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تسجيل مستخدم جديدThe Kilo-Degree Survey
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The Kilo Degree Survey (KiDS) is a 1500 square degree optical imaging survey with the recently commissioned OmegaCAM wide-field imager on the VLT Survey Telescope (VST). A suite of data products will be delivered to the European Southern Observatory (ESO) and the community by the KiDS survey team. Spread over Europe, the KiDS team uses Astro-WISE to collaborate efficiently and pool hardware resources. In Astro-WISE the team shares, calibrates and archives all survey data. The data-centric architectural design realizes a dynamic live archive in which new KiDS survey products of improved quality can be shared with the team and eventually the full astronomical community in a flexible and controllable manner.
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The Kilo-Degree Survey (KiDS) is an optical wide-field imaging survey carried out with the VLT Survey Telescope and the OmegaCAM camera. KiDS will image 1500 square degrees in four filters (ugri), and together with its near-infrared counterpart VIKIN
G will produce deep photometry in nine bands. Designed for weak lensing shape and photometric redshift measurements, the core science driver of the survey is mapping the large-scale matter distribution in the Universe back to a redshift of ~0.5. Secondary science cases are manifold, covering topics such as galaxy evolution, Milky Way structure, and the detection of high-redshift clusters and quasars. KiDS is an ESO Public Survey and dedicated to serving the astronomical community with high-quality data products derived from the survey data, as well as with calibration data. Public data releases will be made on a yearly basis, the first two of which are presented here. For a total of 148 survey tiles (~160 sq.deg.) astrometrically and photometrically calibrated, coadded ugri images have been released, accompanied by weight maps, masks, source lists, and a multi-band source catalog. A dedicated pipeline and data management system based on the Astro-WISE software system, combined with newly developed masking and source classification software, is used for the data production of the data products described here. The achieved data quality and early science projects based on the data products in the first two data releases are reviewed in order to validate the survey data. Early scientific results include the detection of nine high-z QSOs, fifteen candidate strong gravitational lenses, high-quality photometric redshifts and galaxy structural parameters for hundreds of thousands of galaxies. (Abridged)
In this paper, we present the tools used to search for galaxy clusters in the Kilo Degree Survey (KiDS), and our first results. The cluster detection is based on an implementation of the optimal filtering technique that enables us to identify cluster
s as over-densities in the distribution of galaxies using their positions on the sky, magnitudes, and photometric redshifts. The contamination and completeness of the cluster catalog are derived using mock catalogs based on the data themselves. The optimal signal to noise threshold for the cluster detection is obtained by randomizing the galaxy positions and selecting the value that produces a contamination of less than 20%. Starting from a subset of clusters detected with high significance at low redshifts, we shift them to higher redshifts to estimate the completeness as a function of redshift: the average completeness is ~ 85%. An estimate of the mass of the clusters is derived using the richness as a proxy. We obtained 1858 candidate clusters with redshift 0 < z_c < 0.7 and mass 13.5 < log(M500/Msun) < 15 in an area of 114 sq. degrees (KiDS ESO-DR2). A comparison with publicly available Sloan Digital Sky Survey (SDSS)-based cluster catalogs shows that we match more than 50% of the clusters (77% in the case of the redMaPPer catalog). We also cross-matched our cluster catalog with the Abell clusters, and clusters found by XMM and in the Planck-SZ survey; however, only a small number of them lie inside the KiDS area currently available.
We present the results of our first year of quasar search in the on-going ESO public Kilo Degree Survey (KiDS) and VISTA Kilo-Degree Infrared Galaxy (VIKING) surveys. These surveys are among the deeper wide-field surveys that can be used to uncovered
large numbers of z~6 quasars. This allows us to probe a more common population of z~6 quasars that is fainter than the well-studied quasars from the main Sloan Digital Sky Survey. From this first set of combined survey catalogues covering ~250 deg^2 we selected point sources down to Z_AB=22 that had a very red i-Z (i-Z>2.2) colour. After follow-up imaging and spectroscopy, we discovered four new quasars in the redshift range 5.8<z<6.0. The absolute magnitudes at a rest-frame wavelength of 1450 A are between -26.6 < M_1450 < -24.4, confirming that we can find quasars fainter than M^*, which at z=6 has been estimated to be between M^*=-25.1 and M^*=-27.6. The discovery of 4 quasars in 250 deg^2 of survey data is consistent with predictions based on the z~6 quasar luminosity function. We discuss various ways to push the candidate selection to fainter magnitudes and we expect to find about 30 new quasars down to an absolute magnitude of M_1450=-24. Studying this homogeneously selected faint quasar population will be important to gain insight into the onset of the co-evolution of the black holes and their stellar hosts.
The search for minor bodies in the solar system promises insights into its formation history. Wide imaging surveys offer the opportunity to serendipitously discover and identify these traces of planetary formation and evolution. We aim to present a m
ethod to acquire position, photometry, and proper motion measurements of solar system objects in surveys using dithered image sequences. The application of this method on the Kilo-Degree Survey is demonstrated. Optical images of 346 square degree fields of the sky are searched in up to four filters using the AstrOmatic software suite to reduce the pixel to catalog data. The solar system objects within the acquired sources are selected based on a set of criteria depending on their number of observation, motion, and size. The Virtual Observatory SkyBoT tool is used to identify known objects. We observed 20,221 SSO candidates, with an estimated false-positive content of less than 0.05%. Of these SSO candidates, 53.4% are identified by SkyBoT. KiDS can detect previously unknown SSOs because of its depth and coverage at high ecliptic latitude, including parts of the Southern Hemisphere. Thus we expect the large fraction of the 46.6% of unidentified objects to be truly new SSOs. Our method is applicable to a variety of dithered surveys such as DES, LSST, and Euclid. It offers a quick and easy-to-implement search for solar system objects. SkyBoT can then be used to estimate the completeness of the recovered sample.
We present a machine-learning photometric redshift analysis of the Kilo-Degree Survey Data Release 3, using two neural-network based techniques: ANNz2 and MLPQNA. Despite limited coverage of spectroscopic training sets, these ML codes provide photo-z
s of quality comparable to, if not better than, those from the BPZ code, at least up to zphot<0.9 and r<23.5. At the bright end of r<20, where very complete spectroscopic data overlapping with KiDS are available, the performance of the ML photo-zs clearly surpasses that of BPZ, currently the primary photo-z method for KiDS. Using the Galaxy And Mass Assembly (GAMA) spectroscopic survey as calibration, we furthermore study how photo-zs improve for bright sources when photometric parameters additional to magnitudes are included in the photo-z derivation, as well as when VIKING and WISE infrared bands are added. While the fiducial four-band ugri setup gives a photo-z bias $delta z=-2e-4$ and scatter $sigma_z<0.022$ at mean z = 0.23, combining magnitudes, colours, and galaxy sizes reduces the scatter by ~7% and the bias by an order of magnitude. Once the ugri and IR magnitudes are joined into 12-band photometry spanning up to 12 $mu$, the scatter decreases by more than 10% over the fiducial case. Finally, using the 12 bands together with optical colours and linear sizes gives $delta z<4e-5$ and $sigma_z<0.019$. This paper also serves as a reference for two public photo-z catalogues accompanying KiDS DR3, both obtained using the ANNz2 code. The first one, of general purpose, includes all the 39 million KiDS sources with four-band ugri measurements in DR3. The second dataset, optimized for low-redshift studies such as galaxy-galaxy lensing, is limited to r<20, and provides photo-zs of much better quality than in the full-depth case thanks to incorporating optical magnitudes, colours, and sizes in the GAMA-calibrated photo-z derivation.
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