Creating Spectral Templates from Multicolor Redshift Surveys

Abstract

We present a novel method capable of creating optimal eigenspectra from multicolor redshift surveys for photometric redshift estimation. Our iterative training algorithm modifies the templates to represent the photometric measurements better. We present a short description of our algorithm here. We show that the corrected templates give more precise photometric redshifts, essentially a ``free'' feature, since we were not fitting for the redshifts themselves.