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

• Autor(a) principal: Ostrovski, Fernanda
• Data de Publicação: 2017
• Outros Autores: 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-Levy, Aurelien, Bertin, Emmanuel, Brooks, David, Buckley-Geer, Elizabeth, Rosell, Aurelio Carnero, Kind, Matias Carrasco, Carretero, Jorge, Cunha, Carlos E., Costa, Luiz N. da, Desai, Shantanu, Diehl, H. Thomas, Dietrich, Jorg 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, Malagon, Andres Plazas, Reil, Kevin, Romer, Kathy, Sanchez, Eusebio, Santiago, Basilio, Scarpine, Vic, Sevilla-Noarbe, Ignacio, Soares-Santos, Marcelle, Sobreira, Flavia [UNESP], Suchyta, Eric, Tarle, Gregory, Thomas, Daniel, Tucker, Douglas L., Walker, Alistair R.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1093/mnras/stw2958; http://hdl.handle.net/11449/162526
• topic: gravitational lensing: strong; methods: observational; methods: statistical; quasars: general

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 arcsec lensed by a foreground z(l) = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars showthe lens system as a 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 comprising 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 +/- 0.003 and a foreground early-type galaxy with z = 0.400 +/- 0.002. We model the system as a single isothermal ellipsoid and find the Einstein radius theta(E) similar to 1.47 arcsec, enclosed mass M-enc similar to 4 x 10(11) M-circle dot and a time delay of similar to 52 d. 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.