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Title: Photometric redshift analysis in the Dark Energy Survey Science Verification data

Journal Article · · Monthly Notices of the Royal Astronomical Society

In this study, we present results from a study of the photometric redshift performance of the Dark Energy Survey (DES), using the early data from a Science Verification period of observations in late 2012 and early 2013 that provided science-quality images for almost 200 sq. deg. at the nominal depth of the survey. We assess the photometric redshift (photo-z) performance using about 15 000 galaxies with spectroscopic redshifts available from other surveys. These galaxies are used, in different configurations, as a calibration sample, and photo-z's are obtained and studied using most of the existing photo-z codes. A weighting method in a multidimensional colour–magnitude space is applied to the spectroscopic sample in order to evaluate the photo-z performance with sets that mimic the full DES photometric sample, which is on average significantly deeper than the calibration sample due to the limited depth of spectroscopic surveys. In addition, empirical photo-z methods using, for instance, artificial neural networks or random forests, yield the best performance in the tests, achieving core photo-z resolutions σ68 ~ 0.08. Moreover, the results from most of the codes, including template-fitting methods, comfortably meet the DES requirements on photo-z performance, therefore, providing an excellent precedent for future DES data sets.

Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP)
Contributing Organization:
DES Collaboration
Grant/Contract Number:
AC02-07CH11359
OSTI ID:
1374719
Report Number(s):
FERMILAB-PUB-14-260-AE; arXiv:1406.4407; 1300797; TRN: US1702472
Journal Information:
Monthly Notices of the Royal Astronomical Society, Vol. 445, Issue 2; ISSN 0035-8711
Publisher:
Royal Astronomical SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 140 works
Citation information provided by
Web of Science

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PHAT: PHoto-z Accuracy Testing text January 2010
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Spectroscopic Target Selection in the Sloan Digital Sky Survey: The Main Galaxy Sample text January 2002
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Baryons, neutrinos, feedback and weak gravitational lensing journal April 2015
Cross-correlation of gravitational lensing from DES Science Verification data with SPT and Planck lensing journal March 2016
WISE × SuperCOSMOS PHOTOMETRIC REDSHIFT CATALOG: 20 MILLION GALAXIES OVER 3 π STERADIANS journal July 2016
The Dark Energy Survey: more than dark energy – an overview journal March 2016
Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data journal March 2018
Cosmic distance determination from photometric redshift samples using BAO peaks only journal June 2019
Photometric Redshifts and Stellar Masses for Galaxies from the DESI Legacy Imaging Surveys journal May 2019
A cooperative approach among methods for photometric redshifts estimation: an application to KiDS data journal December 2016
CMB lensing tomography with the DES Science Verification galaxies journal January 2016
No galaxy left behind: accurate measurements with the faintest objects in the Dark Energy Survey journal January 2016
A new sample of southern radio galaxies: host-galaxy masses and star-formation rates journal August 2019
Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data journal August 2016
ANNz2: Photometric Redshift and Probability Distribution Function Estimation using Machine Learning journal August 2016
Dark Energy Survey Year 1 Results: Calibration of redMaGiC redshift distributions in DES and SDSS from cross-correlations text January 2018
Baryons, Neutrinos, Feedback and Weak Gravitational Lensing text January 2014
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ANNz2 - photometric redshift and probability distribution function estimation using machine learning text January 2015
redMaGiC: Selecting Luminous Red Galaxies from the DES Science Verification Data text January 2015
CMB lensing tomography with the DES Science Verification galaxies text January 2015
Cross-correlation of gravitational lensing from DES Science Verification data with SPT and Planck lensing text January 2015
The Dark Energy Survey: more than dark energy - an overview text January 2016
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A cooperative approach among methods for photometric redshifts estimation: an application to KiDS data text January 2016
Morpho-z: improving photometric redshifts with galaxy morphology text January 2017
Cross-Correlation Redshift Calibration Without Spectroscopic Calibration Samples in DES Science Verification Data text January 2017
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Galaxies in X-ray Selected Clusters and Groups in Dark Energy Survey Data II: Hierarchical Bayesian Modeling of the Red-Sequence Galaxy Luminosity Function preprint January 2017
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