The PCA Lens-Finder: application to CFHTLS

TL;DR

This paper introduces a new method for detecting galaxy-scale strong lensing systems in CFHTLS data using PCA and clustering algorithms, resulting in 109 new lens candidates and a comprehensive lens catalog.

Contribution

The paper presents a novel lens-finding technique combining PCA and clustering, improving detection efficiency and completeness in CFHTLS wide-field data.

Findings

Identified 1098 lens candidates, with 109 confirmed after visual inspection.

Estimated the sample completeness to be independent of key lens properties.

Total CFHTLS lens count now 678, with implications for future wide surveys.

Abstract

We present the results of a new search for galaxy-scale strong lensing systems in CFHTLS Wide. Our lens-finding technique involves a preselection of potential lens galaxies, applying simple cuts in size and magnitude. We then perform a Principal Component Analysis of the galaxy images, ensuring a clean removal of the light profile. Lensed features are searched for in the residual images using the clustering topometric algorithm DBSCAN. We find 1098 lens candidates that we inspect visually, leading to a cleaned sample of 109 new lens candidates. Using realistic image simulations we estimate the completeness of our sample and show that it is independent of source surface brightness, Einstein ring size (image separation) or lens redshift. We compare the properties of our sample to previous lens searches in CFHTLS. Including the present search, the total number of lenses found in CFHTLS amounts to 678, which corresponds to ~4 lenses per square degree down to i=24.8. This is equivalent to ~ 60.000 lenses in total in a survey as wide as Euclid, but at the CFHTLS resolution and depth.