KiDS Strong Lensing

This is the Kapteyn/OmegaCEN homepage for the KiDS Strong Lensing project.

• Strongly-lensed QSO portal: Strongly Lensed QSOs with KiDS
• Aug14: Added KiDS-LOW-LRG-TWO package to support KiDS/BLF challenge
• May14: “No KiDS Lens No Glory” May 1-2, 2014 meeting at Kapteyn. Euclid SLWG lens finding specialists applied their strong lens finding tools to KiDS data:
  • meeting collaborative notes

We have prepared datapacks:

Each datapack contains:

• README.txt (general summary information)
• <datapackname>.pdf (more detailed information)
• per source cut-outs of coadd images and of associated weight images in the 4 KiDS filters u, g, r and i.
  • size 100pix x 100pix = 20” x 20”
• naming convention: <KiDS_tilename><radecOfSource><filtername><SLIDSIDofSourceList><r if random>__<size>.fits/weight.fits
  • SLID, SID are SourceList and Source IDentifiers in Astro-WISE system.
  • character r is appended if it are random cut-outs instead of centered on candidate sources
  • size is in pixel units (0.2”/pix)
• Units coadd images: mag=-2.5*log10(pixelvalue)
• units weight images: inverse variance images using same unit convention as coadd images (only background noise!).
• png thumbnails and cutouts.html (for browser view on cutouts)
• may2014meeting.py: python code used to generate datapack from Astro-WISE python prompt.

Content to be added next:

• color images

We have prepared a set of 5322 LRG candidates. Selection is aimed to get z<~0.4 luminous red galaxies. They are selected photometrically in 69 KiDS tiles (each approx. 1sq.deg.) The photometric selection is based on the BOSS LOWZ selection, adapted to KiDS:

• |c_perp| < 0.2
• r < 13.5 + c_par/0.3
• 16 < r < 19.6
• SGCLASS_r==2 (means extended object in r)

where magnitudes are in 10 and 2 arcsec diameter apertures and we have used the following auxiliary colors:

• cpar = 0.7(g - r) + 1.2[(r - i) - 0.18)]
• cperp = (r - i) - (g - r)/4.0 - 0.18

Aperture magnitude vs radius containing 50% of the light for example set.

We have prepared a set of 7409 LRG candidates. They are selected photometrically in 80 KiDS tiles (each approx. 1sq.deg.)
The photometric selection is based on the BOSS CMASS selection, adapted to KiDS:

• dperp > 0.55 (with dperp = (r-i) - (g-r)/8.0, and all magnitudes in 2arcsec apertures)
• i < 19.86+ 1.6(dperp - 0.8)
• 17.5 < i < 19.9
• r - i < 2
• SGCLASS_r==2 (means extended object in r)

We have prepared a testset of 5557 QSO candidates. Selection is aimed to get 0.5<z<2 QSOs. They are selected photometrically in 37 KiDS tiles (each approx. 1sq.deg.) The photometric selection is:

• SGCLASS_r==1 (means point source in r)
• 0.0<u-i<1.0
• r<22.0

where magnitudes are in 2 arcsec diameter apertures.

We have prepared a testset for 564 LRG candidates. They are selected photometrically in 5 KiDS tiles (each approx. 1sq.deg.)
The photometric selection is same as HIGHZ-LRG datpack (see above).

We have prepared a testset for 810 LRG candidates. Selection is same as KiDS-LOWZ-LRG (see above)

We have prepared a testset for 472 “random” KiDS locations. These are cut-outs centered on points uniformly selected in a square box of 1arcmin size around HIGHZ-LRG candidate locations in 5 KiDS tiles.

Konrad Kuijken has modeled the PSFs in u, g, r and i for one KiDS tile. Each at 5 locations in the FoV. Model is based on shapelet analysis. Hopefully they are representative enough in this early phase to test lens-finding tools on KiDS data.
See release note at KiDS-ESO-DR1 Consortium Portal for a typical distribution of seeing in KiDS data.

We can use 173 tiles (~173 sq.deg.) in the KiDS area that have completed coverage (i.e., u,g,r and i). This set is called KiDS-INT-DR3.

• KiDS-INT-DR3 synoptic table
• coming soon: KiDS-INT-DR3 four-band catalogs
• KiDS-INT-DR3 Consortium Portal for more details

• AI: JdJ/GVK: 140319: one coadd missing, KiDS-INT-DR3 sourcelists missing.

• KiDSLensFinding shared GoogleDoc
• Euclid SLWG wiki on redmine
• 1-2 May meeting Groningen page
• KiDS+VIKING Combined Catalogs
• may2014meeting.py Astro-WISE python script to make datapacks