The third data release of the Kilo-Degree Survey and associated data products

Abstract

Context. The Kilo-Degree Survey (KiDS) is an ongoing optical wide-field imaging survey with the OmegaCAM camera at the VLT Survey Telescope. It aims to image 1500 square degrees in four filters (ugri). The core science driver is mapping the large-scale matter distribution in the Universe, using weak lensing shear and photometric redshift measurements. Further science cases include galaxy evolution, Milky Way structure, detection of high-redshift clusters, and finding rare sources such as strong lenses and quasars. Aims. Here we present the third public data release and several associated data products, adding further area, homogenized photometric calibration, photometric redshifts and weak lensing shear measurements to the first two releases. Methods. A dedicated pipeline embedded in the Astro-WISE information system is used for the production of the main release. Modifications with respect to earlier releases are described in detail. Photometric redshifts have been derived using both Bayesian template fitting, and machine-learning techniques. For the weak lensing measurements, optimized procedures based on the THELI data reduction and lensfit shear measurement packages are used. Results. In this third data release an additional 292 new survey tiles (≈300 deg 2 ) stacked ugri images are made available, accompanied by weight maps, masks, and source lists. The multi-band catalogue, including homogenized photometry and photometric redshifts, covers the combined DR1, DR2 and DR3 footprint of 440 survey tiles (44 deg 2 ). Limiting magnitudes are typically 24.3, 25.1, 24.9, 23.8 (5σ in a 2 aperture) in ugri, respectively, and the typical r-band PSF size is less than 0.7 . The photometric homogenization scheme ensures accurate colours and an absolute calibration stable to ≈2% for gri and ≈3% in u. Separately released for the combined area of all KiDS releases to date are a weak lensing shear catalogue and photometric redshifts based on two different machine-learning techniques.

The impact of baryonic physics and massive neutrinos on weak lensing peak statistics

“…The WL peak statistics were determined from synthetic aperture mass S/N maps calculated from shape noise realisations of simulated WL data fields. Calculation of the convergence assumed different source redshift distributions from Chang et al (2013) for LSST and from Hildebrandt et al (2017) and de Jong et al (2017) for KiDS. We use source number densities of 9 and 30 gal/arcmin 2 , roughly corresponding to the KiDS data and the expectation for LSST and Euclid.…”

LinKS: discovering galaxy-scale strong lenses in the Kilo-Degree Survey using convolutional neural networks

“…The best seeing observations are reserved for the r-band, with the survey exhibiting median point spread function (PSF) full-width at half-maximum (FWHM) values of 1.0, 0.8, 0.65 and 0.85 arcseconds in the u−, g−, r−, and i−bands respectively. The survey depths per-band, as determined by the 5 − σ limiting magnitudes within a 2 arcsecond circular aperture, are 24.2, 25.1, 25.0, 23.7 in the u−, g−, r−, and i−bands respectively (de Jong et al 2015(de Jong et al , 2017.…”

The COS Absorption Survey of Baryon Harbors: The Galaxy Database and Cross-correlation Analysis of O vi Systems∗

“…We assembled our photometric dataset for SED fitting by cross-matching all galaxies in our spectroscopic database having redshift quality scores Z Q ≥ 3 with several public survey catalogs: SDSS DR12 (Alam et al 2015, ugriz coverage of all fields except PHL1377), the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS; Hudelot et al 2012, ugriz coverage of the PHL1377 field), the Wide-field Infrared Survey Explorer all sky survey (Cutri & et al 2013, 3.4, 4.6, 12, and 22 µm bands for all fields), BASS (Zou et al 2017b,a), UKIDSS (Warren et al 2007;Lawrence et al 2007), KiDS (de Jong et al 2017), DECALS (Dey et al 2018), MzLS (Dey et al 2018), and Pan-STARRS (Flewelling et al 2016;Chambers et al 2016).…”