Reconstructing galaxy spectral energy distributions from broadband photometry

We present a novel approach to photometric redshifts, one that merges the a dvantages of both the template-fitting and empirical-fitting algorithms wit hout any of their disadvantages. This technique derives a set of templates describing the spectral energy distributions of galaxies from a catalog wit h both multicolor photometry and spectroscopic redshifts. The algorithm is essentially using the shapes of the templates as the fitting parameters. Fr om simulated multicolor data we show that for a small training set of galax ies we can reconstruct robustly the underlying spectral energy distribution s even in the presence of substantial errors in the photometric observation s. We apply these techniques to the multicolor and spectroscopic observatio ns of the Hubble Deep Field, building a set of template spectra that reprod uced the observed galaxy colors to better than 10%. Finally, we demonstrate that these improved spectral energy distributions lead to a photometric re dshift relation for the Hubble Deep Field that is more accurate than standa rd template-based approaches.