The GOGREEN survey: post-infall environmental quenching fails to predict the observed age difference between quiescent field and cluster galaxies at <i>z</i> &gt; 1
Bibliographic record
Abstract
ABSTRACT We study the star formation histories (SFHs) and mass-weighted ages of 331 UVJ-selected quiescent galaxies in 11 galaxy clusters and in the field at 1 < z < 1.5 from the Gemini Observations of Galaxies in Rich Early ENvironments (GOGREEN) survey. We determine the SFHs of individual galaxies by simultaneously fitting rest-frame optical spectroscopy and broad-band photometry to stellar population models. We confirm that the SFHs are consistent with more massive galaxies having on average earlier formation times. Comparing galaxies found in massive clusters with those in the field, we find galaxies with M* < 1011.3 M⊙ in the field have more extended SFHs. From the SFHs we calculate the mass-weighted ages, and compare age distributions of galaxies between the two environments, at fixed mass. We constrain the difference in mass-weighted ages between field and cluster galaxies to $0.31_{^{-0.33}}^{_{+0.51}}$ Gyr, in the sense that cluster galaxies are older. We place this result in the context of two simple quenching models and show that neither environmental quenching based on time since infall (without pre-processing) nor a difference in formation times alone can reproduce both the average age difference and relative quenched fractions. This is distinctly different from local clusters, for which the majority of the quenched population is consistent with having been environmentally quenched upon infall. Our results suggest that quenched population in galaxy clusters at z > 1 has been driven by different physical processes than those at play at z = 0.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 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".