Spatially Resolved Stellar Kinematics from LEGA-C: Increased Rotational Support in z ∼ 0.8 Quiescent Galaxies
Bibliographic record
Abstract
Abstract We present stellar rotation curves and velocity dispersion profiles for 104 quiescent galaxies at z = 0.6–1 from the Large Early Galaxy Astrophysics Census (LEGA-C) spectroscopic survey. Rotation is typically probed across 10–20 kpc, or to an average of 2.7 R e . Combined with central stellar velocity dispersions ( σ 0 ) this provides the first determination of the dynamical state of a sample selected by a lack of star formation activity at large lookback time. The most massive galaxies ( M ⋆ > 2 × 10 11 M ⊙ ) generally show no or little rotation measured at 5 kpc ( ∣ V 5 ∣ / σ 0 < 0.2 in eight of ten cases), while ∼64% of less massive galaxies show significant rotation. This is reminiscent of local fast- and slow-rotating ellipticals and implies that low- and high-redshift quiescent galaxies have qualitatively similar dynamical structures. We compare ∣ V 5 ∣ / σ 0 distributions at z ∼ 0.8 and the present day by re-binning and smoothing the kinematic maps of 91 low-redshift quiescent galaxies from the Calar Alto Legacy Integral Field Area (CALIFA) survey and find evidence for a decrease in rotational support since z ∼ 1. This result is especially strong when galaxies are compared at fixed velocity dispersion; if velocity dispersion does not evolve for individual galaxies then the rotational velocity at 5 kpc was an average of 94 ± 22% higher in z ∼ 0.8 quiescent galaxies than today. Considering that the number of quiescent galaxies grows with time and that new additions to the population descend from rotationally supported star-forming galaxies, our results imply that quiescent galaxies must lose angular momentum between z ∼ 1 and the present, presumably through dissipationless merging, and/or that the mechanism that transforms star-forming galaxies also reduces their rotational support.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".