Quiescent galaxies in clusters are older than those in the field at z>1: Implications for quenching
Bibliographic record
Abstract
Galaxies in dense clusters experience additional quenching processes compared to field galaxies, which are subject only to secular processes. Timescales of quenching processes can be used to constrain the physical mechanisms which suppress star formation. With the Gemini Observation of Galaxies in Rich Early Environments (GOGREEN) survey, we have collected a sample of ~300 spectra of quiescent galaxies (~200 in clusters) at z=1-1.5 -- when the star formation rate was twice as high as it is today. We explore the differences of the populations, as a function of both environment and mass, through modelling their star formation histories. We confirm that in general there is mass-dependent evolution, and add to this picture that at fixed mass galaxies in the field have overall longer star forming time scales and later formation times. We try to explain this age difference through two scenarios, i) galaxies in clusters formed earlier or ii) galaxies in clusters experience environmental quenching post-infall, and find that neither are sufficient (without preprocessing) in simultaneously predicting the observed age difference and quenched fractions. This is distinctly different from local clusters, for which quenching of recently accreted field galaxies plays an important role, particularly at low stellar masses. Our results suggest that the quenched population in galaxy clusters at redshifts above one has been driven by different physical processes than those at play locally.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".