Search for the edge-on galaxies using an artificial neural network

Autor:	Savchenko, S. S., Makarov, D. I., Antipova, A. V., Tikhonenko, I. S.
Rok vydání:	2023
Předmět:	Astrophysics - Instrumentation and Methods for Astrophysics Astrophysics - Astrophysics of Galaxies
Zdroj:	Astronomy and Computing, Volume 46, 100771, 2024
Druh dokumentu:	Working Paper
DOI:	10.1016/j.ascom.2023.100771
Popis:	We present an application of an artificial neural network methodology to a modern wide-field sky survey Pan-STARRS1 in order to build a high-quality sample of disk galaxies visible in edge-on orientation. Such galaxies play an important role in the study of the vertical distribution of stars, gas and dust, which is usually not available to study in other galaxies outside the Milky Way. We give a detailed description of the network architecture and the learning process. The method demonstrates good effectiveness with detection rate about 97\% and it works equally well for galaxies over a wide range of brightnesses and sizes, which resulted in a creation of a catalogue of edge-on galaxies with $10^5$ of objects. The catalogue is published on-line with an open access. Comment: 15 pages, 11 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2312.02742 Zobrazit plný text záznamu View this record from Arxiv