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Title: Combining Dark Energy Survey Science Verification data with near-infrared data from the ESO VISTA Hemisphere Survey

Journal Article · · Monthly Notices of the Royal Astronomical Society

We present the combination of optical data from the Science Verification phase of the Dark Energy Survey (DES) with near-infrared (NIR) data from the European Southern Observatory VISTA Hemisphere Survey (VHS). The deep optical detections from DES are used to extract fluxes and associated errors from the shallower VHS data. Joint seven-band (grizYJK) photometric catalogues are produced in a single 3 sq-deg dedicated camera field centred at 02h26m-04d36m where the availability of ancillary multiwavelength photometry and spectroscopy allows us to test the data quality. Dual photometry increases the number of DES galaxies with measured VHS fluxes by a factor of similar to 4.5 relative to a simple catalogue level matching and results in a similar to 1.5 mag increase in the 80 per cent completeness limit of the NIR data. Almost 70 per cent of DES sources have useful NIR flux measurements in this initial catalogue. Photometric redshifts are estimated for a subset of galaxies with spectroscopic redshifts and initial results, although currently limited by small number statistics, indicate that the VHS data can help reduce the photometric redshift scatter at both z < 0.5 and z > 1. We present example DES VHS colour selection criteria for high-redshift luminous red galaxies (LRGs) at z similar to 0.7 as well as luminous quasars. Using spectroscopic observations in this field we show that the additional VHS fluxes enable a cleaner selection of both populations with <10 per cent contamination from galactic stars in the case of spectroscopically confirmed quasars and <0.5 per cent contamination from galactic stars in the case of spectroscopically confirmed LRGs. The combined DES+VHS data set, which will eventually cover almost 5000 sq-deg, will therefore enable a range of new science and be ideally suited for target selection for future wide-field spectroscopic surveys.

Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC); National Science Foundation (NSF)
DOE Contract Number:
AC02-06CH11357
OSTI ID:
1342907
Journal Information:
Monthly Notices of the Royal Astronomical Society, Vol. 446, Issue 3; ISSN 0035-8711
Publisher:
Royal Astronomical Society
Country of Publication:
United States
Language:
English

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Cited By (18)

Galaxy formation and evolution science in the era of the Large Synoptic Survey Telescope journal June 2019
SDSS-IV eBOSS emission-line galaxy pilot survey journal August 2016
Photometric redshifts for the Kilo-Degree Survey: Machine-learning analysis with artificial neural networks journal August 2018
KiDS+VIKING-450: A new combined optical and near-infrared dataset for cosmology and astrophysics journal November 2019
The dark Energy Camera journal October 2015
The Dark Energy Survey: more than dark energy – an overview journal March 2016
The PAU survey: star–galaxy classification with multi narrow-band data journal November 2018
Candidate massive galaxies at z  ∼ 4 in the Dark Energy Survey journal December 2018
Three new VHS–DES quasars at 6.7 < z < 6.9 and emission line properties at z > 6.5 journal May 2019
A new sample of southern radio galaxies: host-galaxy masses and star-formation rates journal August 2019
Brown dwarf census with the Dark Energy Survey year 3 data and the thin disc scale height of early L types journal September 2019
Quasar Accretion Disk Sizes from Continuum Reverberation Mapping from the Dark Energy Survey journal July 2018
Quasar Accretion Disk Sizes from Continuum Reverberation Mapping from the Dark Energy Survey text January 2018
KiDS+VIKING-450: A new combined optical and near-infrared dataset for cosmology and astrophysics text January 2019
The Dark Energy Survey: more than dark energy - an overview text January 2016
Photometric redshifts for the Kilo-Degree Survey. Machine-learning analysis with artificial neural networks text January 2017
The PAU Survey: star-galaxy classification with multi narrow-band data text January 2018
A new sample of southern radio galaxies: Host galaxy masses and star-formation rates text January 2019

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