Photo-z Quality Cuts and their Effect on the Measured Galaxy Clustering
  Photometric galaxy surveys are an essential tool to further our understanding
of the large-scale structure of the universe, its matter and energy content and
its evolution. These surveys necessitate the determination of the galaxy
redshifts using photometric techniques (photo-z). Oftentimes, it is
advantageous to remove from the galaxy sample those for which one suspects that
the photo-z estimation might be unreliable. In this paper, we show that
applying these photo-z quality cuts blindly can grossly bias the measured
galaxy correlations within and across photometric redshift bins. We then extend
the work of Ho et al. (2012) and Ross et al. (2011) to develop a simple and
effective method to correct for this using the data themselves. Finally, we
apply the method to the Mega-Z catalog, containing about a million luminous red
galaxies in the redshift range 0.45 < z < 0.65. After splitting the sample into
four \Delta z = 0.05 photo-z bins using the BPZ algorithm, we see how our
corrections bring the measured galaxy auto- and cross-correlations into
agreement with expectations. We then look for the BAO feature in the four bins,
with and without applying the photo-z quality cuts, and find a broad agreement
between the BAO scales extracted in both cases. Intriguingly, we observe a
correlation between galaxy density and photo-z quality even before any photo-z
quality cuts are applied. This may be due to uncorrected observational effects
that result in correlated gradients across the sky of the galaxy density and
the galaxy photo-z precision. Our correction procedure could also help to
mitigate some of these systematic effects.
