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Combining the exquisite angular resolution of Gaia with optical light curves and WISE photometry, the Gaia Gravitational Lenses group (GraL) uses machine learning techniques to identify candidate strongly lensed quasars, and has confirmed over two dozen new strongly lensed quasars from the Gaia Data Release 2. This paper reports on the 12 quadruply-imaged quasars identified by this effort to date, which is approximately a 20% increase in the total number of confirmed quadruply-imaged quasars. We discuss the candidate selection, spectroscopic follow-up, and lens modeling. We also report our spectroscopic failures as an aid for future investigations.
The discovery of multiply-imaged gravitationally lensed QSOs is fundamental to many astronomical and cosmological studies. However, these objects are rare and challenging to discover due to requirements of high-angular resolution astrometric, multiwa
Aims: In this work, we aim to provide a reliable list of gravitational lens (GL) candidates based on a search performed over the entire Gaia Data Release 2 (Gaia DR2). We also show that the sole astrometric and photometric informations coming from th
Context. Strong gravitationally lensed quasars are among the most interesting and useful observable extragalactic phenomena. Because their study constitutes a unique tool in various fields of astronomy, they are highly sought, not without difficulty.
Multiple image gravitational lens systems, and especially quads are invaluable in determining the amount and distribution of mass in galaxies. This is usually done by mass modeling using parametric or free-form methods. An alternative way of extracti
Gravitational lensing of point sources located inside the lens caustic is known to produce four images in a configuration closely related to the source position. We study this relation in the particular case of a sample of quadruply-imaged quasars ob