ALeRCE light curve classifier: Tidal disruption event expansion pack

¹ Instituto de Astrofísica, Facultad de Física, Pontificia Universidad Católica de Chile, Campus San Joaquín, Av. Vicuña Mackenna 4860, Macul Santiago 7820436, Chile
² Millennium Institute of Astrophysics (MAS), Nuncio Monseñor Sótero Sanz 100, Providencia, Santiago, Chile
³ Departamento de Astronomía, Universidad de Chile, Casilla 36D, Santiago, Chile
⁴ European Southern Observatory, Karl-Schwarzschild-Strasse 2, 85748 Garching bei München, Germany
⁵ Millennium Nucleus on Transversal Research and Technology to Explore Supermassive Black Holes (TITANS), 4030000 Concepción, Chile
⁶ Instituto de Física y Astronomía, Facultad de Ciencias, Universidad de Valparaíso, Gran Bretana 1111, Playa Ancha, Valparaíso, Chile
⁷ Centro de Astroingeniería, Facultad de Física, Pontificia Universidad Católica de Chile, Campus San Joaquín, Av. Vicuña Mackenna 4860, Macul Santiago 7820436, Chile
⁸ Space Science Institute, 4750 Walnut Street, Suite 205, Boulder, Colorado 80301, USA
⁹ Data and Artificial Intelligence Initiative (IDIA), Faculty of Physical and Mathematical Sciences, Universidad de Chile, Chile
¹⁰ Center for Mathematical Modeling, Universidad de Chile, Beauchef 851, Santiago 8370456, Chile
¹¹ Instituto de Estudios Astrofísicos, Facultad de Ingeniería y Ciencias, Universidad Diego Portales, Av. Ejército Libertador 441, Santiago, Chile
¹² Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871, China
¹³ Data Observatory Foundation, Santiago, Chile
¹⁴ Institute of Astronomy, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium
¹⁵ Department of Computer Science, Universidad de Concepción, Concepción, Chile
¹⁶ Data Science Unit, Universidad de Concepción, Edmundo Larenas 310, Concepción, Chile

^★ Corresponding author; mpavezh@estudiante.uc.cl

Received: 22 August 2024
Accepted: 21 February 2025

Abstract

Context. ALeRCE (Automatic Learning for the Rapid Classification of Events) is currently processing the Zwicky Transient Facility (ZTF) alert stream, in preparation for the Vera C. Rubin Observatory, and classifying objects using a broad taxonomy. The ALeRCE light curve classifier is a balanced random forest (BRF) algorithm with a two-level scheme that uses variability features computed from the ZTF alert stream, and colors obtained from AllWISE and ZTF photometry.

Aims. This work develops an updated version of the ALeRCE broker light curve classifier that includes tidal disruption events (TDEs) as a new subclass. For this purpose we incorporated 24 new features, notably including the distance to the nearest source detected in ZTF science images and a parametric model of the power-law decay for transients. We also expanded the labeled set to include 219 792 spectroscopically classified sources, including 60 TDEs.

Methods. To effectively integrate TDEs into the ALeRCE’s taxonomy, we identified specific characteristics that set them apart from other transient classes, such as their central position in a galaxy, the typical decay pattern displayed when fully disrupted, and the lack of color variability after disruption. Based on these attributes, we developed features to distinguish TDEs from other transient events.

Results. The modified classifier can distinguish between a broad range of classes with a better performance compared to the previous version and it can integate the TDE class achieving 91% recall, also identifying a large number of potential TDE candidates in ZTF alert stream unlabeled data.