TY - JOUR
T1 - Chitah
T2 - STRONG-GRAVITATIONAL-LENS HUNTER in IMAGING SURVEYS
AU - Chan, James H.H.
AU - Suyu, Sherry H.
AU - Chiueh, Tzihong
AU - More, Anupreeta
AU - Marshall, Philip J.
AU - Coupon, Jean
AU - Oguri, Masamune
AU - Price, Paul
N1 - Publisher Copyright:
© 2015. The American Astronomical Society. All rights reserved..
PY - 2015/7/10
Y1 - 2015/7/10
N2 - Strong gravitationally lensed quasars provide powerful means to study galaxy evolution and cosmology. Current and upcoming imaging surveys will contain thousands of new lensed quasars, augmenting the existing sample by at least two orders of magnitude. To find such lens systems, we built a robot, Chitah, that hunts for lensed quasars by modeling the configuration of the multiple quasar images. Specifically, given an image of an object that might be a lensed quasar, Chitah first disentangles the light from the supposed lens galaxy and the light from the multiple quasar images based on color information. A simple rule is designed to categorize the given object as a potential four-image (quad) or two-image (double) lensed quasar system. The configuration of the identified quasar images is subsequently modeled to classify whether the object is a lensed quasar system. We test the performance of Chitah using simulated lens systems based on the Canada-France-Hawaii Telescope Legacy Survey. For bright quads with large image separations (with Einstein radius ) simulated using Gaussian point-spread functions, a high true-positive rate (TPR) of and a low false-positive rate of show that this is a promising approach to search for new lens systems. We obtain high TPR for lens systems with , so the performance of Chitah is set by the seeing. We further feed a known gravitational lens system, COSMOS 5921+0638, to Chitah, and demonstrate that Chitah is able to classify this real gravitational lens system successfully. Our newly built Chitah is omnivorous and can hunt in any ground-based imaging surveys.
AB - Strong gravitationally lensed quasars provide powerful means to study galaxy evolution and cosmology. Current and upcoming imaging surveys will contain thousands of new lensed quasars, augmenting the existing sample by at least two orders of magnitude. To find such lens systems, we built a robot, Chitah, that hunts for lensed quasars by modeling the configuration of the multiple quasar images. Specifically, given an image of an object that might be a lensed quasar, Chitah first disentangles the light from the supposed lens galaxy and the light from the multiple quasar images based on color information. A simple rule is designed to categorize the given object as a potential four-image (quad) or two-image (double) lensed quasar system. The configuration of the identified quasar images is subsequently modeled to classify whether the object is a lensed quasar system. We test the performance of Chitah using simulated lens systems based on the Canada-France-Hawaii Telescope Legacy Survey. For bright quads with large image separations (with Einstein radius ) simulated using Gaussian point-spread functions, a high true-positive rate (TPR) of and a low false-positive rate of show that this is a promising approach to search for new lens systems. We obtain high TPR for lens systems with , so the performance of Chitah is set by the seeing. We further feed a known gravitational lens system, COSMOS 5921+0638, to Chitah, and demonstrate that Chitah is able to classify this real gravitational lens system successfully. Our newly built Chitah is omnivorous and can hunt in any ground-based imaging surveys.
KW - gravitational lensing: strong
KW - methods: data analysis
KW - quasars: individual (anguita)
UR - http://www.scopus.com/inward/record.url?scp=84937002900&partnerID=8YFLogxK
U2 - 10.1088/0004-637X/807/2/138
DO - 10.1088/0004-637X/807/2/138
M3 - Article
AN - SCOPUS:84937002900
SN - 0004-637X
VL - 807
JO - Astrophysical Journal
JF - Astrophysical Journal
IS - 2
M1 - 138
ER -