The LEGA-C and SAMI galaxy surveys: quiescent stellar populations and the mass–size plane across 6 Gyr
Bibliographic record
Abstract
ABSTRACT We investigate changes in stellar population age and metallicity ([Z/H]) scaling relations for quiescent galaxies from intermediate redshift (0.60 ≤ $z$ ≤ 0.76) using the LEGA-C Survey to low redshift (0.014 ≤ $z$ ≤ 0.10) using the SAMI Galaxy Survey. Specifically, we study how the spatially integrated global age and metallicity of individual quiescent galaxies vary in the mass–size plane, using the stellar mass M* and a dynamical mass proxy derived from the virial theorem MD ∝ σ2 Re. We find that, similarly to at low redshift, the metallicity of quiescent galaxies at 0.60 ≤ $z$ ≤ 0.76 closely correlates with M/Re (a proxy for the gravitational potential or escape velocity), in that galaxies with deeper potential wells are more metal-rich. This supports the hypothesis that the relation arises due to the gravitational potential regulating the retention of metals by determining the escape velocity for metal-rich stellar and supernova ejecta to escape the system and avoid being recycled into later stellar generations. Conversely, we find no correlation between age and surface density ($M/R_\mathrm{e}^2$) at 0.60 ≤ $z$ ≤ 0.76, despite this relation being strong at low redshift. We consider this change in the age–$M/R_\mathrm{e}^2$ relation in the context of the redshift evolution of the star-forming and quiescent mass–size relations, and find our results are consistent with galaxies forming more compactly at higher redshifts and remaining compact throughout their evolution. Furthermore, galaxies appear to quench at a characteristic surface density that decreases with decreasing redshift. The $z$ ∼ 0 age–$M/R_\mathrm{e}^2$ relation is therefore a result of building up the quiescent and star-forming populations with galaxies that formed at a range of redshifts and therefore a range of surface densities.
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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) | 0.001 | 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".