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The PAU Survey: narrow-band photometric redshifts using Gaussian processes

Soo, JYH; Joachimi, B; Eriksen, M; Siudek, M; Alarcon, A; Cabayol, L; Carretero, J; ... Tallada-Crespí, P; + view all (2021) The PAU Survey: narrow-band photometric redshifts using Gaussian processes. Monthly Notices of the Royal Astronomical Society , 503 (3) pp. 4118-4135. 10.1093/mnras/stab711. Green open access

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Abstract

We study the performance of the hybrid template machine learning photometric redshift (photo-z) algorithm DELIGHT, which uses Gaussian processes, on a subset of the early data release of the Physics of the Accelerating Universe Survey (PAUS). We calibrate the fluxes of the 40 PAUS narrow bands with six broad-band fluxes (uBVriz) in the Cosmic Evolution Survey (COSMOS) field using three different methods, including a new method that utilizes the correlation between the apparent size and overall flux of the galaxy. We use a rich set of empirically derived galaxy spectral templates as guides to train the Gaussian process, and we show that our results are competitive with other standard photometric redshift algorithms. DELIGHT achieves a photo-z 68th percentile error of σ68 = 0.0081(1 + z) without any quality cut for galaxies with iauto < 22.5 as compared to 0.0089(1 + z) and 0.0202(1 + z) for the BPZ and ANNZ2 codes, respectively. DELIGHT is also shown to produce more accurate probability distribution functions for individual redshift estimates than BPZ and ANNZ2. Common photo-z outliers of DELIGHT and BCNZ2 (previously applied to PAUS) are found to be primarily caused by outliers in the narrow-band fluxes, with a small number of cases potentially indicating spectroscopic redshift failures in the reference sample. In the process, we introduce performance metrics derived from the results of BCNZ2 and DELIGHT, allowing us to achieve a photo-z quality of σ68 < 0.0035(1 + z) at a magnitude of iauto < 22.5 while keeping 50 per cent objects of the galaxy sample.

Type: Article
Title: The PAU Survey: narrow-band photometric redshifts using Gaussian processes
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/mnras/stab711
Publisher version: http://dx.doi.org/10.1093/mnras/stab711
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: methods: numerical, methods: statistical, galaxies: distances and redshifts
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy
URI: https://discovery.ucl.ac.uk/id/eprint/10125245
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