Improved Photometric Redshifts via Enhanced Estimates of System Response, Galaxy Templates, and Magnitude Priors

TL;DR

This paper enhances photometric redshift accuracy in the Deep Lens Survey by refining system response models, galaxy templates, and priors, resulting in significantly reduced scatter and bias in photo-z estimates.

Contribution

It introduces improved calibration methods and models for system response, galaxy templates, and priors, leading to more accurate photometric redshift estimates.

Findings

20% reduction in photo-z scatter

Bias reduced by more than a factor of two

Provides system response function for other surveys

Abstract

Wide, deep photometric surveys require robust photometric redshift estimates (photo-z's) for studies of large-scale structure. These estimates depend critically on accurate photometry. We describe the improvements to the photometric calibration and the photo-z estimates in the Deep Lens Survey (DLS) from correcting three of the inputs to the photo-z calculation: the system response as a function of wavelength, the spectral energy distribution templates, and template prior probabilities as a function of magnitude. We model the system response with a physical model of the MOSAIC camera's CCD, which corrects a 0.1 magnitude discrepancy in the colours of type M2 and later stars relative to the SDSS z-band photometry. We provide our estimated z-band response function for the use of other surveys that used MOSAIC before its recent detector upgrade. The improved throughput curve, template set, and Bayesian prior lead to a 20 per cent reduction in photo-z scatter and a reduction of the bias by a factor of more than two. This paper serves as both a photo-z data release description for DLS and a guide for testing the quality of photometry and resulting photo-z's generally.