$\mu$--PhotoZ: Photometric Redshifts by Inverting the Tolman Surface Brightness Test

Abstract

Surface brightness is a fundamental observational parameter of galaxies. We show, for the first time in detail, how it can be used to obtain photometric redshifts for galaxies, the $\mu$-PhotoZ method. We demonstrate that the Tolman surface brightness relation, $\mu \propto (1+z{)}^{-4}$, is a powerful tool for determining galaxy redshifts from photometric data. We develop a model using $\mu$ and a color percentile (ranking) measure to demonstrate the $\mu$-PhotoZ method. We apply our method to a set of galaxies from the SHELS survey, and demonstrate that the photometric redshift accuracy achieved using the surface brightness method alone is comparable with the best color-based methods. We show that the $\mu$-PhotoZ method is very effective in determining the redshift for red galaxies using only two photometric bands. We discuss the properties of the small, skewed, non-gaussian component of the error distribution. We calibrate ${\mu }_r,(r-i)$ from the SDSS to redshift, and tabulate the result, providing a simple, but accurate look up table to estimate the redshift of distant red galaxies.

Accepted for publication in the Astronomical Journal

References in corpus (3)

• The Zurich Extragalactic Bayesian Redshift Analyzer (ZEBRA) and its first application: COSMOS
• Multiaperture $UBVRIzJHK$ Photometry of Galaxies in the Coma Cluster
• Color-magnitude relations of late-type galaxies

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• New Approaches To Photometric Redshift Prediction Via Gaussian Process Regression In The Sloan Digital Sky Survey
• A New Technique for Galaxy Photometric Redshifts in the Sloan Digital Sky Survey
• Photometric Redshifts with Surface Brightness Priors
• SuperNova Acceleration Probe (SNAP): Investigating Photometric Redshift Optimization
• Photometric Redshift Estimation with Galaxy Morphology using Self-Organizing Maps