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

VDES J2325-5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
VDES J2325-5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift zs = 2.74 and image separation of 2.9 arcsec lensed by a foreground zl = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars show the 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 IAB = 18.61 and IAB = 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 θE ∼ 1.47 arcsec, enclosed mass Menc ∼ 4 × 1011 M⊙ and a time delay of ∼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.
gravitational lensing: strong, methods: observational, methods: statistical, quasars: general
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4325-4334
Ostrovski, Fernanda
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McMahon, Richard G.
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Connolly, Andrew J.
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Lemon, Cameron A.
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Auger, Matthew W.
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Evrard, August E.
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Finley, David A.
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Flaugher, Brenna
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Fosalba, Pablo
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Gerdes, David W.
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Honscheid, Klaus
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James, David J.
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Kuehn, Kyler
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Kuropatkin, Nikolay
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Lima, Marcos
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Lin, Huan
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Maia, Marcio A.G.
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Marshall, Jennifer L.
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Martini, Paul
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Melchior, Peter
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Miquel, Ramon
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Ogando, Ricardo
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Plazas Malagón, Andrés
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Reil, Kevin
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Romer, Kathy
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Sanchez, Eusebio
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et al.
Ostrovski, Fernanda
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McMahon, Richard G.
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Connolly, Andrew J.
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Lemon, Cameron A.
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Auger, Matthew W.
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Banerji, Manda
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Hung, Johnathan M.
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Koposov, Sergey E.
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Lidman, Christopher E.
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Reed, Sophie L.
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Allam, Sahar
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Benoit-Lévy, Aurélien
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Bertin, Emmanuel
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Brooks, David
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Buckley-Geer, Elizabeth
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Carnero Rosell, Aurelio
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Carrasco Kind, Matias
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Carretero, Jorge
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Cunha, Carlos E.
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da Costa, Luiz N.
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Desai, Shantanu
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Diehl, H. Thomas
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Evrard, August E.
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Finley, David A.
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Flaugher, Brenna
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Fosalba, Pablo
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Frieman, Josh
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Gerdes, David W.
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Goldstein, Daniel A.
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Gruen, Daniel
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Gruendl, Robert A.
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Gutierrez, Gaston
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Honscheid, Klaus
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James, David J.
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Kuehn, Kyler
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Kuropatkin, Nikolay
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Lima, Marcos
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Lin, Huan
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Maia, Marcio A.G.
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Marshall, Jennifer L.
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Martini, Paul
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Melchior, Peter
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Miquel, Ramon
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Ogando, Ricardo
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Plazas Malagón, Andrés
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Reil, Kevin
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Romer, Kathy
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Sanchez, Eusebio
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Santiago, Basilio
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Ostrovski, Fernanda, McMahon, Richard G. and Connolly, Andrew J. , et al. (2016) VDES J2325-5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning. Monthly Notices Of The Royal Astronomical Society, 465 (4), 4325-4334. (doi:10.1093/mnras/stw2958).

Record type: Article

Abstract

We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift zs = 2.74 and image separation of 2.9 arcsec lensed by a foreground zl = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars show the 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 IAB = 18.61 and IAB = 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 θE ∼ 1.47 arcsec, enclosed mass Menc ∼ 4 × 1011 M⊙ and a time delay of ∼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.

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Accepted/In Press date: 14 November 2016
Published date: 17 November 2016
Keywords: gravitational lensing: strong, methods: observational, methods: statistical, quasars: general

Identifiers

Local EPrints ID: 508807
URI: http://eprints.soton.ac.uk/id/eprint/508807
ISSN: 1365-2966
PURE UUID: 99f30d90-fe91-4800-ad6d-b76985c01a0b
ORCID for Manda Banerji: ORCID iD orcid.org/0000-0002-0639-5141

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Date deposited: 04 Feb 2026 17:32
Last modified: 05 Feb 2026 02:59

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Contributors

Author: Fernanda Ostrovski
Author: Richard G. McMahon
Author: Andrew J. Connolly
Author: Cameron A. Lemon
Author: Matthew W. Auger
Author: Manda Banerji ORCID iD
Author: Johnathan M. Hung
Author: Sergey E. Koposov
Author: Christopher E. Lidman
Author: Sophie L. Reed
Author: Sahar Allam
Author: Aurélien Benoit-Lévy
Author: Emmanuel Bertin
Author: David Brooks
Author: Elizabeth Buckley-Geer
Author: Aurelio Carnero Rosell
Author: Matias Carrasco Kind
Author: Jorge Carretero
Author: Carlos E. Cunha
Author: Luiz N. da Costa
Author: Shantanu Desai
Author: H. Thomas Diehl
Author: Jörg P. Dietrich
Author: August E. Evrard
Author: David A. Finley
Author: Brenna Flaugher
Author: Pablo Fosalba
Author: Josh Frieman
Author: David W. Gerdes
Author: Daniel A. Goldstein
Author: Daniel Gruen
Author: Robert A. Gruendl
Author: Gaston Gutierrez
Author: Klaus Honscheid
Author: David J. James
Author: Kyler Kuehn
Author: Nikolay Kuropatkin
Author: Marcos Lima
Author: Huan Lin
Author: Marcio A.G. Maia
Author: Jennifer L. Marshall
Author: Paul Martini
Author: Peter Melchior
Author: Ramon Miquel
Author: Ricardo Ogando
Author: Andrés Plazas Malagón
Author: Kevin Reil
Author: Kathy Romer
Author: Eusebio Sanchez
Author: Basilio Santiago
Corporate Author: et al.

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