Back to Search Start Over

Survey of Gravitationally-lensed Objects in HSC Imaging (SuGOHI). I. Automatic search for galaxy-scale strong lenses.

Authors :
Alessandro SONNENFELD
CHAN, James H. H.
Yiping SHU
MORE, Anupreeta
Masamune OGURI
SUYU, Sherry H.
WONG, Kenneth C.
Chien-Hsiu LEE
COUPON, Jean
Atsunori YONEHARA
BOLTON, Adam S.
JAELANI, Anton T.
Masayuki TANAKA
Satoshi MIYAZAKI
Yutaka KOMIYAMA
Source :
Publications of the Astronomical Society of Japan; Jan2018, Vol. 70 Issue Supp1, p1-N.PAG, 19p
Publication Year :
2018

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00046264
Volume :
70
Issue :
Supp1
Database :
Complementary Index
Journal :
Publications of the Astronomical Society of Japan
Publication Type :
Academic Journal
Accession number :
127785988
Full Text :
https://doi.org/10.1093/pasj/psx062