A method for classification of red, blue, and green galaxies using fuzzy set theory
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Sep 02, 2020
- Source ID
- 10.1093/mnrasl/slaa152
Entities
People
- Biswajit Pandey
Organizations
- Alfred P. Sloan Foundation
- American Museum of Natural History
- Case Western Reserve University
- Chinese Academy of Sciences
- Department of Science and Technology
- Drexel University
- Higher Education Funding Council for England
- Institute for Advanced Study
- Johns Hopkins University
- Los Alamos National Laboratory
- Max Planck Society
- National Aeronautics and Space Administration
- National Science Foundation
- New Mexico State University
- Ohio State University Press
- Princeton University
- Science and Engineering Research Board
- United States Department of Energy
- United States Naval Observatory
- University of Basel
- University of Cambridge
- University of Chicago
- University of Pittsburgh
- University of Portsmouth
- University of Washington
- Visva-Bharati University