The SDSS-IV extended Baryonic Oscillation Spectroscopic Survey: Luminous Red Galaxy Target Selection
Abhishek Prakash, Timothy C. Licquia, Jeffrey A. Newman, Ashley J., Ross, Adam D. Myers, Kyle S. Dawson, Jean-Paul Kneib, Will J. Percival,, Julian E. Bautista, Johan Comparat, Jeremy L. Tinker, David J. Schlegel, Rita, Tojeiro, Shirley Ho, Dustin Lang, Sandhya M. Rao

TL;DR
This paper details the selection algorithm for Luminous Red Galaxy targets in the eBOSS survey, achieving high redshift accuracy and low contamination, enabling large-scale structure studies at higher redshifts.
Contribution
The paper introduces an effective target selection algorithm combining SDSS and WISE data, optimized for high-redshift LRGs with low stellar contamination and reliable redshift measurements.
Findings
Approximately 50 LRGs per square degree selected
89% of targets yield secure redshifts
Sample is uniform and suitable for large-scale structure analysis
Abstract
We describe the algorithm used to select the Luminous Red Galaxy (LRG) sample for the extended Baryon Oscillation Spectroscopic Survey (eBOSS) of the Sloan Digital Sky Survey IV (SDSS-IV) using photometric data from both the SDSS and the Wide-Field Infrared Survey Explorer (WISE). LRG targets are required to meet a set of color selection criteria and have z-band and i-band MODEL magnitudes z < 19.95 and 19.9 < i < 21.8, respectively. Our algorithm selects roughly 50 LRG targets per square degree, the great majority of which lie in the redshift range 0.6 < z < 1.0 (median redshift 0.71). We demonstrate that our methods are highly effective at eliminating stellar contamination and lower-redshift galaxies. We perform a number of tests using spectroscopic data from SDSS-III/BOSS to determine the redshift reliability of our target selection and its ability to meet the science requirements of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
