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تسجيل مستخدم جديدAvocado: Photometric Classification of Astronomical Transients with Gaussian Process Augmentation
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Kyle Boone
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Upcoming astronomical surveys such as the Large Synoptic Survey Telescope (LSST) will rely on photometric classification to identify the majority of the transients and variables that they discover. We present a set of techniques for photometric classification that can be applied even when the training set of spectroscopically-confirmed objects is heavily biased towards bright, low-redshift objects. Using Gaussian process regression to model arbitrary light curves in all bands simultaneously, we augment the training set by generating n
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