CHITAH: Strong-gravitational-lens hunter in imaging surveys

TL;DR

CHITAH is an automated tool that identifies strong gravitational lens systems in imaging surveys by modeling quasar image configurations and separating lens and quasar light, showing high accuracy in simulations and real data.

Contribution

This paper introduces CHITAH, a novel automated method for detecting gravitationally lensed quasars in large imaging surveys, based on configuration modeling and color-based light separation.

Findings

High true-positive rate (~90%) for bright quads with large separations

Effective classification of real gravitational lens system COSMOS 5921+0638

Performance depends on seeing conditions, with good results for separations >0.5"

Abstract

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 $r_{\rm ein}>1.1"$) simulated using Gaussian point-spread functions, a high true-positive rate (TPR) of $\sim$90% and a low false-positive rate of $\sim$$3\%$ show that this is a promising approach to search for new lens systems. We obtain high TPR for lens systems with $r_{\rm ein}\gtrsim0.5"$, 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.