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

TL;DR

This paper introduces the $$-PhotoZ method, which uses surface brightness and the Tolman relation to accurately estimate galaxy redshifts from photometric data, especially effective for red galaxies with minimal bands.

Contribution

It presents a novel approach to photometric redshift estimation based on surface brightness, expanding the tools available beyond traditional color-based methods.

Findings

Photometric redshift accuracy comparable to color-based methods.

Effective redshift determination for red galaxies using only two bands.

Calibrated surface brightness-redshift relation with a simple lookup table.

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.