Mass and magnification maps for the Hubble Space Telescope Frontier Fields clusters: implications for high redshift studies
J.Richard (CRAL), M.Jauzac (Durban, Durham), M.Limousin, E.Jullo, (LAM), B.Cl\'ement (Steward), H.Ebeling (IfA, Hawaii), J.P.Kneib, H.Atek, (EPFL), P.Natarajan (Yale), E.Egami (Steward), R.Livermore (UT Austin),, R.Bower (Durham)

TL;DR
This paper presents detailed mass and magnification maps for six Hubble Frontier Fields clusters, enabling improved detection and study of high-redshift galaxies through gravitational lensing.
Contribution
It provides the first combined strong- and weak-lensing models for these clusters, calibrated with 88 multiple-image systems, to aid in high-redshift galaxy research.
Findings
Maps enable detection of galaxies at z>10 as faint as m(AB)=32.
Lensing boosts sensitivity, allowing observations 2 magnitudes deeper than the Hubble Ultra Deep Field.
Models serve as a community resource for future high-redshift studies.
Abstract
Extending over three Hubble Space Telescope (HST) cycles, the Hubble Frontier Fields (HFF) initiative constitutes the largest commitment ever of HST time to the exploration of the distant Universe via gravitational lensing by massive galaxy clusters. We here present models of the mass distribution in the six HFF cluster lenses, derived from a joint strong- and weak-lensing analysis anchored by a total of 88 multiple-image systems identified in existing HST data. The resulting maps of the projected mass distribution and of the gravitational magnification effectively calibrate the HFF clusters as gravitational telescopes. Allowing the computation of search areas in the source plane, these maps are provided to the community to facilitate the exploitation of forthcoming HFF data for quantitative studies of the gravitationally lensed population of background galaxies. Our models of the…
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.
