$\texttt{tdescore}$: An Accurate Photometric Classifier for Tidal Disruption Events

Understand

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%.