Characterization and modeling of contamination for Lyman break galaxy
  samples at high redshift
  The selection of high redshift sources from broad-band photometry using the
Lyman-break galaxy (LBG) technique is a well established methodology, but the
characterization of its contamination for the faintest sources is still
incomplete. We use the optical and near-IR data from four (ultra)deep Hubble
Space Telescope legacy fields to investigate the contamination fraction of LBG
samples at z~5-8 selected using a colour-colour method. Our approach is based
on characterizing the number count distribution of interloper sources, that is
galaxies with colors similar to those of LBGs, but showing detection at
wavelengths shorter than the spectral break. Without sufficient sensitivity at
bluer wavelengths, a subset of interlopers may not be properly classified, and
contaminate the LBG selection. The surface density of interlopers in the sky
gets steeper with increasing redshift of LBG selections. Since the intrinsic
number of dropouts decreases significantly with increasing redshift, this
implies increasing contamination from misclassified interlopers with increasing
redshift, primarily by intermediate redshift sources with unremarkable
properties (intermediate ages, lack of ongoing star formation and low/moderate
dust content). Using Monte Carlo simulations, we estimate that the CANDELS deep
data have contamination induced by photometric scatter increasing from ~2% at
z~5 to ~6% at z~8 for a typical dropout color >1 mag, with contamination
naturally decreasing for a more stringent dropout selection. Contaminants are
expected to be located preferentially near the detection limit of surveys,
ranging from 0.1 to 0.4 contaminants per arcmin2 at J=30, depending on the
field considered. This analysis suggests that the impact of contamination in
future studies of z>10 galaxies needs to be carefully considered.
