Abstract
In this paper, we present and validate the galaxy sample used for the analysis of the baryon acoustic oscillation (BAO) signal in the Dark Energy Survey (DES) Y3 data. The definition is based on a colour and redshift-dependent magnitude cut optimized to select galaxies at redshifts higher than 0.5, while ensuring a high-quality determination. The sample covers similar to 4100 deg(2) to a depth of i = 22.3 (AB) at 10 sigma. It contains 7031 993 galaxies in the redshift range from z = 0.6 to 1.1, with a mean effective redshift of 0.835. Redshifts are estimated with the machine learning algorithm DNF, and are validated using the VIPERS PDR2 sample. We find a mean redshift bias of z(bi)(as) similar to 0.01 and a mean uncertainty, in units of 1 + z, of sigma(68)similar to 0.03. We evaluate the galaxy population of the sample, showing it is mostly built upon Elliptical to Sbc types. Furthermore, we find a low level of stellar contamination of less than or similar to 4 per cent. We present the method used to mitigate the effect of spurious clustering coming from observing conditions and other large-scale systematics. We apply it to the BAO sample and calculate weights that are used to get a robust estimate of the galaxy clustering signal. This paper is one of a series dedicated to the analysis of the BAO signal in DFS Y3. In the companion papers, we present the galaxy mock catalogues used to calibrate the analysis and the angular diameter distance constraints obtained through the fitting to the BAO scale.
Item Type: | Journal article |
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Faculties: | Physics |
Subjects: | 500 Science > 530 Physics |
ISSN: | 0035-8711 |
Language: | English |
Item ID: | 101540 |
Date Deposited: | 05. Jun 2023, 15:37 |
Last Modified: | 05. Jun 2023, 15:37 |