Virgo Cluster Membership Based on <i>K</i>-Means Algorithm

作     者：Ibrahim Mohamed Selim Passent Elkafrawy Walid Dabour Mohamed Eassa 

作者机构：National Research Institute of Astronomy and Geophysics Cairo Egypt Computer Science Department Integrated Thebes Institute Cairo Egypt Math and Computer Science Department Faculty of Science Menoufia University Shibin El Kom Egypt Computer Science Department Taibah University Alula Branch Medina KSA 

出 版 物：《International Journal of Astronomy and Astrophysics》 (天文学与天体物理学国际期刊（英文）)

年 卷 期：2020年第10卷第1期

页      面：1-10页

学科分类：07[理学] 070401[理学-天体物理] 0704[理学-天文学] 

主　　题：Virgo Cluster K-Means Normal Distribution 

摘      要：The Virgo cluster of galaxies is of great importance to study the development of the universe due to its close distance from the earth as well as being the center of the local super cluster. The problem that faces Virgo cluster studies is that it shares the same right ascension (RA) and Declination (DEC) ranges with large number of background as well as foreground galaxies. This study aims to geometrically and statistically estimate Virgo cluster membership. The study employs Virgo cluster data, prepared by Harvard University. The radial velocity (RV) data of the Virgo cluster were treated and employed in exchange of missing galaxies’ third dimension, taking advantage of their proportionality. The data were treated by K-means algorithm, using Matlab 2014, and visual and logical exclusion of extremity galaxies to determine the rational center of the Virgo galaxies cluster. Results were presented, compared and discussed. Finally distances of galaxies from the Virgo cluster center were employed along with normal probability distribution characteristics to identify the most probable Virgo cluster members from the range of Virgo cluster of galaxies. The results showed that out of 17,466 objects surveyed in Virgo galaxy range, only few of galaxies were estimated to be genuine Virgo members.