Producing a BOSS-CMASS sample with DES imaging
  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 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 $1,244 {\rm
deg}^2$. 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 $\Delta z = \left( 3.46^{+5.48}_{-5.55} \right)
\times 10^{-3}$ for the SGC portion of CMASS, and $\Delta b =
0.044^{+0.044}_{-0.043} $ and $\Delta z= ( 3.51^{+4.93}_{-5.91}) \times
10^{-3}$ for the full CMASS sample. These values indicate that the mean bias of
galaxies and mean redshift in the DMASS sample is consistent with both CMASS
samples within $1\sigma$.
