Keywords :
gravitational lensing strong - methods: statistical - catalogues
Abstract:Wide-field photometric surveys enable searches of rare yet interesting objects, such as strongly lensed quasars or quasars with a bright host galaxy. Past searches for lensed quasars based on their optical and near-infrared properties have relied on photometric cuts and spectroscopic preselection (as in the Sloan Quasar Lens Search), or neural networks applied to photometric samples. These methods rely on cuts in morphology and colours, with the risk of losing many interesting objects due to scatter in their population properties, restrictive training sets, systematic uncertainties in catalogue-based magnitudes and survey-to-survey photometric variations. Here, we explore the performance of a Gaussian mixture model to separate
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