Extensive light profile fitting of galaxy-scale strong lenses
Florence Brault, Raphael Gavazzi

TL;DR
This paper evaluates a forward modeling approach to identify galaxy-scale strong lenses in ground-based images, highlighting the importance of accurate foreground light subtraction for effective lens detection and parameter recovery.
Contribution
It introduces a simulation-based method for lens detection using forward modeling and assesses its effectiveness on real survey data, emphasizing the impact of foreground subtraction.
Findings
High efficiency in recovering lens parameters under ideal conditions.
Foreground subtraction issues significantly bias lens detection.
Method shows promise for future wide-field surveys.
Abstract
We investigate the merits of a massive forward modeling of ground-based optical imaging as a diagnostic for the strong lensing nature of Early-Type Galaxies, in the light of which blurred and faint Einstein rings can hide. We simulate several thousand mock strong lenses under ground- and space-based conditions as arising from the deflection of an exponential disk by a foreground de Vaucouleurs light profile whose lensing potential is described by a Singular Isothermal Ellipsoid. We then fit for the lensed light distribution with sl_fit after having subtracted the foreground light emission off (ideal case) and also after having fitted the deflector's light with galfit. By setting thresholds in the output parameter space, we can decide the lens/not-a-lens status of each system. We finally apply our strategy to a sample of 517 lens candidates present in the CFHTLS data to test the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
