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The Gaussian beam superposition method is an asymptotic method for computing high frequency wave fields in smoothly varying inhomogeneous media. In this paper we study the accuracy of the Gaussian beam superposition method and derive error…

Numerical Analysis · Mathematics 2010-02-04 Mohammad Motamed , Olof Runborg

We introduce a fast and easy-to-implement simulation algorithm for a multivariate normal distribution truncated on the intersection of a set of hyperplanes, and further generalize it to efficiently simulate random variables from a…

Computation · Statistics 2017-02-21 Yulai Cong , Bo Chen , Mingyuan Zhou

In this paper, we study high-dimensional random projections of $\ell_p^n$-balls. More precisely, for any $n\in\mathbb N$ let $E_n$ be a random subspace of dimension $k_n\in\{1,\ldots,n\}$ and $X_n$ be a random point in the unit ball of…

Probability · Mathematics 2018-08-29 David Alonso-Gutierrez , Joscha Prochno , Christoph Thaele

We consider the problem of recovering an unknown matching between a set of $n$ randomly placed points in $\mathbb{R}^d$ and random perturbations of these points. This can be seen as a model for particle tracking and more generally, entity…

Statistics Theory · Mathematics 2024-03-27 Lucas da Rocha Schwengber , Roberto Imbuzeiro Oliveira

In this paper, we consider the rectilinear one-center problem on uncertain points in the plane. In this problem, we are given a set $P$ of $n$ (weighted) uncertain points in the plane and each uncertain point has $m$ possible locations each…

Computational Geometry · Computer Science 2015-09-18 Haitao Wang , Jingru Zhang

We consider the problem of finding an optimal transport plan between an absolutely continuous measure $\mu$ on $\mathcal{X} \subset \mathbb{R}^d$ and a finitely supported measure $\nu$ on $\mathbb{R}^d$ when the transport cost is the…

Numerical Analysis · Mathematics 2018-10-08 Valentin Hartmann , Dominic Schuhmacher

While equivariant methods have seen many fruitful applications in geometric combinatorics, their inability to answer the now settled Topological Tverberg Conjecture has made apparent the need to move beyond the use of Borsuk--Ulam type…

Metric Geometry · Mathematics 2018-08-23 Steven Simon

Given a point set $P$ in the Euclidean space, a geometric $t$-spanner $G$ is a graph on $P$ such that for every pair of points, the shortest path in $G$ between those points is at most a factor $t$ longer than the Euclidean distance between…

Computational Geometry · Computer Science 2024-12-10 Kevin Buchin , Carolin Rehs , Torben Scheele

We solve the Random Euclidean Matching problem with exponent 2 for the Gaussian distribution defined on the plane. Previous works by Ledoux and Talagrand determined the leading behavior of the average cost up to a multiplicative constant.…

Probability · Mathematics 2024-01-22 Emanuele Caglioti , Francesca Pieroni

A straight-line drawing $\delta$ of a planar graph $G$ need not be plane, but can be made so by \emph{untangling} it, that is, by moving some of the vertices of $G$. Let shift$(G,\delta)$ denote the minimum number of vertices that need to…

Computational Geometry · Computer Science 2009-01-27 Xavier Goaoc , Jan Kratochvil , Yoshio Okamoto , Chan-Su Shin , Andreas Spillner , Alexander Wolff

In this paper, we prove that the Euclidean distance between two independent random vectors uniformly distributed on $l_p^n$-balls $(1 \leq p \leq \infty)$ or on its boundary satisfies a central limit theorem as $n$ tends to $\infty$. Also,…

Probability · Mathematics 2026-01-01 David Alonso-Gutiérrez , Javier Martín Goñi , Joscha Prochno

We pursue two goals in this article. As our first goal, we construct a family $\mathcal{M}_G$ of Gibbs like measures on the set of piecewise linear convex functions $g:\mathbb{R}^2\to\mathbb{R}$. It turns out that there is a one-to-one…

Probability · Mathematics 2022-05-18 Mehdi Ouaki , Fraydoun Rezakhanlou

Fitting an unknown number of hyperplanes to data is a fundamental yet challenging problem in machine learning, characterized by its non-convexity, non-differentiability, and unknown model order. Existing approaches often struggle with local…

Machine Learning · Computer Science 2026-05-28 Zhiqin Cheng , Yu Zhan , Mingjin Zhang , Lingbo Liu , Liang Lin

The question of optimally approximating an arbitrary probability measure in the Wasserstein distance by a discrete one with uniform weights is considered. Estimates are obtained for the optimal approximation distance, with an explicit rate…

Probability · Mathematics 2026-04-14 Benjamin Seeger

Uniformity testing is one of the most well-studied problems in property testing, with many known test statistics, including ones based on counting collisions, singletons, and the empirical TV distance. It is known that the optimal sample…

Machine Learning · Statistics 2022-06-23 Shivam Gupta , Eric Price

With any max-stable random process $\eta$ on $\mathcal{X}=\mathbb{Z}^d$ or $\mathbb{R}^d$, we associate a random tessellation of the parameter space $\mathcal{X}$. The construction relies on the Poisson point process representation of the…

Probability · Mathematics 2016-01-07 Clément Dombry , Z. Kabluchko

We develop estimators of agreement and disagreement between correlated cosmological data sets. These account for data correlations when computing the significance of both tensions and excess confirmation while remaining statistically…

Cosmology and Nongalactic Astrophysics · Physics 2020-05-27 Marco Raveri , Georgios Zacharegkas , Wayne Hu

We consider the thick points of random walk, i.e. points where the local time is a fraction of the maximum. In two dimensions, we answer a question of Dembo, Peres, Rosen and Zeitouni and compute the number of thick points of planar random…

Probability · Mathematics 2020-03-02 Antoine Jego

An equidistant set in the Euclidean space consists of points having equal distances to both members of a given pair of sets, called focal sets. Since there is no effective formula to compute the distance of a point and a set, it is hard to…

Metric Geometry · Mathematics 2026-05-22 Á. Nagy , M. Oláh , M. Stoika , Cs. Vincze

Finding an exact maximum distance of two points in the given set is a fundamental computational problem which is solved in many applications. This paper presents a fast, simple to implement and robust algorithm for finding this maximum…

Data Structures and Algorithms · Computer Science 2017-08-10 Vaclav Skala , Zuzana Majdisova