Photometric Redshifts and Model Spectral Energy Distributions of Galaxies From the SDSS-III BOSS DR10 Data

TL;DR

This paper develops specialized spectral energy distribution models for BOSS CMASS galaxies to improve photometric redshift estimation, achieving very low outlier rates and high accuracy.

Contribution

It introduces modified SED templates tailored for CMASS galaxies, enhancing photometric redshift accuracy over previous SDSS methods.

Findings

Photometric redshift outlier rate of 0.22%.

Bias in redshift estimates is 0.002.

Redshift scatter (σ68) is 0.026.

Abstract

We construct a set of model spectra specifically designed to match the colours of the BOSS CMASS galaxies and to be used with photometric redshift template fitting techniques. As a basis we use a set of spectral energy distributions (SEDs) of single and composite stellar population models. These models cannot describe well the whole colour range populated by the CMASS galaxies at all redshifts, wherefore we modify them by multiplying the SEDs with $\lambda^{-\beta}$ for $\lambda>\lambda_i$ for different values of $\lambda_i$ and $\beta$. When fitting these SEDs to the colours of the CMASS sample, with a burst and dust components in superposition, we can recreate the location in colour spaces inhabited by the CMASS galaxies. From the best fitting models we select a small subset in a two-dimensional plane, whereto the galaxies were mapped by a self-organizing map. These models are used for the estimation of photometric redshifts with a Bayesian template fitting code. The photometric redshifts with the novel templates have a very small outlier rate of $0.22\,\%$, a low bias $\langle\Delta z/(1+z)\rangle=2.0\cdot10^{-3}$, and scatter of $\sigma_{68}=0.026$ in the restframe. Using our models, the galaxy colours are reproduced to a better extent with the photometric redshifts of this work than with photometric redshifts of SDSS.