Producing a BOSS CMASS sample with DES imaging Academic Article uri icon


  • ABSTRACT We present a sample of galaxies with the Dark 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 galaxygalaxy 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 117293 effective galaxies covering $1244,deg ^2$. 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 $Delta b = 0.010^{+0.045}_{-0.052}$ and $Delta z = left(3.46^{+5.48}_{-5.55}
    ight) imes 10^{-3}$ for the SGC portion of CMASS, and $Delta b = 0.044^{+0.044}_{-0.043}$ and $Delta z= (3.51^{+4.93}_{-5.91}) imes 10^{-3}$ 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 1.

published proceedings


altmetric score

  • 5.08

author list (cited authors)

  • Lee, S., Huff, E. M., Ross, A. J., Choi, A., Hirata, C., Honscheid, K., ... Zuntz, J.

citation count

  • 17

complete list of authors

  • Lee, S||Huff, EM||Ross, AJ||Choi, A||Hirata, C||Honscheid, K||MacCrann, N||Troxel, MA||Davis, C||Eifler, TF||Cawthon, R||Elvin-Poole, J||Annis, J||Avila, S||Bertin, E||Brooks, D||Carnero Rosell, A||Carrasco Kind, M||Carretero, J||da Costa, LN||De Vicente, J||Desai, S||Flaugher, B||Fosalba, P||García-Bellido, J||Gaztanaga, E||Gerdes, DW||Gruen, D||Gruendl, RA||Gschwend, J||Gutierrez, G||Hollowood, DL||James, DJ||Jeltema, T||Kuehn, K||Lima, M||Maia, MAG||Marshall, JL||Martini, P||Melchior, P||Menanteau, F||Miller, CJ||Miquel, R||Ogando, RLC||Palmese, A||Plazas, AA||Sanchez, E||Scarpine, V||Schubnell, M||Serrano, S||Sevilla-Noarbe, I||Smith, M||Soares-Santos, M||Sobreira, F||Suchyta, E||Swanson, MEC||Tarle, G||Thomas, D||Weller, J||Zuntz, J

publication date

  • September 2019