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

Ostrovski, F; McMahon, RG; Connolly, AJ; Lemon, CA; Auger, MW; Banerji, M; Hung, JM; ... Walker, AR; + view all (2017) 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) pp. 4325-4334. 10.1093/mnras/stw2958. Green open access

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Abstract

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 θ E ~ 1.47 arcsec, enclosed mass M enc ~ 4 × 10 11 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.

Type: Article
Title: VDES J2325-5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/mnras/stw2958
Publisher version: https://doi.org/10.1093/mnras/stw2958
Language: English
Additional information: This is the published version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: gravitational lensing: strong, methods: observational, methods: statistical, quasars: general
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy
URI: https://discovery.ucl.ac.uk/id/eprint/1555150
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