: An Accurate Photometric Classifier for Tidal Disruption Events

arxiv(2023)

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摘要
Optical surveys have become increasingly adept at identifying candidate Tidal Disruption Events (TDEs) in large numbers, but classifying these generally requires extensive spectroscopic resources. Here we present , a simple binary photometric classifier that is trained using a systematic census of ∼3000 nuclear transients from the Zwicky Transient Facility (ZTF). The sample is highly imbalanced, with TDEs representing ∼2 reject non-TDEs with 99.6 recall of 77.5 substantially better than any available TDE photometric classifier scheme in the literature, with performance not far from spectroscopy as a method for classifying ZTF nuclear transients, despite relying solely on ZTF data and multi-wavelength catalogue cross-matching. In a novel extension, we use `SHapley Additive exPlanations' () to provide a human-readable justification for each individual classification, enabling users to understand and form opinions about the underlying classifier reasoning. can serve as a model for photometric identification of TDEs with time-domain surveys, such as the upcoming Rubin observatory.
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