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Related papers: Distance Distributions in Regular Polygons

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Consider an i.i.d. sample from an unknown density function supported on an unknown manifold embedded in a high dimensional Euclidean space. We tackle the problem of learning a distance between points, able to capture both the geometry of…

Probability · Mathematics 2019-12-30 Pablo Groisman , Matthieu Jonckheere , Facundo Sapienza

We consider two independent symmetric Markov random flights $\bold Z_1(t)$ and $\bold Z_2(t)$ performed by the particles that simultaneously start from the origin of the Euclidean plane $\Bbb R^2$ in random directions distributed uniformly…

Probability · Mathematics 2014-02-18 Alexander D. Kolesink

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

We study the asymptotic behavior of the diameter or maximum interpoint distance of a cloud of i.i.d. $d$-dimensional random vectors when the number of points in the cloud tends to infinity. This is a non standard extreme value problem since…

Probability · Mathematics 2017-11-30 Yann Demichel , Ana Karina Fermin , Philippe Soulier

Let $X_1,X_2, \ldots $ be independent random uniform points in a bounded domain $A \subset \mathbb{R}^d$ with smooth boundary. Define the coverage threshold $R_n$ to be the smallest $r$ such that $A$ is covered by the balls of radius $r$…

Probability · Mathematics 2022-01-12 Mathew D. Penrose

The probability distribution function (PDF) of the mass surface density of molecular clouds provides essential information about the structure of molecular cloud gas and condensed structures out of which stars may form. In general, the PDF…

Astrophysics of Galaxies · Physics 2015-06-22 Jörg Fischera

The distribution function of the end-to-end distance of a semiflexible polymer, G(R;L) (where R denotes the end-to-end distance and L the contour length), is calculated using a meanfield-like approach. The theory yields an extremely simple…

Statistical Mechanics · Physics 2016-08-31 J. K. Bhattacharjee , D. Thirumalai , J. D. Bryngelson

In this note, we consider a complete intersection $X=\{x\in \mathbb{R}^n : f_1(x)= \ldots = f_m(x)=0\}, n>m$ and study its Euclidean distance degree in terms of the mixed volume of the Newton polytopes. We show that if the Newton polytopes…

Algebraic Geometry · Mathematics 2024-05-03 Nguyen Tat Thang , Pham Thu Thuy

We calculate the distribution function of the end--to--end distance of a semiflexible polymer with large bending rigidity. This quantity is directly observable in experiments on single semiflexible polymers (e.g., DNA, actin) and relevant…

Condensed Matter · Physics 2009-10-28 Jan Wilhelm , Erwin Frey

Let $p$ and $q$ be two imprecise points, given as probability density functions on $\mathbb R^2$, and let $\cal R$ be a set of $n$ line segments (obstacles) in $\mathbb R^2$. We study the problem of approximating the probability that $p$…

Computational Geometry · Computer Science 2019-03-12 Kevin Buchin , Irina Kostitsyna , Maarten Löffler , Rodrigo I. Silveira

Motivated by the problem of compressing point sets into as few bits as possible while maintaining information about approximate distances between points, we construct random nonlinear maps $\varphi_\ell$ that compress point sets in the…

Computational Geometry · Computer Science 2024-03-05 Brett Leroux , Luis Rademacher

We consider the continuous Fermat-Weber problem, where the customers are continuously (uniformly) distributed along the boundary of a convex polygon. We derive the closed-form expression for finding the average distance from a given point…

Computational Geometry · Computer Science 2014-03-18 Thomas T. C. K. Zhang , John Gunnar Carlsson

The average distance from a node to all other nodes in a graph, or from a query point in a metric space to a set of points, is a fundamental quantity in data analysis. The inverse of the average distance, known as the (classic) closeness…

Social and Information Networks · Computer Science 2015-06-29 Shiri Chechik , Edith Cohen , Haim Kaplan

In this paper a relative number density parameter, called the neighborhood function, is introduced so that the crowded nature of the neighborhood of individual sources can be described. With this parameter one can determine the probability…

Astrophysics · Physics 2009-11-13 Yi-Ping Qin , Lian-Zhong Lv , Fu-Wen Zhang , Bin-Bin Zhang , Jin Zhang

Consider an unlimited homogeneous medium disturbed by points generated via Poisson process. The neighborhood of a point plays an important role in spatial statistics problems. Here, we obtain analytically the distance statistics to $k$th…

Statistical Mechanics · Physics 2015-08-11 Cristiano Roberto Fabri Granzotti , Alexandre Souto Martinez

Euclidean distance geometry is the study of Euclidean geometry based on the concept of distance. This is useful in several applications where the input data consists of an incomplete set of distances, and the output is a set of points in…

Quantitative Methods · Quantitative Biology 2012-05-03 Leo Liberti , Carlile Lavor , Nelson Maculan , Antonio Mucherino

We study the asymptotic behavior of the maximum interpoint distance of random points in a $d$-dimensional set with a unique diameter and a smooth boundary at the poles. Instead of investigating only a fixed number of $n$ points as $n$ tends…

Probability · Mathematics 2017-09-13 Michael Schrempp

We consider the distribution of free path lengths, or the distance between consecutive bounces of random particles, in an n-dimensional rectangular box. If each particle travels a distance R, then, as R tends to infinity the free path…

Dynamical Systems · Mathematics 2018-11-14 Samuel Holmin , Pär Kurlberg , Daniel Månsson

The wrapped normal distribution arises when a the density of a one-dimensional normal distribution is wrapped around the circle infinitely many times. At first look, evaluation of its probability density function appears tedious as an…

Computation · Statistics 2018-01-01 Gerhard Kurz , Igor Gilitschenski , Uwe D. Hanebeck

We provide upper bounds of the expected Wasserstein distance between a probability measure and its empirical version, generalizing recent results for finite dimensional Euclidean spaces and bounded functional spaces. Such a generalization…

Statistics Theory · Mathematics 2020-01-29 Jing Lei