Spectroscopic Needs for Training of LSST Photometric Redshifts
  This white paper summarizes those conclusions of the Snowmass White Paper
"Spectroscopic Needs for Imaging Dark Energy Experiments" (arXiv:1309.5384)
which are relevant to the training of LSST photometric redshifts; i.e., the use
of spectroscopic redshifts to improve algorithms and reduce photo-z errors. The
larger and more complete the available training set is, the smaller the RMS
error in photo-z estimates should be, increasing LSST's constraining power.
Among the better US-based options for this work are the proposed MANIFEST fiber
feed for the Giant Magellan Telescope or (with lower survey speed) the WFOS
spectrograph on the Thirty Meter Telescope (TMT). Due to its larger field of
view and higher multiplexing, the PFS spectrograph on Subaru would be able to
obtain a baseline training sample faster than TMT; comparable performance could
be achieved with a highly-multiplexed spectrograph on Gemini with at least a 20
arcmin diameter field of view.
