Phenotypic redshifts with self-organizing maps: A novel method to
  characterize redshift distributions of source galaxies for weak lensing
  Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on
coarse measurements of spectral energy distributions in a few filters to
estimate the redshift distribution of source galaxies. In this regime, sample
variance, shot noise, and selection effects limit the attainable accuracy of
redshift calibration and thus of cosmological constraints. We present a new
method to combine wide-field, few-filter measurements with catalogs from deep
fields with additional filters and sufficiently low photometric noise to break
degeneracies in photometric redshifts. The multi-band deep field is used as an
intermediary between wide-field observations and accurate redshifts, greatly
reducing sample variance, shot noise, and selection effects. Our implementation
of the method uses self-organizing maps to group galaxies into phenotypes based
on their observed fluxes, and is tested using a mock DES catalog created from
N-body simulations. It yields a typical uncertainty on the mean redshift in
each of five tomographic bins for an idealized simulation of the DES Year 3
weak-lensing tomographic analysis of $\sigma_{\Delta z} = 0.007$, which is a
60% improvement compared to the Year 1 analysis. Although the implementation of
the method is tailored to DES, its formalism can be applied to other large
photometric surveys with a similar observing strategy.
