: An Accurate Photometric Classifier for Tidal Disruption Events
arxiv(2023)
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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