Photometric Redshift Biases from Galaxy Evolution

TL;DR

This paper examines how differences in galaxy properties between bright training samples and faint target populations can introduce significant biases in photometric redshift estimates, impacting cosmological measurements.

Contribution

It identifies specific galaxy evolution factors causing photo-z biases and emphasizes the need for comprehensive spectroscopic training sets covering faint galaxy populations.

Findings

Small metallicity shifts (~0.003dex) induce 10^-3 bias in photo-z

Minor AGN flux contamination (~0.2%) causes significant biases

Extrapolating bright galaxy behavior to faint populations is risky

Abstract

Proposed cosmological surveys will make use of photometric redshifts of galaxies that are significantly fainter than any complete spectroscopic redshift surveys that exist to train the photo-z methods. We investigate the photo-z biases that result from known differences between the faint and bright populations: a rise in AGN activity toward higher redshift, and a metallicity difference between intrinsically luminous and faint early-type galaxies. We find that even very small mismatches between the mean photometric target and the training set can induce photo-z biases large enough to corrupt derived cosmological parameters significantly. A metallicity shift of ~0.003dex in an old population, or contamination of any galaxy spectrum with ~0.2% AGN flux, is sufficient to induce a 10^-3 bias in photo-z. These results highlight the danger in extrapolating the behavior of bright galaxies to a fainter population, and the desirability of a spectroscopic training set that spans all of the characteristics of the photo-z targets, i.e. extending to the 25th mag or fainter galaxies that will be used in future surveys.