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The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2017/2018 follow-up campaign: Discovery of 10 lensed quasars and 10 quasar pairs

We report the results of the STRong lensing Insights from the Dark Energy Survey (STRIDES) follow-up campaign of the late 2017/early 2018 season. We obtained spectra of 65 lensed quasar candidates either with EFOSC2 on the NTT or ESI on Keck, which confirm 10 new gravitationally lensed quasars and 10 quasar pairs with similar spectra, but which do not show a lensing galaxy in DES images. Eight lensed quasars are doubly imaged with source redshifts between 0.99 and 2.90, one is triply imaged by a group (DESJ0345-2545, $z=1.68$), and one is quadruply imaged (quad: DESJ0053-2012, $z=3.8$). Singular isothermal ellipsoid models for the doubles, based on high-resolution imaging from SAMI on SOAR or NIRC2 on Keck, give total magnifications between 3.2 and 5.6, and Einstein radii between 0.49 and 1.97 arcseconds. After spectroscopic follow-up, we extract multi-epoch $grizY$ photometry of confirmed lensed quasars and contaminant quasar+star pairs from the first 4 years of DES data using parametric multi-band modelling, and compare variability in each system's components. By measuring the reduced $χ^2$ associated with fitting all epochs to the same magnitude, we find a simple cut on the less variable component that retains all confirmed lensed quasars, while removing 94 per cent of contaminant systems with stellar components. Based on our spectroscopic follow-up, this variability information can improve selection of lensed quasars and quasar pairs from 34-45 per cent to 51-70 per cent, with the majority of remaining contaminants being compact star-forming galaxies. Using mock lensed quasar lightcurves we demonstrate that selection based only on variability will over-represent the quad fraction by 10 per cent over a complete DES magnitude-limited sample (excluding microlensing differences), explained by the magnification bias and hence lower luminosity (more variable) sources in quads.

preprint2019arXivOpen access

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