A Hubble & Spitzer Space Telescope Survey for Gravitationally-Lensed Galaxies: Further Evidence for a Significant Population of Low Luminosity Galaxies beyond Redshift Seven
Johan Richard (Caltech), Daniel P. Stark (Caltech), Richard S. Ellis, (Caltech), Matthew R. George (Caltech), Eiichi Egami (Steward Observatory),, Jean-Paul Kneib (LAM/OAMP), Graham P. Smith (U. Birmingham)

TL;DR
This study uses deep Hubble and Spitzer imaging of galaxy clusters to identify and analyze faint, high-redshift galaxies beyond redshift 7, providing new constraints on their abundance and role in cosmic reionization.
Contribution
It presents the first systematic search for z>7 galaxies using gravitational lensing, reaching unprecedented faintness levels and evaluating the high-redshift galaxy population.
Findings
Detected 12 candidate galaxies beyond redshift 7.
Provided constraints on the UV luminosity function at z~7.5.
Highlighted challenges in spectroscopic confirmation of high-redshift galaxies.
Abstract
We present the results of a systematic search for gravitationally-lensed continuum Lyman break `drop-outs' beyond a redshift 7 conducted via very deep imaging through six foreground clusters undertaken with the Hubble and Spitzer Space Telescopes. The survey has yielded 10 z-band and 2 J-band drop-out candidates to photometric limits of J_110~=26.2 AB (5sigma). Taking into account the magnifications afforded by our clusters (1-4 magnitudes), we probe the presence of z>7 sources to unlensed limits of J_{110}~=30 AB, fainter than those charted in the Hubble Ultradeep Field. To verify the fidelity of our candidates we conduct a number of tests for instrumental effects which would lead to spurious detections, and carefully evaluate the likelihood of foreground contamination by considering photometric uncertainties in the drop-out signature, the upper limits from stacked IRAC data and 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.
