1. $\texttt{tdescore}$: An Accurate Photometric Classifier for Tidal Disruption Events
- Author
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Stein, Robert, Mahabal, Ashish, Reusch, Simeon, Graham, Matthew, Kasliwal, Mansi M., Kowalski, Marek, Gezari, Suvi, Hammerstein, Erica, Nakoneczny, Szymon J., Nicholl, Matt, Sollerman, Jesper, van Velzen, Sjoert, Yao, Yuhan, Laher, Russ R., and Rusholme, Ben
- Subjects
Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - High Energy Astrophysical Phenomena - Abstract
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 $\texttt{tdescore}$, a simple binary photometric classifier that is trained using a systematic census of $\sim$3000 nuclear transients from the Zwicky Transient Facility (ZTF). The sample is highly imbalanced, with TDEs representing $\sim$2% of the total. $\texttt{tdescore}$ is nonetheless able to reject non-TDEs with 99.6% accuracy, yielding a sample of probable TDEs with recall of 77.5% for a precision of 80.2%. $\texttt{tdescore}$ is thus 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' ($\texttt{SHAP}$) to provide a human-readable justification for each individual $\texttt{tdescore}$ classification, enabling users to understand and form opinions about the underlying classifier reasoning. $\texttt{tdescore}$ can serve as a model for photometric identification of TDEs with time-domain surveys, such as the upcoming Rubin observatory., Comment: Accepted for publication, 16 pages, 7 figures, 2 tables
- Published
- 2023
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