http://arxiv.org/abs/1411.1265
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 consistency of our selection approach. The efficiency of the fast modeling method at recovering the main lens parameters like Einstein radius, total magnification or total lensed flux, is quite comparable under CFHT and HST conditions when the deflector is perfectly subtracted off (only possible in simulations), fostering a sharp distinction between the good and the bad candidates. Conversely, for a more realistic subtraction, a substantial fraction of the lensed light is absorbed into the deflector’s model, which biases the subsequent fitting of the rings and then disturbs the selection process. We quantify completeness and purity of the lens finding method in both cases. This suggests that the main limitation currently resides in the subtraction of the foreground light. Provided further enhancement of the latter, the direct forward modeling of large numbers of galaxy-galaxy strong lenses thus appears tractable and could constitute a competitive lens finder in the next generation of wide-field imaging surveys.
F. Brault and R. Gavazzi
Thu, 6 Nov 14
26/67
Comments: Submitted to Astronomy & Astrophysics (13 pages, 10 figures)
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