Super-resolving distant galaxies with gravitational telescopes: Keck-LGSAO and Hubble imaging of the lens system SDSSJ0737+3216
P.J. Marshall (1), T.Treu (1), J. Melbourne (2), R. Gavazzi (1), K., Bundy (3), S.M. Ammons (2), A.S. Bolton (4), S. Burles (5), J.E. Larkin (6),, D. Le Mignant (7), D.C. Koo (3), L.V.E. Koopmans (8), C.E. Max (2), L.A., Moustakas (9), E.Steinbring (10)

TL;DR
This study demonstrates that ground-based laser guide star adaptive optics combined with Hubble imaging can accurately analyze distant galaxies, revealing their properties and aiding in understanding galaxy formation at low masses.
Contribution
It shows that ground-based Keck LGSAO imaging can match HST precision in gravitational lens studies, enabling detailed multi-wavelength analysis of distant, compact galaxies.
Findings
Ground-based LGSAO images are comparable to HST in precision.
The source galaxy is a compact, disk-like object with properties similar to dwarf galaxies.
This approach extends the study of size-mass relations to lower mass, high-redshift galaxies.
Abstract
We combine high-resolution images in four optical/infra-red bands, obtained with the laser guide star adaptive optics system on the Keck Telescope and with the Hubble Space Telescope, to study the gravitational lens system SDSSJ0737+3216 (lens redshift 0.3223, source redshift 0.5812). We show that (under favorable observing conditions) ground-based images are comparable to those obtained with HST in terms of precision in the determination of the parameters of both the lens mass distribution and the background source. We also quantify the systematic errors associated with both the incomplete knowledge of the PSF, and the uncertain process of lens galaxy light removal, and find that similar accuracy can be achieved with Keck LGSAO as with HST. We then exploit this well-calibrated combination of optical and gravitational telescopes to perform a multi-wavelength study of the source galaxy…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
