Discovery of a [CLC]z[/CLC] = 0.77 Galaxy Cluster with Multiple, Bright, Strong-Lensing Arcs
Bibliographic record
Abstract
We report the discovery of a remarkable strong-lensing cluster from the ongoing Red-Sequence Cluster Survey (RCS). RCS 0224-0002, at a spectroscopic redshift of 0.773, lenses two to four separate background sources. These arcs are of relatively high surface brightness and hence amenable to detailed follow-up study. We provide preliminary photometry and spectroscopy of RCS 0224-0002 and discuss in detail the one lensed source for which a redshift has so far been determined. This galaxy, at a redshift of 4.8786, appears to be composed of a star-forming core enveloped in a Lyα emitting cloud. Moreover, it shows no measurable velocity structure to a limit of ∼50 km s -1 over a region likely to be ∼1 kpc in size. The available data are also used to develop an initial lensing model, which shows RCS 0224-0002 to have a mass corresponding to a central velocity dispersion of ∼1000 km s -1 , consistent with the measured optical richness of the cluster. This preliminary model is also used to estimate redshifts for all lensed components visible in our ground-based imaging. RCS 0224-0002 is the highest-redshift cluster to show lensing with such a large number of bright arcs (comparable to the best lensing clusters at much lower redshifts), and the highest-redshift strong-lensing cluster for which both the cluster redshift and at least one source redshift have been established spectroscopically, and as such it provides a powerful opportunity to directly measure the geometry of the universe and galaxy properties at high redshift.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".