Photometric Redshifts with the LSST: Evaluating Survey Observing
  Strategies
  In this paper we present and characterize a nearest-neighbors color-matching
photometric redshift estimator that features a direct relationship between the
precision and accuracy of the input magnitudes and the output photometric
redshifts. This aspect makes our estimator an ideal tool for evaluating the
impact of changes to LSST survey parameters that affect the measurement errors
of the photometry, which is the main motivation of our work (i.e., it is not
intended to provide the "best" photometric redshifts for LSST data). We show
how the photometric redshifts will improve with time over the 10-year LSST
survey and confirm that the nominal distribution of visits per filter provides
the most accurate photo-$z$ results. The LSST survey strategy naturally
produces observations over a range of airmass, which offers the opportunity of
using an SED- and $z$-dependent atmospheric affect on the observed photometry
as a color-independent redshift indicator. We show that measuring this airmass
effect and including it as a prior has the potential to improve the photometric
redshifts and can ameliorate extreme outliers, but that it will only be
adequately measured for the brightest galaxies, which limits its overall impact
on LSST photometric redshifts. We furthermore demonstrate how this airmass
effect can induce a bias in the photo-$z$ results, and caution against survey
strategies that prioritize high-airmass observations for the purpose of
improving this prior. Ultimately, we intend for this work to serve as a guide
for the expectations and preparations of the LSST science community with
regards to the minimum quality of photo-$z$ as the survey progresses.
