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High energy experimental data can be viewed as a sampling of the relevant phase space. We point out that one can apply Voronoi tessellations in order to understand the underlying probability distributions in this phase space. Interesting…

High Energy Physics - Phenomenology · Physics 2015-11-10 Dipsikha Debnath , James S. Gainer , Doojin Kim , Konstantin T. Matchev

This note describes a simple method to draw random points such that the cells of the corresponding Voronoi tesselation (approximately) satisfy a desired size distribution, for instance, follow a power law. The method is illustrated and…

Numerical Analysis · Mathematics 2025-08-12 Georg Stadler , Gonzalo G. De Diego

In this study the Voronoi interpolation is used to interpolate a set of points drawn from a topological space with higher homology groups on its filtration. The technique is based on Voronoi tessellation, which induces a natural dual map to…

Computational Geometry · Computer Science 2026-03-24 Luciano Melodia , Richard Lenz

Voids are a prominent feature of the galaxy distribution but their quantitative study is hindered by the lack of a precise definition of what constitutes a void. Here we propose a definition of voids in point distributions that uses methods…

Astrophysics · Physics 2007-05-23 Jose Gaite

Voronoi tessellations are used to partition the Euclidean space into polyhedral regions, which are called Voronoi cells. Labeling the Voronoi cells with the class information, we can map any classification problem into a Voronoi…

Machine Learning · Computer Science 2021-06-17 Rahman Salim Zengin , Volkan Sezer

We introduce two new methods to obtain reliable velocity field statistics from N-body simulations, or indeed from any general density and velocity fluctuation field sampled by discrete points. These methods, the {\it Voronoi tessellation…

Astrophysics · Physics 2017-03-08 Francis Bernardeau , Rien van de Weygaert

This article represents the computational model for spacial addresation of the sensors in the dynamically changing real-time internet of things system. The model bases on the Voronoi diagrams as a basic data structure. Problem - the correct…

Data Structures and Algorithms · Computer Science 2022-01-11 Almagul Kondybayeva , Giovanna Di Marzo

We review the concepts of the Voronoi binning technique (Cappellari & Copin 2003), which optimally solves the problem of preserving the maximum spatial resolution of general two-dimensional data, given a constraint on the minimum…

Instrumentation and Methods for Astrophysics · Physics 2009-12-08 Michele Cappellari

Motivated by the rapidly increasing relevance of virtual material design in the domain of materials science, it has become essential to assess whether topological properties of stochastic models for a spatial tessellation are in accordance…

Statistics Theory · Mathematics 2022-09-28 Christian Hirsch , Johannes Krebs , Claudia Redenbach

We present DisPerSE, a novel approach to the coherent multi-scale identification of all types of astrophysical structures, and in particular the filaments, in the large scale distribution of matter in the Universe. This method and…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-20 Thierry Sousbie

Voronoi intensity estimators, which are non-parametric estimators for intensity functions of point processes, are both parameter-free and adaptive; the intensity estimate at a given location is given by the reciprocal size of the…

The Voronoi Entropy (VE) and the continuous measure of symmetry (CSM) characterize the orderliness of a set of points on a 2D plane. The Voronoi entropy is the Shannon entropy of the Voronoi tessellation of the plane into polygons,…

Statistical Mechanics · Physics 2024-10-30 Edward Bormashenko , Shraga Shoval , Mark Frenkel , Michael Nosonovsky

Color image segmentation is a crucial step in many computer vision and pattern recognition applications. This article introduces an adaptive and unsupervised clustering approach based on Voronoi regions, which can be applied to solve the…

Computer Vision and Pattern Recognition · Computer Science 2016-04-05 R. Hettiarachchi , J. F. Peters

With our previous study, the Super-k algorithm, we have introduced a novel way of piecewise-linear classification. While working on the Super-k algorithm, we have found that there is a similar, and simpler way to explain for obtaining a…

Machine Learning · Computer Science 2021-02-03 Rahman Salim Zengin , Volkan Sezer

Random tessellations are a prominent class of models in stochastic geometry. In this chapter, we give an overview of mechanisms that have been used to formulate random tessellation models. First, the notion of a random tessellation and…

Probability · Mathematics 2025-01-10 Claudia Redenbach , Christian Jung

3D Voronoi's tessellation method was first applied to identify groups of galaxies in the structure of a supercluster. The sample under consideration consists of more than 7000 galaxies of the Local Supercluster (LS) with radial velocities…

Astrophysics · Physics 2008-11-26 O. V. Melnyk , A. A. Elyiv , I. B. Vavilova

I present a regression algorithm that provides a continuous, piecewise-smooth function approximating scattered data. It is based on composing and blending linear functions over Voronoi cells, and it scales to high dimensions. The algorithm…

Computational Geometry · Computer Science 2025-10-07 Shankar Prasad Sastry

Polycrystal microstructures, with their distinct physical, chemical, structural and topological entities, play an important role in determining the effective properties of materials. Particularly for computational studies, the well-known…

Materials Science · Physics 2021-07-07 Prince Henry Serrao , Stefan Sandfeld , Aruna Prakash

We introduce a new approach for identifying and characterizing voids within two-dimensional (2D) point distributions through the integration of Delaunay triangulation and Voronoi diagrams, combined with a Minimal Distance Scoring algorithm.…

Computational Geometry · Computer Science 2024-01-01 Netzer Moriya

The size of large, geo-located datasets has reached scales where visualization of all data points is inefficient. Random sampling is a method to reduce the size of a dataset, yet it can introduce unwanted errors. We describe a method for…

Human-Computer Interaction · Computer Science 2017-09-14 Yan Zheng , Yi Ou , Alexander Lex , Jeff M. Phillips