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Discovery of two bright high-redshift gravitationally lensed quasars revealed by Gaia
ABSTRACT We present the discovery and preliminary characterisation of two high-redshift gravitationally lensed quasar systems in Gaia Data Release 2 (DR2). Candidates with multiple close-separation Gaia detections and quasar-like colours in WISE, Pan-STARRS, and DES are selected for follow-up spectr...
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Published in: | Monthly notices of the Royal Astronomical Society 2022-01, Vol.509 (1), p.738-747 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Request full text |
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Summary: | ABSTRACT
We present the discovery and preliminary characterisation of two high-redshift gravitationally lensed quasar systems in Gaia Data Release 2 (DR2). Candidates with multiple close-separation Gaia detections and quasar-like colours in WISE, Pan-STARRS, and DES are selected for follow-up spectroscopy with the New Technology Telescope. We confirm DES J215028.71−465251.3 as a $z$ = 4.130 ± 0.006 asymmetric, doubly imaged lensed quasar system and model the lensing mass distribution as a singular isothermal sphere. The system has an Einstein radius of 1.202 ± 0.005 arcsec and a predicted time delay of ∼122.0 d between the quasar images, assuming a lensing galaxy redshift of $z$ = 0.5, making this a priority system for future optical monitoring. We confirm PS J042913.17+142840.9 as a $z$ = 3.866 ± 0.003 four-image quasar system in a cusp configuration, lensed by two foreground galaxies. The system is well modelled using a singular isothermal ellipsoid for the primary lens and a singular isothermal sphere for the secondary lens with Einstein radii 0.704 ± 0.006 and 0.241 ± 0.030 arcsec, respectively. A maximum predicted time delay of 9.6 d is calculated, assuming lensing galaxy redshifts of $z$ = 1.0. Furthermore, PS J042913.17+142840.9 exhibits a large flux ratio anomaly, up to a factor of 2.66 ± 0.37 in i band, that varies across optical and near-infrared wavelengths. We discuss LSST and its implications for future high-redshift lens searches and outline an extension to the search using supervised machine learning techniques. |
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ISSN: | 0035-8711 1365-2966 |
DOI: | 10.1093/mnras/stab2960 |