Producing a BOSS CMASS sample with DES imaging
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We present a sample of galaxies with theDark Energy Survey (DES) photometry that replicates the properties of the BOSS CMASS sample. The CMASS galaxy sample has been well characterized by the Sloan Digital Sky Survey (SDSS) collaboration and was used to obtain the most powerful redshift-space galaxy clustering measurements to date. A joint analysis of redshift-space distortions (such as those probed by CMASS from SDSS) and a galaxy-galaxy lensing measurement for an equivalent sample from DES can provide powerful cosmological constraints. Unfortunately, the DES and SDSS-BOSS footprints have only minimal overlap, primarily on the celestial equator near the SDSS Stripe 82 region. Using this overlap, we build a robust Bayesian model to select CMASS-like galaxies in the remainder of the DES footprint. The newly defined DES-CMASS (DMASS) sample consists of 117 293 effective galaxies covering 1244 deg2. Through various validation tests, we show that the DMASS sample selected by this model matches well with the BOSS CMASS sample, specifically in the South Galactic cap (SGC) region that includes Stripe 82. Combining measurements of the angular correlation function and the clustering-z distribution of DMASS, we constrain the difference in mean galaxy bias and mean redshift between the BOSS CMASS and DMASS samples to be Δb = 0.010+0.045 -0.052 and Δz = (3.46+5.48 -5.55) × 10-3 for the SGC portion of CMASS, and Δb = 0.044+0.044 -0.043 and Δz = (3.51+4.93 -5.91) × 10-3 for the full CMASS sample. These values indicate that the mean bias of galaxies and mean redshift in the DMASS sample are consistent with both CMASS samples within 1σ.
|Number of pages||20|
|Journal||Monthly Notices of the Royal Astronomical Society|
|Early online date||2 Sep 2019|
|Publication status||Published - 1 Oct 2019|
Rights statement: This article has been accepted for publication in MNRAS © 2019 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.
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