Low/High Redshift Classification of Emission Line Galaxies in the HETDEX survey. Issue Volume 10:Issue S306(2014) (1st July 2015)

• Record Type: Journal Article
• Authors: Acquaviva, Viviana; Gawiser, Eric; Leung, Andrew S.; Martin, Mario R.
• Editors: Heavens, A. F.; Starck, J.-L.; Krone-Martins, A.
• Is Part Of: Proceedings of the International Astronomical Union. Volume 10:Issue S306(2014)
• Page Start: 365
• Page End: 368
• Publication Date: 2015-07-01
• Subjects: galaxies: distances and redshifts, -- methods: statistical, -- Machine Learning; Astronomy -- Congresses; Astronomy -- Periodicals; 520
• DOI: 10.1017/S1743921314013805
• Languages: English
• ISSNs: 1743-9213

Abstract

Abstract: We discuss different methods to separate high- from low-redshift galaxies based on a combination of spectroscopic and photometric observations. Our baseline scenario is the Hobby-Eberly Telescope Dark Energy eXperiment (HETDEX) survey, which will observe several hundred thousand Lyman Alpha Emitting (LAE) galaxies at 1.9 < z < 3.5, and for which the main source of contamination is [OII]-emitting galaxies at z < 0.5. Additional information useful for the separation comes from empirical knowledge of LAE and [OII] luminosity functions and equivalent width distributions as a function of redshift. We consider three separation techniques: a simple cut in equivalent width, a Bayesian separation method, and machine learning algorithms, including support vector machines. These methods can be easily applied to other surveys and used on simulated data in the framework of survey planning.