Red Dragon: a redshift-evolving Gaussian mixture model for galaxies
Abstract
Precision-era optical cluster cosmology calls for a precise definition of the red sequence (RS), consistent across redshift. To this end, we present the Red Dragon algorithm: an error-corrected multivariate Gaussian mixture model (GMM). Simultaneous use of multiple colours and smooth evolution of GMM parameters result in a continuous RS and blue cloud (BC) characterization across redshift, avoiding the discontinuities of red fraction inherent in swapping RS selection colours. Based on a mid-redshift spectroscopic sample of SDSS galaxies, an RS defined by Red Dragon selects quiescent galaxies (low specific star formation rate) with a balanced accuracy of over $90{{\ \rm per\ cent}}$. This approach to galaxy population assignment gives more natural separations between RS and BC galaxies than hard cuts in colour-magnitude or colour-colour spaces. The Red Dragon algorithm is publicly available at bitbucket.org/wkblack/red-dragon-gamma/.
- Publication:
-
Monthly Notices of the Royal Astronomical Society
- Pub Date:
- October 2022
- DOI:
- 10.1093/mnras/stac2052
- arXiv:
- arXiv:2204.10141
- Bibcode:
- 2022MNRAS.516.1170B
- Keywords:
-
- methods: numerical;
- techniques: photometric;
- galaxies: stellar content;
- large-scale structure of Universe;
- Astrophysics - Cosmology and Nongalactic Astrophysics;
- Astrophysics - Astrophysics of Galaxies
- E-Print:
- 17 pages, 14 figures