Gatti, M;
Vielzeuf, P;
Davis, C;
Cawthon, R;
Rau, MM;
DeRose, J;
De Vicente, J;
... Wolf, RC; + view all
(2018)
Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization.
Monthly Notices of the Royal Astronomical Society (MNRAS)
, 477
(2)
pp. 1651-1669.
10.1093/mnras/sty466.
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Abstract
We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing source galaxies from the Dark Energy Survey Year 1 sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We apply the method to two photo-z codes run in our simulated data: Bayesian Photometric Redshift and Directional Neighbourhood Fitting. We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering versus photo-zs. The systematic uncertainty in the mean redshift bias of the source galaxy sample is Δz ≲ 0.02, though the precise value depends on the redshift bin under consideration. We discuss possible ways to mitigate the impact of our dominant systematics in future analyses.
| Type: | Article |
|---|---|
| Title: | Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/mnras/sty466 |
| Publisher version: | https://doi.org/10.1093/mnras/sty466 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Science & Technology, Physical Sciences, Astronomy & Astrophysics, galaxies: distances and redshifts, cosmology: observations, DIGITAL SKY SURVEY, PHOTOMETRIC GALAXY SAMPLES, SCIENCE VERIFICATION DATA, COSMIC SHEAR, RANDOM FORESTS, DATA RELEASE, DEEP FIELD, DISTRIBUTIONS, MAGNIFICATION, LUMINOSITY |
| 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-pp.ucl.ac.uk/id/eprint/10053764 |
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