Photometric redshift estimation of strongly lensed galaxies

Abstract

Around $10^5$ strongly lensed galaxies are expected to be discovered with Euclid and the LSST. Utilising these large samples to study the inner structure of lens galaxies requires source redshifts, to turn lens models into mass measurements. However, obtaining spectroscopic source redshifts for large lens samples is prohibitive with the capacity of spectroscopic facilities. Alternatively, we study the possibility of obtaining source photometric redshifts (photo-zs) for large lens samples. Our strategy consists of deblending the source and lens light by simultaneously modelling the lens and background source in all available photometric bands, and feeding the derived source colours to a template-fitting photo-z algorithm. We describe the lens and source light with a Sersic profile, and the lens mass with a Singular Isothermal Ellipsoid. We test our approach on a simulated and a real sample of lenses, both in broad-band photometry of the Hyper Suprime-Cam survey. We identify the deviations of the lens light from a Sersic profile and the contrast between the lens and source image as the main drivers of the source colour measurement error. We split the real sample based on the ratio $\Lambda$ of the lens to source surface brightness measured at the image locations. In the $\Lambda <1$ regime, the photo-z outlier fraction is $20\%$, and the accuracy of photo-z estimation is limited by the performance of template-fitting process. In the opposite regime, the photo-z outlier fraction is $75\%$, and the errors from the source colour measurements dominate the photo-z uncertainty. Measuring source photo-zs for lenses with $\Lambda <1$ poses no particular challenges, compared to isolated galaxies. For systems with significant lens light contamination, however, improving the description of the surface brightness distribution of the lens is required: a single Sersic model is not sufficiently accurate.

15 pages, 13 figures, Accepted for Publication in A&A

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Cited by in corpus (1)

• Strong lensing selection effects