryan T. Adey

We introduce and analyze a class of growing geometric random graphs that are invariant under rescaling of space and time. Directed connections between nodes are drawn according to influence zones that depend on node position in space and…

Physics and Society · Physics 2016-03-23 Zheng Xie , Tim Rogers

In recent work, Jon Kleinberg considered a small-world network model consisting of a d-dimensional lattice augmented with shortcuts. The probability of a shortcut being present between two points decays as a power of the distance between…

Probability · Mathematics 2007-05-23 M. Draief , A. Ganesh

The paper is a study of geodesic in two-dimensional pseudo-Riemannian metrics. Firstly, the local properties of geodesics in a neighborhood of generic parabolic points are investigated. The equation of the geodesic flow has singularities at…

Differential Geometry · Mathematics 2016-11-22 Alexey Remizov

Euclidean invariant Klein-Gordon, Dirac and massive Chern-Simons field theories are constructed in terms of a random walk with a spin factor on a three dimensional lattice. We exactly calculate the free energy and the correlation functions…

High Energy Physics - Theory · Physics 2009-10-28 Masako Asano , Chigak Itoi , Shin-Ichi Kojima

We introduce Physics Informed Symbolic Networks (PISN) which utilize physics-informed loss to obtain a symbolic solution for a system of Partial Differential Equations (PDE). Given a context-free grammar to describe the language of symbolic…

Machine Learning · Computer Science 2022-12-21 Ritam Majumdar , Vishal Jadhav , Anirudh Deodhar , Shirish Karande , Lovekesh Vig , Venkataramana Runkana

This work addresses the problem of simulating Gaussian random fields that are continuously indexed over a class of metric graphs, termed graphs with Euclidean edges, being more general and flexible than linear networks. We introduce three…

Statistics Theory · Mathematics 2024-04-29 Alfredo Alegría , Xavier Emery , Tobia Filosi , Emilio Porcu

Random fields are useful mathematical tools for representing natural phenomena with complex dependence structures in space and/or time. In particular, the Gaussian random field is commonly used due to its attractive properties and…

Is there a constant $r_0$ such that, in any invariant tree network linking rate-$1$ Poisson points in the plane, the mean within-network distance between points at Euclidean distance $r$ is infinite for $r > r_0$? We prove a slightly weaker…

Probability · Mathematics 2021-03-02 David J. Aldous

We study the performance of wireless links for a class of Poisson networks, in which packets arrive at the transmitters following Bernoulli processes. By combining stochastic geometry with queueing theory, two fundamental measures are…

Information Theory · Computer Science 2020-07-22 Howard H. Yang , Tony Q. S. Quek , H. Vincent Poor

Random projections are random linear maps, sampled from appropriate distributions, that approx- imately preserve certain geometrical invariants so that the approximation improves as the dimension of the space grows. The well-known…

Optimization and Control · Mathematics 2017-06-12 Ky Vu , Pierre-Louis Poirion , Leo Liberti

For a geodesic ball with non-negative Ricci curvature and almost maximal volume, without using compactness argument, we construct an $\epsilon$-splitting map on a concentric geodesic ball with uniformly small radius. There are two new…

Differential Geometry · Mathematics 2023-06-14 Guoyi Xu , Jie Zhou

Let a random geometric graph be defined in the supercritical regime for the existence of a unique infinite connected component in Euclidean space. Consider the first-passage percolation model with independent and identically distributed…

We study semi-infinite paths of the radial spanning tree (RST) of a Poisson point process in the plane. We first show that the expectation of the number of intersection points between semi-infinite paths and the sphere with radius $r$ grows…

Probability · Mathematics 2012-11-27 François Baccelli , David Coupier , Viet Chi Tran

In the Hammersley-Aldous-Diaconis process infinitely many particles sit in R and at most one particle is allowed at each position. A particle at x$ whose nearest neighbor to the right is at y, jumps at rate y-x to a position uniformly…

Probability · Mathematics 2007-07-31 Pablo A. Ferrari , James B. Martin

We formalize the notion of limit of an inverse system of metric spaces with $1$-Lipschitz projections having unbounded fibers. The purpose is to use sub-Riemannian groups for metrizing the space of signatures of rectifiable paths in…

Metric Geometry · Mathematics 2019-10-11 Enrico Le Donne , Roger Züst

Slinky, a helical elastic rod, is a seemingly simple structure with unusual mechanical behavior; for example, it can walk down a flight of stairs under its own weight. Taking Slinky as a test-case, we propose a physics-informed deep…

Computational Physics · Physics 2023-01-30 Qiaofeng Li , Tianyi Wang , Vwani Roychowdhury , M. Khalid Jawed

Complex systems, ranging from soft materials to wireless communication, are often organised as random geometric networks in which nodes and edges evenly fill up the volume of some space. Studying such networks is difficult because they…

Probability · Mathematics 2022-07-19 Ivan Kryven , Rik Versendaal