Survey of Gravitationally-lensed Objects in HSC Imaging (SuGOHI). I. Automatic search for galaxy-scale strong lenses
arXiv:1704.01585 · doi:10.1093/pasj/psx062
Abstract
The Hyper Suprime-Cam Subaru Strategic Program (HSC SSP) is an excellent survey for the search for strong lenses, thanks to its area, image quality and depth. We use three different methods to look for lenses among 43,000 luminous red galaxies from the Baryon Oscillation Spectroscopic Survey (BOSS) sample with photometry from the S16A internal data release of the HSC SSP. The first method is a newly developed algorithm, named YATTALENS, which looks for arc-like features around massive galaxies and then estimates the likelihood of an object being a lens by performing a lens model fit. The second method, CHITAH, is a modeling-based algorithm originally developed to look for lensed quasars. The third method makes use of spectroscopic data to look for emission lines from objects at a different redshift from that of the main galaxy. We find 15 definite lenses, 36 highly probable lenses and 282 possible lenses. Among the three methods, YATTALENS, which was developed specifically for this problem, performs best in terms of both completeness and purity. Nevertheless five highly probable lenses were missed by YATTALENS but found by the other two methods, indicating that the three methods are highly complementary. Based on these numbers we expect to find 300 definite or probable lenses by the end of the HSC SSP.
Published on PASJ. 17 pages, 8 figures. Image quality of Figures 6 and 7 has been degraded due to arXiv file size limit. Full quality versions can be found at http://member.ipmu.jp/alessandro.sonnenfeld/sugohi1_candidates.html
References in corpus (20)
- First Data Release of the Hyper Suprime-Cam Subaru Strategic Program
- The Hyper Suprime-Cam Software Pipeline
- H0LiCOW V. New COSMOGRAIL time delays of HE0435-1223: to 3.8% precision from strong lensing in a flat CDM model
- The Sloan Lens ACS Survey. V. The Full ACS Strong-Lens Sample
- H0LiCOW IV. Lens mass model of HE 0435-1223 and blind measurement of its time-delay distance for cosmology
- Great Optically Luminous Dropout Research Using Subaru HSC (GOLDRUSH). I. UV Luminosity Functions at Derived with the Half-Million Dropouts on the 100 deg Sky
- The Sloan Lens ACS Survey. VI: Discovery and analysis of a double Einstein ring
- The CFHTLS Strong Lensing Legacy Survey: I. Survey overview and T0002 release sample
- The SL2S Galaxy-scale Lens Sample. V. Dark Matter Halos and Stellar IMF of Massive Early-type Galaxies out to Redshift 0.8
- The SL2S Galaxy-scale Lens Sample. II. Cosmic evolution of dark and luminous mass in early-type galaxies
- RingFinder: automated detection of galaxy-scale gravitational lenses in ground-based multi-filter imaging data
- The Sloan Lens ACS Survey. XII. Extending Strong Lensing to Lower Masses
- The BOSS Emission-Line Lens Survey. IV. : Smooth Lens Models for the BELLS GALLERY Sample
- A calibration of the stellar mass fundamental plane at z ~ 0.5 using the micro-lensing induced flux ratio anomalies of macro-lensed quasars
- The role of luminous substructure in the gravitational lens system MG 2016+112
- Red nuggets grow inside-out: evidence from gravitational lensing
- CHITAH: Strong-gravitational-lens hunter in imaging surveys
- Can one determine cosmological parameters from multi-plane strong lens systems?
- Probing a massive radio galaxy with gravitational lensing
- A Spectroscopically Confirmed Double Source Plane Lens System in the Hyper Suprime-Cam Subaru Strategic Program
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