A new method to improve photometric redshift reconstruction: Applications to the Large Synoptic Survey Telescope

In the next decade, the Large Synoptic Survey Telescope (LSST) will become a major facility for the astronomical community. However, accurately determining the redshifts of the observed galaxies without using spectroscopy is a major challenge. Reconstruction of the redshifts with high resolution and well-understood uncertainties is mandatory for many science goals, including the study of baryonic acoustic oscillations (BAO). We investigate different approaches to establish the accuracy that can be reached by the LSST six-band photometry. We construct a realistic mock galaxy catalog, based on the Great Observatories Origins Deep Survey (GOODS) luminosity function, by simulating the expected apparent magnitude distribution for the LSST. We demonstrate that the photometric redshifts will be accurately estimated with the LSST if a Bayesian prior probability and a calibration sample are used.