Inverse stellar population age gradients of post-starburst galaxies at z = 0.8 with LEGA-C
Bibliographic record
Abstract
ABSTRACT We use deep, spatially resolved spectroscopy from the Large Early Galaxy Astrophysics Census Survey to study radial variations in the stellar population of 17 spectroscopically selected post-starburst (PSB) galaxies. We use spectral fitting to measure two Lick indices, H δA and Fe 4383 , and find that, on average, PSB galaxies have radially decreasing H δA and increasing Fe 4383 profiles. In contrast, a control sample of quiescent, non-PSB galaxies in the same mass range shows outwardly increasing H δA and decreasing Fe 4383 . The observed gradients are weak (≈−0.2 Å/Re), mainly due to seeing convolution. A two-SSP (simple stellar population) model suggests that intrinsic gradients are as strong as observed in local PSB galaxies (≈−0.8 Å/Re). We interpret these results in terms of inside-out growth (for the bulk of the quiescent population) versus star formation occurring last in the centre (for PSB galaxies). At z ≈ 0.8, central starbursts are often the result of gas-rich mergers, as evidenced by the high fraction of PSB galaxies with disturbed morphologies and tidal features (40 per cent). Our results provide additional evidence for multiple paths to quiescence: a standard path, associated with inside-out disc formation and with gradually decreasing star formation activity, without fundamental structural transformation, and a fast path, associated with centrally concentrated starbursts, leaving an inverse age gradient and smaller half-light radius.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".