Artículos de revistas
Alert classification for the alerce broker system: the real-time stamp classifier
Fecha
2021Registro en:
The Astronomical Journal, 162:231 (27pp), 2021 December
10.3847/1538-3881/ac0ef1
Autor
Carrasco Davis, Rodrigo Antonio
Reyes, E.
Valenzuela, C.
Foerster, F.
Estévez Valencia, Pablo Antonio
Pignata, G.
Bauer, F. E.
Reyes, I.
Sánchez Sáez, P.
Cabrera Vives, G.
Eyheramendy, S.
Catelan, M.
Arredondo, J.
Castillo Navarrete, E.
Rodríguez Mancini, D.
Ruz Mieres, Daniela Valentina
Moya, A.
Sabatini Gacitúa, Luis Alfredo
Sepúlveda Cobo, Cristóbal Mario
Mahabal, A. A.
Silva Farfán, Javier Ignacio
Camacho Iñiguez, E.
Galbany, L.
Institución
Resumen
We present a real-time stamp classifier of astronomical events for the Automatic Learning for the Rapid
Classification of Events broker, ALeRCE. The classifier is based on a convolutional neural network, trained on
alerts ingested from the Zwicky Transient Facility (ZTF). Using only the science, reference, and difference images
of the first detection as inputs, along with the metadata of the alert as features, the classifier is able to correctly
classify alerts from active galactic nuclei, supernovae (SNe), variable stars, asteroids, and bogus classes, with high
accuracy (∼94%) in a balanced test set. In order to find and analyze SN candidates selected by our classifier from
the ZTF alert stream, we designed and deployed a visualization tool called SN Hunter, where relevant information
about each possible SN is displayed for the experts to choose among candidates to report to the Transient Name
Server database. From 2019 June 26 to 2021 February 28, we have reported 6846 SN candidates to date (11.8
candidates per day on average), of which 971 have been confirmed spectroscopically. Our ability to report objects
using only a single detection means that 70% of the reported SNe occurred within one day after the first detection.
ALeRCE has only reported candidates not otherwise detected or selected by other groups, therefore adding new
early transients to the bulk of objects available for early follow-up. Our work represents an important milestone
toward rapid alert classifications with the next generation of large etendue telescopes, such as the Vera C. Rubin
Observatory.