An Exquisitely Deep View of Quenching Galaxies through the Gravitational Lens: Stellar Population, Morphology, and Ionized Gas
Bibliographic record
Abstract
Abstract This work presents an in-depth analysis of four gravitationally lensed red galaxies at z = 1.6–3.2. The sources are magnified by factors of 2.7–30 by foreground clusters, enabling spectral and morphological measurements that are otherwise challenging. Our sample extends below the characteristic mass of the stellar mass function and is thus more representative of the quiescent galaxy population at z > 1 than previous spectroscopic studies. We analyze deep VLT/X-SHOOTER spectra and multiband Hubble Space Telescope photometry that cover the rest-frame UV-to-optical regime. The entire sample resembles stellar disks as inferred from lensing-reconstructed images. Through stellar population synthesis analysis, we infer that the targets are young (median age = 0.1–1.2 Gyr) and formed 80% of their stellar masses within 0.07–0.47 Gyr. Mg ii λλ 2796, 2803 absorption is detected across the sample. Blueshifted absorption and/or redshifted emission of Mg ii are found in the two youngest sources, indicative of a galactic-scale outflow of warm ( T ∼ 10 4 K) gas. The [O iii ] λ 5007 luminosity is higher for the two young sources (median age less than 0.4 Gyr) than the two older ones, perhaps suggesting a decline in nuclear activity as quenching proceeds. Despite high-velocity ( v ≈ 1500 km s −1 ) galactic-scale outflows seen in the most recently quenched galaxies, warm gas is still present to some extent long after quenching. Altogether, our results indicate that star formation quenching at high redshift must have been a rapid process (<1 Gyr) that does not synchronize with bulge formation or complete gas removal. Substantial bulge growth is required if they are to evolve into the metal-rich cores of present-day slow rotators.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".