The Voronoi tessellation method in astronomy

Abstract

The Voronoi tessellation is a natural way of space segmentation, which has many applications in various fields of science and technology, as well as in social sciences and visual art. The varieties of the Voronoi tessellation methods are commonly used in computational fluid dynamics, computational geometry, geolocation and logistics, game dev programming, cartography, engineering, liquid crystal electronic technology, machine learning, etc. The very innovative results were obtained in astronomy, namely for a large-scale galaxy distribution and cosmic web pattern, for revealing the quasi-periodicity in a pencil-beam survey, for a description of constraints on the isotropic cosmic microwave background and the explosion scenario likely supernova events, for image processing, adaptive smoothing, segmentation, for signal-to-noise ratio balancing, for spectrography data analysis as well as in the moving-mesh cosmology simulation. We briefly describe these results, paying more attention to the practical application of the Voronoi tessellation related to the spatial large-scale galaxy distribution.

24 pages, 6 figures, accepted to Intelligent Astrophysics, Eds. I. Zelinka, D. Baron, M. Brescia

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• Machine learning technique for morphological classification of galaxies from the SDSS. III. Image-based inference of detailed features
• Machine learning technique for morphological classification of galaxies from SDSS. II. The image-based morphological catalogs of galaxies at 0.02<z<0.1
• AMEP: The Active Matter Evaluation Package for Python
• Discovery of the Polar Ring Galaxies with deep learning
• Milky Way galaxy-analogs and isolated galaxies with bars: environmental density in the Local Volume