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Among several things, we find the side density for random triangles circumscribing the unit circle and calculate that its median is 5.5482.... An analogous exact computation for perimeter density remains open.

Probability · Mathematics 2015-03-17 Steven R. Finch

We consider $N$ circles of equal radii, $r$, having their centers randomly placed within a square domain $\mathcal{D}$ of size $L \times L$ with periodic boundary conditions ($\mathcal{D} \in \mathbb{R}^2$). When two or more circles…

Statistical Mechanics · Physics 2020-03-23 Renat K. Akhunzhanov , Yuri Yu. Tarasevich , Irina V. Vodolazskaya

The construction of $r$-nets offers a powerful tool in computational and metric geometry. We focus on high-dimensional spaces and present a new randomized algorithm which efficiently computes approximate $r$-nets with respect to Euclidean…

Computational Geometry · Computer Science 2017-05-09 Georgia Avarikioti , Ioannis Z. Emiris , Loukas Kavouras , Ioannis Psarros

The analysis of strings of $n$ random variables with geometric distribution has recently attracted renewed interest: Archibald et al. consider the number of distinct adjacent pairs in geometrically distributed words. They obtain the…

Probability · Mathematics 2024-02-14 Guy Louchard , Werner Schachinger , Mark Daniel Ward

Divergence functions are measures of distance or dissimilarity between probability distributions that serve various purposes in statistics and applications. We propose decompositions of Wasserstein and Cram\'er distances$-$which compare two…

Methodology · Statistics 2025-08-08 Johannes Resin , Daniel Wolffram , Johannes Bracher , Timo Dimitriadis

In this paper we introduce the intuitive notion of trivergence of probability distributions (TPD). This notion allow us to calculate the similarity among triplets of objects. For this computation, we can use the well known measures of…

Information Theory · Computer Science 2015-06-23 Juan-Manuel Torres-Moreno

Randomness is viewed through an analogy between a physical quantity, density of gas, and a mathematical construct -- probability density. Boltzmann's deduction of equilibrium distribution of ideal gas placed in an external potential field…

Probability · Mathematics 2012-08-27 M. Grendar, , M. Grendar

This paper studies the strong quasiconvexity of norm and distance functions in finite-dimensional normed spaces. Although the Euclidean norm is known to be strongly quasiconvex on bounded convex sets, a complete characterization of this…

Optimization and Control · Mathematics 2026-05-26 V. S. T. Long , N. M. Nam

Random walk has wide applications in many fields, such as machine learning, biology, physics, and chemistry. Random walk can be discrete or continuous in time and space. Asymmetric random walk could be described by drift-diffusion equation.…

Statistical Mechanics · Physics 2024-03-01 Guoxing Lin , Shaokun Zheng

The chord length probability density of the regular octahedron is explicitly evaluated throughout its full range of distances by separating it into three contributions respectively due to the pairs of facets opposite to each other or…

Mathematical Physics · Physics 2014-02-11 Salvino Ciccariello

We study a Fermi-Pasta-Ulam-like chain with realistic potentials, which models a unidimensional solid in contact with heat baths at some temperature. We formulate an explicit analytical expression for the probability density of bonding…

Statistical Mechanics · Physics 2015-06-16 Roman Belousov , Paolo De Gregorio , Lamberto Rondoni , Livia Conti

We present several natural notions of distance between spectral density functions of (discrete-time) random processes. They are motivated by certain filtering problems. First we quantify the degradation of performance of a predictor which…

Optimization and Control · Mathematics 2008-07-19 Tryphon T. Georgiou

Exact formulas are derived for the probability density functions of the sum and difference of two independent non-central gamma distributed random variables, with both series and integral representations of the density presented. These…

Probability · Mathematics 2026-05-18 Robert E. Gaunt , Heather L. Sutcliffe

Proximity catch digraphs (PCDs) are based on proximity maps which yield proximity regions and are special types of proximity graphs. PCDs are based on the relative allocation of points from two or more classes in a region of interest and…

Probability · Mathematics 2009-03-31 Elvan Ceyhan

Consider that the coordinates of $N$ points are randomly generated along the edges of a $d$-dimensional hypercube (random point problem). The probability that an arbitrary point is the $m$th nearest neighbor to its own $n$th nearest…

Disordered Systems and Neural Networks · Physics 2007-05-23 Cesar Augusto Sangaletti Tercariol , Felipe de Mouta Kiipper , Alexandre Souto Martinez

We study several models of random geometric subdivisions arising from the model of Diaconis and Miclo (2011). In particular, we show that the limiting shape of an indefinite subdivision of a quadrilateral is a.s.\ a parallelogram. We also…

Probability · Mathematics 2011-12-06 Stanislav Volkov

We introduce a new class of countably infinite random geometric graphs, whose vertices are points in a metric space, and vertices are adjacent independently with probability p if the metric distance between the vertices is below a given…

Combinatorics · Mathematics 2012-08-28 Anthony Bonato , Jeannette Janssen

The inverse structure functions of exit distances have been introduced as a novel diagnostic of turbulence which emphasizes the more laminar regions [1-4]. Using Taylor's frozen field hypothesis, we investigate the statistical properties of…

Fluid Dynamics · Physics 2007-05-23 W. -X. Zhou , D. Sornette , W. -K. Yuan

We obtain asymptotic approximations for the probability density function of the product of two correlated normal random variables with non-zero means and arbitrary variances. As a consequence, we deduce asymptotic approximations for the…

Probability · Mathematics 2024-10-22 Robert E. Gaunt , Zixin Ye

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
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