DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images

We present DELIGHT, or Deep Learning Identification of Galaxy Hosts of Transients, a new algorithm designed to automatically and in real time identify the host galaxies of extragalactic transients. The proposed algorithm receives as input compact, multiresolution images centered at the position of a...

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Veröffentlicht in:	The Astronomical journal 2022-11, Vol.164 (5), p.195
Hauptverfasser:	Förster, Francisco, Muñoz Arancibia, Alejandra M., Reyes-Jainaga, Ignacio, Gagliano, Alexander, Britt, Dylan, Cuellar-Carrillo, Sara, Figueroa-Tapia, Felipe, Polzin, Ava, Yousef, Yara, Arredondo, Javier, Rodríguez-Mancini, Diego, Correa-Orellana, Javier, Bayo, Amelia, Bauer, Franz E., Catelan, Márcio, Cabrera-Vives, Guillermo, Dastidar, Raya, Estévez, Pablo A., Pignata, Giuliano, Hernández-García, Lorena, Huijse, Pablo, Reyes, Esteban, Sánchez-Sáez, Paula, Ramírez, Mauricio, Grandón, Daniela, Pineda-García, Jonathan, Chabour-Barra, Francisca, Silva-Farfán, Javier
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Astroinformatics Astronomical object identification Astronomy Classification Deep learning Galaxies Machine learning Neural networks Pixels Real time Red shift Regression models Stars & galaxies Supernovae Telescopes
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