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[Abridged] We exploit the clustering of massive galaxies to perform a highefficiency imaging search for gravitational lenses. Our dataset comprises 44fields imaged by the Hubble Space Telescope (HST) Advanced Camera for Surveys(ACS), each of which is centered on a lens discovered by the Strong Lens ACSSurvey (SLACS). We compare four different search methods: 1) automateddetection with the HST Archive Galaxy-scale Gravitational Lens Survey (HAGGLeS)robot, 2) examining cutout images of bright galaxies (BGs) after subtraction ofa smooth galaxy light distribution, 3) examining the unsubtracted BG cutouts,and 4) performing a full-frame visual inspection of the ACS images. We computepurity and completeness and consider investigator time for the four algorithms,using the main SLACS lenses as a testbed. The first and second algorithmsperform the best. We present the four new lens systems discovered during thiscomprehensive search, as well as one other likely candidate. For each new lenswe use the fundamental plane to estimate the lens velocity dispersion andpredict, from the resulting lens geometry, the redshifts of the lensed sources.Two of these new systems are found in galaxy clusters, which include the SLACSlenses in the two respective fields. Overall we find that the enhanced lensabundance (30^{+24}_{-8} lenses/degree^2) is higher than expected for randomfields (12^{+4}_{-2} lenses/degree^2 for the COSMOS survey). Additionally, wefind that the gravitational lenses we detect are qualitatively different fromthose in the parent SLACS sample: this imaging survey is largely probinghigher-redshift, and lower-mass, early-type galaxies.

Enhanced lensing rate by clustering of massive galaxies: newly discovered systems in the SLACS fields