Towards a physical picture of star formation quenching: the photometric properties of recently quenched galaxies in the Sloan Digital Sky Survey
Bibliographic record
Abstract
We select a sample of young passive galaxies from the Sloan Digital Sky Survey data release 7 in order to study the processes that quench star formation in the local universe. Quenched galaxies are identified based on the contribution of A-type stars to their observed (central) spectra and relative lack of ongoing star formation; we find that such systems account for roughly 2.5 per cent of all galaxies with |$ \log ( M/{\mathrm M}_{\odot }) \ge 9.5$|, and have a space density of ∼2.2 × 10−4 Mpc−3. We show that quenched galaxies span a range of morphologies, but visual classifications suggest that they are predominantly early-type systems. Their visual early-type classification is supported by quantitative structural measurements (Sérsic indices) that show a notable lack of disc-dominated galaxies, suggesting that any morphological transformation associated with galaxies’ transition from star forming to passive – e.g. the formation of a stellar bulge – occurs contemporaneously with the decline of their star formation activity. We show that there is no clear excess of optical active galactic nuclei (AGN) in quenched galaxies, suggesting that: (i) AGN feedback is not associated with the majority of quenched systems or (ii) that the observability of quenched galaxies is such that the quenching phase in general outlives any associated nuclear activity. Comparison with classical post-starburst galaxies shows that both populations show similar signatures of bulge growth, and we suggest that the defining characteristic of post-starburst galaxies is the efficiency of their bulge growth rather than a particular formation mechanism.
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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".