VDES J2325-5229 a z=2.7 gravitationally lensed quasar discovered using morphology independent supervised machine learning
Creators: name: Ostrovski, Fernanda
name: McMahon, Richard G.
name: Connolly, Andrew J.
name: Lemon, Cameron A.
name: Auger, Matthew W.
name: Banerji, Manda
name: Hung, Johnathan M.
name: Koposov, Sergey E.
name: Lidman, Christopher E.
name: Reed, Sophie L.
name: Allam, Sahar
name: Benoit-Lévy, Aurélien
name: Bertin, Emmanuel
name: Brooks, David
name: Buckley-Geer, Elizabeth
name: Rosell, Aurelio Carnero
name: Kind, Matias Carrasco
name: Carretero, Jorge
name: Cunha, Carlos E.
name: da Costa, Luiz N.
name: Desai, Shantanu
name: Diehl, H. Thomas
name: Dietrich, Jörg P.
name: Evrard, August E.
name: Finley, David A.
name: Flaugher, Brenna
name: Fosalba, Pablo
name: Frieman, Josh
name: Gerdes, David W.
name: Goldstein, Daniel A.
name: Gruen, Daniel
name: Gruendl, Robert A.
name: Gutierrez, Gaston
name: Honscheid, Klaus
name: James, David J.
name: Kuehn, Kyler
name: Kuropatkin, Nikolay
name: Lima, Marcos
name: Lin, Huan
name: Maia, Marcio A. G.
name: Marshall, Jennifer L.
name: Martini, Paul
name: Melchior, Peter
name: Miquel, Ramon
name: Ogando, Ricardo
name: Malagón, Andrés Plazas
name: Reil, Kevin
name: Romer, Kathy
name: Sanchez, Eusebio
name: Santiago, Basilio
name: Scarpine, Vic
name: Sevilla-Noarbe, Ignacio
name: Soares-Santos, Marcelle
name: Sobreira, Flavia
name: Suchyta, Eric
name: Tarle, Gregory
name: Thomas, Daniel
name: Tucker, Douglas L.
name: Walker, Alistair R.
Publisher: name: arXiv
Year: 2016
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences
subject: FOS: Physical sciences

description: 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. Using this technique and $gi$ multicolour photometric observations from the Dark Energy Survey (DES), near IR $JK$ photometry from the VISTA Hemisphere Survey (VHS) and WISE mid IR photometry, we have identified a candidate system with two catalogue components with $i_{AB}=18.61$ and $i_{AB}=20.44$ comprised of an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of $z=2.739\pm0.003$ and a foreground early type galaxy with $z=0.400\pm0.002$. We model the system as a single isothermal ellipsoid and find the Einstein radius $θ_E \sim 1.47"$, enclosed mass $M_{enc} \sim 4 \times 10^{11}$M$_{\odot}$ and a time delay of $\sim$52 days. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1.
description: 11 pages, 7 figures, 7 tables, MNRAS accepted