Rejuvenation in z ∼ 0.8 Quiescent Galaxies in LEGA-C
Bibliographic record
Abstract
We use reconstructed star formation (SF) histories of quiescent galaxies at z = 0.6─1 in the Large Early Galaxy Astrophysics Census survey to identify secondary SF episodes that, after an initial period of quiescence, moved the galaxies back to the star-forming main sequence (blue cloud). 16 ± 3% of the z ∼ 0.8 quiescent population has experienced such rejuvenation events in the redshift range of 0.7 < z < 1.5 after reaching quiescence at some earlier time. On average, these galaxies first became quiescent at z = 1.2, and those that rejuvenated, remained quiescent for ∼1 Gyr before their secondary SF episode, which lasted ∼0.7 Gyr. The stellar mass attributed to rejuvenation is on average 10% of the galaxy stellar mass, with rare instances of an increase of more than a factor of 2. Overall, rejuvenation events only contribute ∼2% of the total stellar mass in z ∼ 0.8 quiescent galaxies and we conclude that rejuvenation is not an important evolutionary channel when considering the growth of the red sequence. However, our results complicate the interpretation of galaxy demographics in color space: the galaxies with rejuvenation events tend to lie in the so-called “green valley,” yet their progenitors were quiescent at z ∼ 2.
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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 | 0.001 |
| 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".