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We consider the Voronoi tessellation associated to a stationary simple point process on $\mathbb{R}^d$ with finite and positive intensity. We introduce the Delaunay triangulation as its dual graph, i.e.~the graph with vertex set given by…

Probability · Mathematics 2026-03-25 A. Faggionato , C. Tagliaferri

Voronoi tessellations have been used to model the geometric arrangement of cells in morphogenetic or cancerous tissues, however so far only with flat hypersurfaces as cell-cell contact borders. In order to reproduce the experimentally…

Biological Physics · Physics 2009-12-02 Martin Bock , Amit Kumar Tyagi , Jan-Ulrich Kreft , Wolfgang Alt

Mapping between discrete and continuous distributions is a difficult task and many have had to resort to heuristical approaches. We propose a tessellation-based approach that directly learns quantization boundaries in a continuous space,…

Machine Learning · Computer Science 2022-12-13 Ricky T. Q. Chen , Brandon Amos , Maximilian Nickel

The computation of Voronoi Diagrams, or their dual Delauney triangulations is difficult in high dimensions. In a recent publication Polianskii and Pokorny propose an iterative randomized algorithm facilitating the approximation of Voronoi…

Computational Geometry · Computer Science 2024-05-17 Alexander Sikorski , Martin Heida

Voronoi tessellation, also known as Voronoi diagram, is an important computational geometry technique that has applications in various scientific disciplines. It involves dividing a given space into regions based on the proximity to a set…

Computational Geometry · Computer Science 2024-12-17 Sergei Shumilin , Alexander Ryabov , Serguei Barannikov , Evgeny Burnaev , Vladimir Vanovskii

Given a countable set of points in a continuous space, Voronoi tessellation is an intuitive way of partitioning the space according to the distance to the individual points. As a powerful approach to obtain structural information, it has a…

Soft Condensed Matter · Physics 2020-02-17 Simeon Völkel , Kai Huang

Many methods for modelling spatial processes assume global smoothness properties; such assumptions are often violated in practice. We introduce a method for modelling spatial processes that display heterogeneity or contain discontinuities.…

The application of Voronoi and Delaunay tessellation based methods for reconstructing continuous fields from discretely sampled data sets is discussed. The succesfull operation as ``multidimensional interpolation'' method is corroborated…

Astrophysics · Physics 2009-10-31 Rien van de Weygaert , Willem Schaap

We redevelop persistent homology (topological persistence) from a categorical point of view. The main objects of study are diagrams, indexed by the poset of real numbers, in some target category. The set of such diagrams has an interleaving…

Algebraic Topology · Mathematics 2014-05-13 Peter Bubenik , Jonathan A. Scott

Given a network, the statistical ensemble of its graph-Voronoi diagrams with randomly chosen cell centers exhibits properties convertible into information on the network's large scale structures. We define a node-pair level measure called…

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

Consider a Voronoi tiling of the Euclidean space based on a realization of a inhomogeneous Poisson random set. A Voronoi polyomino is a finite and connected union of Voronoi tiles. In this paper we provide tail bounds for the number of…

Probability · Mathematics 2011-08-15 Leandro P. R. Pimentel

We address the problem of finding a wombling boundary in point data generated by a general Poisson point process, a specific example of which is an LHC event sample distributed in the phase space of a final state signature, with the…

High Energy Physics - Phenomenology · Physics 2021-01-12 Konstantin T. Matchev , Alexander Roman , Prasanth Shyamsundar

Voronoi tessellations of Poisson point processes are widely used for modeling many types of physical and biological systems. In this paper, we analyze simulated Poisson-Voronoi structures containing a total of 250,000,000 cells to provide…

Computational Physics · Physics 2014-01-09 Emanuel A. Lazar , Jeremy K. Mason , Robert D. MacPherson , David J. Srolovitz

Topological data analysis is becoming increasingly relevant to support the analysis of unstructured data sets. A common assumption in data analysis is that the data set is a sample---not necessarily a uniform one---of some high-dimensional…

Algebraic Topology · Mathematics 2021-01-20 Bastian Rieck , Markus Banagl , Filip Sadlo , Heike Leitte

Appropriately representing elements in a database so that queries may be accurately matched is a central task in information retrieval; recently, this has been achieved by embedding the graphical structure of the database into a manifold in…

Machine Learning · Statistics 2023-07-10 Yueqi Cao , Athanasios Vlontzos , Luca Schmidtke , Bernhard Kainz , Anthea Monod

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

A novel algorithm to detect coherent structures with sparse Lagrangian particle tracking data, using Voronoi tessellation and techniques from spectral graph theory, is tested. Neighbouring tracer particles are naturally identified through…

Fluid Dynamics · Physics 2021-07-29 F. A. C. Martins , D. E. Rival

Persistent homology is a popular computational tool for analyzing the topology of point clouds, such as the presence of loops or voids. However, many real-world datasets with low intrinsic dimensionality reside in an ambient space of much…

Machine Learning · Computer Science 2024-11-01 Sebastian Damrich , Philipp Berens , Dmitry Kobak

Persistent homology is a central methodology in topological data analysis that has been successfully implemented in many fields and is becoming increasingly popular and relevant. The output of persistent homology is a persistence diagram --…

Statistics Theory · Mathematics 2024-04-24 Konstantin Häberle , Barbara Bravi , Anthea Monod
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