Automated detection of galaxy-scale gravitational lenses in high-resolution imaging data

Philip J. Marshall, David W. Hogg, Leonidas A. Moustakas, Christopher D. Fassnacht, Marua Brada, Tim Schrabback, Roger D. Blandford

    Research output: Contribution to journalArticlepeer-review


    We expect direct lens modeling to be the key to successful and meaningful automated strong galaxy-scale gravitational lens detection. We have implemented a lens-modeling "robot" that treats every bright red galaxy (BRG) in a large imaging survey as a potential gravitational lens system. Having optimized a simple model for "typical" galaxy-scale gravitational lenses, we generate four assessments of model quality that are then used in an automated classification. The robot infers from these four data the lens classification parameter H that a human would have assigned; the inference is performed using a probability distribution generated from a human-classified training set of candidates, including realistic simulated lenses and known false positives drawn from the Hubble Space Telescope (HST) Extended Groth Strip (EGS) survey. We compute the expected purity, completeness, and rejection rate, and find that these statistics can be optimized for a particular application by changing the prior probability distribution for H; this is equivalent to defining the robot's "character." Adopting a realistic prior based on expectations for the abundance of lenses, we find that a lens sample may be generated that is 100% pure, but only 20% complete. This shortfall is due primarily to the oversimplicity of the model of both the lens light and mass. With a more optimistic robot, 90% completeness can be achieved while rejecting 90% of the candidate objects. The remaining candidates must be classified by human inspectors. Displaying the images used and produced by the robot on a custom "one-click" web interface, we are able to inspect and classify lens candidates at a rate of a few seconds per system, suggesting that a future 1000 deg2 imaging survey containing 107 BRGs, and some 10 4 lenses, could be successfully, and reproducibly, searched in a modest amount of time. We have verified our projected survey statistics, albeit at low significance, using the HST EGS data, discovering four new lens candidates in the process.

    Original languageEnglish (US)
    Pages (from-to)924-942
    Number of pages19
    JournalAstrophysical Journal
    Issue number2
    StatePublished - 2009


    • Galaxies: elliptical and lenticular, cD
    • Gravitational lensing
    • Methods: data analysis
    • Methods: statistical
    • Surveys
    • Techniques: miscellaneous

    ASJC Scopus subject areas

    • Astronomy and Astrophysics
    • Space and Planetary Science


    Dive into the research topics of 'Automated detection of galaxy-scale gravitational lenses in high-resolution imaging data'. Together they form a unique fingerprint.

    Cite this