REQUIEM-2D: A Diversity of Formation Pathways in a Sample of Spatially Resolved Massive Quiescent Galaxies at z ∼ 2
Bibliographic record
Abstract
Abstract REQUIEM-2D (Resolving Quiescent Magnified Galaxies with 2D Grism Spectroscopy) comprises a sample of eight massive ( log ( M ∗ / M ⊙ ) > 10.6 ) strongly lensed quiescent galaxies at z ∼ 2. REQUIEM-2D combines the natural magnification from strong gravitational lensing with the high-spatial-resolution grism spectroscopy of the Hubble Space Telescope through a spectrophotometric fit to study spatially resolved stellar populations. We show that quiescent galaxies in the REQUIEM-2D survey have diverse formation histories with age gradients at the 1 σ –3 σ level, including examples of (1) a younger central region supporting outside-in formation, (2) flat age gradients that show evidence for both spatially uniform early formation and inside-out quenching, and (3) regions at a fixed radial distance having different ages (such asymmetries cannot be recovered when averaging stellar population measurements azimuthally). The typical dust attenuation curve for the REQUIEM-2D galaxies is constrained to be steeper than Calzetti’s law in the UV and generally consistent with A V < 1. Combined together and accounting for the different physical radial distances and formation timescales, we find that the REQUIEM-2D galaxies that formed earlier in the universe exhibit slow and uniform growth in their inner core, whereas the galaxies that formed later have rapid inner growth in their inner core with younger ages than the outskirts. These results challenge the currently accepted paradigm of how massive quiescent galaxies form, where the earliest galaxies are thought to form most rapidly. Significantly larger samples close to the epoch of formation with similar data quality and higher spectral resolution are required to validate this finding.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".