Abstract

We describe the construction of a template set of spectral energy distributions (SEDs) for the estimation of photometric redshifts of luminous red galaxies (LRGs) with a Bayesian template fitting method. By examining the color properties of several publicly available SED sets within a redshift range of 0<z<0.5 and comparing them to SDSS DR7 data, we show that only some of the investigated SEDs approximately match the colors of the LRG data throughout the redshift range, however not at the quantitative level required for precise photometric redshifts. We generate new SEDs by superposing model SEDs of composite stellar populations with a burst model, allowing both components to be reddened by dust, in order to match the data in five different redshift bins. We select a set of SEDs which represents the LRG data in color space within five redshift bins, thus defining our new SED template set for photometric redshift estimates. The results we get with the new template set and our Bayesian template fitting photometric redshift code (PhotoZ) are nearly unbiased, with a scatter of \sigma(\Delta z)=0.027 (including outliers), and a fraction of catastrophic outliers (|z_phot-z_spec|/(1+z_spec)>0.15) of 0.12%. We show that templates that optimally describe the brightest galaxies (-24.5<M_R<-22.7) indeed vary from z=0.1 to z=0.5, consistent with aging of the stellar population. Furthermore, we find that templates that optimally describe galaxies at z<0.1 strongly differ as a function of the absolute magnitude of the galaxies, indicating an increase in star formation activity for less luminous galaxies. Our findings based on the photometry of the SDSS LRGs and our SED template fitting are supported by comparison to the average SDSS LRG spectra in different luminosity and redshift bins.

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