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We present a semi-automated method to search for strong galaxy-galaxy lenses in optical imaging surveys. Our search technique constrains the shape of strongly lensed galaxies (or arcs) in a multi-parameter space, which includes the third order (octopole) moments of objects. This method is applied to the Deep Lens Survey (DLS), a deep ground based weak lensing survey imaging to $Rsim26$. The parameter space of arcs in the DLS is simulated using real galaxies extracted from deep HST fields in order to more accurately reproduce the properties of arcs. Arcs are detected in the DLS using a pixel thresholding method and candidate arcs are selected within this multi-parameter space. Examples of strong galaxy-galaxy lens candidates discovered in the DLS F2 field (4 square degrees) are presented.
We present a spectroscopic survey for strong galaxy-galaxy lenses. Exploiting optimal sight-lines to massive, bulge-dominated galaxies at redshifts $z sim 0.4$ with wide-field, multifibre spectroscopy, we anticipate the detection of 10-20 lensed Lyma
We present an algorithm using Principal Component Analysis (PCA) to subtract galaxies from imaging data, and also two algorithms to find strong, galaxy-scale gravitational lenses in the resulting residual image. The combined method is optimized to fi
We have conducted a search for new strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Data Release 8. We use deep residual neural networks, building on previous work presented in Huang et al. (2020
We present the first galaxy scale lens catalog from the second Red-Sequence Cluster Survey. The catalog contains 60 lensing system candidates comprised of Luminous Red Galaxy (LRG) lenses at 0.2 < z < 0.5 surrounded by blue arcs or apparent multiple