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Title:
A Computer Vision Approach to Identify Einstein Rings and Arcs
Authors:
Lee, Chien-Hsiu
Affiliation:
AA(Subaru Telescope, National Astronomical Observatory of Japan, 650 North Aohoku Place, Hilo, HI 96720, USA)
Publication:
Publications of the Astronomical Society of Australia, Volume 34, id.e014 6 pp. (PASA Homepage)
Publication Date:
03/2017
Origin:
PASA
Astronomy Keywords:
galaxies: high-redshift, gravitational lensing: strong, methods: data analysis, surveys, techniques: image processing
Abstract Copyright:
2017: Astronomical Society of Australia
DOI:
10.1017/pasa.2017.7
Bibliographic Code:
2017PASA...34...14L

Abstract

Einstein rings are rare gems of strong lensing phenomena; the ring images can be used to probe the underlying lens gravitational potential at every position angles, tightly constraining the lens mass profile. In addition, the magnified images also enable us to probe high-z galaxies with enhanced resolution and signal-to-noise ratios. However, only a handful of Einstein rings have been reported, either from serendipitous discoveries or or visual inspections of hundred thousands of massive galaxies or galaxy clusters. In the era of large sky surveys, an automated approach to identify ring pattern in the big data to come is in high demand. Here, we present an Einstein ring recognition approach based on computer vision techniques. The workhorse is the circle Hough transform that recognise circular patterns or arcs in the images. We propose a two-tier approach by first pre-selecting massive galaxies associated with multiple blue objects as possible lens, than use Hough transform to identify circular pattern. As a proof-of-concept, we apply our approach to SDSS, with a high completeness, albeit with low purity. We also apply our approach to other lenses in DES, HSC-SSP, and UltraVISTA survey, illustrating the versatility of our approach.
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