2021
DOI: 10.1093/mnras/stab2995
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Dark Energy Survey Year 3 results: galaxy sample for BAO measurement

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 ${\sim }\, 4100$ deg2to a depth of i = 22.3 (AB) at 10σ. It contains 7031 993 galaxies in the redshift range from $z$ = 0.6 to 1.1, with a mean effectiv… Show more

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Cited by 13 publications
(37 citation statements)
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References 68 publications
(82 reference statements)
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“…We start by applying the same color cut as in Y1 to the Gold sample to select red galaxies. Despite the changes in photometry from Y1 and Y3, the color selection still isolates galaxies at z > 0.5, as attested in [38]. The primary selection includes the aforementioned color cut, a magnitude cut as a function of photometric redshift z photo (to remove fainter galaxies at lower redshifts), and the redshift range.…”
Section: B Bao Samplementioning
confidence: 96%
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“…We start by applying the same color cut as in Y1 to the Gold sample to select red galaxies. Despite the changes in photometry from Y1 and Y3, the color selection still isolates galaxies at z > 0.5, as attested in [38]. The primary selection includes the aforementioned color cut, a magnitude cut as a function of photometric redshift z photo (to remove fainter galaxies at lower redshifts), and the redshift range.…”
Section: B Bao Samplementioning
confidence: 96%
“…The sample covers 4108.47 deg 2 , almost three times larger than the Y1 sample, and comprises 7,031,993 galaxies in the redshift range 0.6 < z < 1.1, up to a magnitude limit of i < 22.3ðAB; 10σ). Full details about the sample selection and characterization is found in [38], here we summarize the main properties.…”
Section: B Bao Samplementioning
confidence: 99%
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“…Avila et al 2020;Alam et al 2021;Rossi et al 2021), understand the impact of observational systematic effects (e.g. Rosell et al 2022;Spinelli et al 2022) or to compute covariance matrices (e.g. Manera et al 2013;Avila et al 2018;Zhao et al 2021).…”
Section: Introductionmentioning
confidence: 99%