A method for classification of red, blue, and green galaxies using fuzzy set theory. (2nd September 2020)

• Record Type: Journal Article
• Authors: Pandey, Biswajit
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 499:Number 1(2020)
• Page Start: L31
• Page End: L35
• Publication Date: 2020-09-02
• Subjects: methods: data analysis -- methods: statistical -- galaxies: evolution -- galaxies: formation -- large scale structure of Universe; Astronomy -- Research -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnrasl/slaa152
• Languages: English
• ISSNs: 1745-3933

Abstract

ABSTRACT: Red and blue galaxies are traditionally classified using some specific cuts in colour or other galaxy properties, which are supported by empirical arguments. The vagueness associated with such cuts are likely to introduce a significant contamination in these samples. Fuzzy sets are vague boundary sets that can efficiently capture the classification uncertainty in the absence of any precise boundary. We propose a method for classification of galaxies according to their colours using fuzzy set theory. We use data from the Sloan Digital Sky Survey (SDSS) to construct a fuzzy set for red galaxies with its members having different degrees of 'redness'. We show that the fuzzy sets for the blue and green galaxies can be obtained from it using different fuzzy operations. We also explore the possibility of using fuzzy relation to study the relationship between different galaxy properties and discuss its strengths and limitations.