We present an algorithm for selecting a uniform sample of gravitationally lensed quasar candidates from low-redshift (0.6<z<2.2) quasars brighter than i=19.1 that have been spectroscopically identified in the Sloan Digital Sky Survey (SDSS). Our algorithm uses morphological and color selections that are intended to identify small- and large-separation lenses, respectively. Our selection algorithm only relies on parameters that the SDSS standard image processing pipeline generates, allowing easy and fast selection of lens candidates. The algorithm has been tested against simulated SDSS images, which adopt distributions of field and quasar parameters taken from the real SDSS data as input. Furthermore, we take differential reddening into account. We find that our selection algorithm is almost complete down to separations of 1" and flux ratios of 10^-0.5^.

Cone search capability for table J/AJ/132/999/table2 (Quadruply lensed quasars used in the simulation)