VDES J2325-5229 a z=2.7 gravitationally lensed quasar discovered using morphology independent supervised machine learning

15 Nov 2016 Ostrovski Fernanda McMahon Richard G. Connolly Andrew J. Lemon Cameron A. Auger Matthew W. Banerji Manda Hung Johnathan M. Koposov Sergey E. Lidman Christopher E. Reed Sophie L. Allam Sahar Benoit-Lévy Aurélien Bertin Emmanuel Brooks David Buckley-Geer Elizabeth Rosell Aurelio Carnero Kind Matias Carrasco Carretero Jorge Cunha Carlos E. da Costa Luiz N. Desai Shantanu Diehl H. Thomas Dietrich Jörg P. Evrard August E. Finley David A. Flaugher Brenna Fosalba Pablo Frieman Josh Gerdes David W. Goldstein Daniel A. Gruen Daniel Gruendl Robert A. Gutierrez Gaston Honscheid Klaus James David J. Kuehn Kyler Kuropatkin Nikolay Lima Marcos Lin Huan Maia Marcio A. G. Marshall Jennifer L. Martini Paul Melchior Peter Miquel Ramon Ogando Ricardo Malagón Andrés Plazas Reil Kevin Romer Kathy Sanchez Eusebio Santiago Basilio Scarpine Vic Sevilla-Noarbe Ignacio Soares-Santos Marcelle Sobreira Flavia Suchyta Eric Tarle Gregory Thomas Daniel Tucker Douglas L. Walker Alistair R.

We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift $z_{s}=2.74$ and image separation of $2.9"$ lensed by a foreground $z_{l}=0.40$ elliptical galaxy. Since the images of gravitationally lensed quasars are the superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning... (read more)

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  • ASTROPHYSICS OF GALAXIES