Automated Lensing Learner: Automated Strong Lensing Identification with a Computer Vision Technique

Understand

Forthcoming surveys such as the Large Synoptic Survey Telescope (LSST) and Euclid necessitate automatic and efficient identification methods of strong lensing systems.

• We present a strong lensing identification approach that utilizes a feature extraction method from computer vision, the Histogram of Oriented Gradients (HOG), to capture edge patterns of arcs.
• We train a supervised classifier model on the HOG of mock strong galaxy-galaxy lens images similar to observations from the Hubble Space Telescope (HST) and LSST.
• We assess model performance with the area under the curve (AUC) of a Receiver Operating Characteristic (ROC) curve.