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  1. Home
  2. Browse by Author

Browsing by Author "Cabrera Vives, G."

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    ALeRCE light curve classifier: Tidal disruption event expansion pack
    (2025) Pavez Herrera, M.; Sánchez Sáez, P.; Hernández García, L.; Bauer, F. E.; Förster, F.; Catelan, Márcio; Muñoz Arancibia, A.; Ricci, C.; Reyes Jainaga, I.; Bayo, A.; Huijse, P.; Cabrera Vives, G.
    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.
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    The delay of shock breakout due to circumstellar material evident in most type II supernovae
    (2018) Forster, F.; Moriya, T. J.; Maureira, J. C.; Anderson, J. P.; Blinnikov, S.; Bufano, F.; Cabrera Vives, G.; Clocchiatti, Alejandro; De Jaeger, T.; Estevez, P. A.; Galbany, L.; González -Gaitán, S.; Grafener, G.; Hamuy, M.; Hsiao, E. Y.; Huentelemu, P.; Huijse, P.; Kuncarayakti, H.; Martínez, J.; Medina, G.; Olivares, F.; Pignata, Giuliano; Razza, A.; Reyes, I.; San Martín, J.; Smith, R. C.; Vera, E.; Vivas, A. K.; Postigo, A. D.; Yoon, S. C.; Ashall, C.; Fraser, M.; Gal-Yam, A.; Kankare, E.; Le Guillou, L.; Mazzali, P. A.; Walton, N. A.; Young, D. R.

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