(Authors: Jeff Newman, A. Abate, F. Abdalla, S. Allam, S. Allen, R. Ansari, S. Bailey, W. Barkhouse, T. Beers, M. Blanton, M. Brodwin, J. Brownstein, R. Brunner, M. Carrasco-Kind, J. Cervantes-Cota, E. Chisari, M. Colless, J. Comparat, J. Coupon, E. Cheu, C. Cunha,A. de la Macorra, I. Dell'Antonio, B. Frye, E. Gawiser, N. Gehrels, K. Grady, A. Hagen, P. Hall, A. Hearin, H. Hildebrandt, C. Hirata, S. Ho, K. Honscheid, D. Huterer, Z. Ivezic, J.-P. Kneib, J. Kruk, O. Lahav, R. Mandelbaum, J. Marshall, D. Matthews, B. Ménard, R. Miquel, M. Moniez, W. Moos, J. Moustakas, C. Papovich, J. Peacock, C. Park, J. Rhodes, J-S. Ricol, I. Sadeh, A. Slozar,S. Schmidt, D. Stern, T. Tyson, A. von der Linden, R. Wechsler, W. Wood-Vasey, A. Zentner.)
As part of the Snowmass process, we investigated the scope of spectroscopic datasets that could enhance the capabilities of LSST, posted to the arxiv at http://arxiv.org/abs/1309.5384 . Specifically, large sets of objects with spectroscopic redshift measurements will be needed for LSST to achieve its full potential, serving two goals: training, i.e., the use of objects with known redshift to develop and optimize photometric redshift algorithms; and calibration, i.e., the characterization of moments of redshift (or photo-z error) distributions. Better training makes cosmological constraints from a given experiment stronger, while highly-accurate calibration is needed for photo-z systematics not to dominate errors.
In the resulting white paper, we investigate the required scope of spectroscopic datasets which can serve both these purposes for LSST and other dark energy experiments, as well as the time required to obtain such data with instruments available in the next decade. Large time allocations on kilo-object spectrographs will be necessary, ideally augmented by infrared spectroscopy from space. Alternatively, precision calibrations could be obtained by measuring cross-correlation statistics using samples of bright objects from a large baryon acoustic oscillation experiment such as DESI. We also summarize the additional work on photometric redshift methods needed to prepare for LSST.