Gaia GraL: Gaia DR2 Gravitational Lens Systems. V. Doubly-imaged QSOs discovered from entropy and wavelets

Autor: Krone-Martins, A., Graham, M. J., Stern, D., Djorgovski, S. G., Delchambre, L., Ducourant, C., Teixeira, R., Drake, A. J., Scarano Jr., S., Surdej, J., Galluccio, L., Jalan, P., Wertz, O., Klüter, J., Mignard, F., Spindola-Duarte, C., Dobie, D., Slezak, E., Sluse, D., Murphy, T., Boehm, C., Nierenberg, A. M., Bastian, U., Wambsganss, J., LeCampion, J. -F.
Rok vydání: 2019
Předmět:
Druh dokumentu: Working Paper
Popis: 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, multiwavelength photometric and spectroscopic data. This has limited the number of known systems to a few hundred objects. We aim to reduce the constraints on angular resolution and discover multiply-imaged QSO candidates by using new candidate selection principles based on unresolved photometric time-series and ground-based images from public surveys. We selected candidates for multiply-imaged QSOs based on low levels of entropy computed from Catalina unresolved photometric time-series or Euclidean similarity to known lenses in a space defined by the wavelet power spectra of Pan-STARSS DR2 or DECaLS DR7 images, combined with multiple {\it Gaia} DR2 sources or large astrometric errors and supervised and unsupervised learning methods. We then confirmed spectroscopically some candidates with the Palomar Hale, Keck-I, and ESO/NTT telescopes. Here we report the discovery and confirmation of seven doubly-imaged QSOs and one likely double quasar. This demonstrates the potential of combining space-astrometry, even if unresolved, with low spatial-resolution photometric time-series and/or low-spatial resolution multi-band imaging to discover multiply-imaged lensed QSOs.
Comment: 8 pages including Appendix, 3 figures, 1 table. To be submitted to A&A - Comments are very welcome
Databáze: arXiv