The MUSE Hubble Ultra Deep Field Survey: III. Testing photometric redshifts to 30th magnitude

TL;DR

This study evaluates the accuracy of photometric redshifts for extremely faint galaxies in the Hubble Ultra Deep Field, revealing systematic biases and the impact of additional photometry on redshift estimation.

Contribution

It provides a comprehensive comparison of photometric redshift codes at unprecedented depths and highlights biases and challenges in associating spectra with photometric objects.

Findings

Photometric redshifts are accurate within bias |Dzn|<0.05 down to magnitude 30.

Systematic biases exist: underestimation at 0.4<z<1.5 and overestimation at z>3.

Adding ground-based and IRAC photometry can worsen redshift estimates for faint galaxies.

Abstract

We tested the performance of photometric redshifts for galaxies in the Hubble Ultra Deep field down to 30th magnitude. We compared photometric redshift estimates from three spectral fitting codes from the literature (EAZY, BPZ and BEAGLE) to high quality redshifts for 1227 galaxies from the MUSE integral field spectrograph. All these codes can return photometric redshifts with bias |Dzn|=|z-z_phot|/(1+z)<0.05 down to F775W=30 and spectroscopic incompleteness is unlikely to strongly modify this statement. We have, however, identified clear systematic biases in the determination of photometric redshifts: in the 0.4<z<1.5 range, photometric redshifts are systematically biased low by as much as Dzn=-0.04 in the median, and at z>3 they are systematically biased high by up to Dzn = 0.05, an offset that can in part be explained by adjusting the amount of intergalactic absorption applied. In agreement with previous studies we find little difference in the performance of the different codes, but in contrast to those we find that adding extensive ground-based and IRAC photometry actually can worsen photo-z performance for faint galaxies. We find an outlier fraction, defined through |Dzn|>0.15, of 8% for BPZ and 10% for EAZY and BEAGLE, and show explicitly that this is a strong function of magnitude. While this outlier fraction is high relative to numbers presented in the literature for brighter galaxies, they are very comparable to literature results when the depth of the data is taken into account. Finally, we demonstrate that while a redshift might be of high confidence, the association of a spectrum to the photometric object can be very uncertain and lead to a contamination of a few percent in spectroscopic training samples that do not show up as catastrophic outliers, a problem that must be tackled in order to have sufficiently accurate photometric redshifts for future cosmological surveys.