The SAURON project - XV. Modes of star formation in early-type galaxies and the evolution of the red sequence
Bibliographic record
Abstract
We combine SAURON integral field data of a representative sample of local early-type, red sequence galaxies with Spitzer/Infrared Array Camera imaging in order to investigate the presence of trace star formation in these systems. With the Spitzer data, we identify galaxies hosting low-level star formation, as traced by polycyclic aromatic hydrocarbon emission, with measured star formation rates that compare well to those estimated from other tracers. This star formation proceeds according to established scaling relations with molecular gas content, in surface density regimes characteristic of disc galaxies and circumnuclear starbursts. We find that star formation in early-type galaxies happens exclusively in fast-rotating systems and occurs in two distinct modes. In the first, star formation is a diffuse process, corresponding to widespread young stellar populations and high molecular gas content. The equal presence of co- and counter-rotating components in these systems strongly implies an external origin for the star-forming gas, and we argue that these star formation events may be the final stages of (mostly minor) mergers that build up the bulges of red sequence lenticulars. In the second mode of star formation, the process is concentrated into well-defined disc or ring morphologies, outside of which the host galaxies exhibit uniformly evolved stellar populations. This implies that these star formation events represent rejuvenations within previously quiescent stellar systems. Evidence for earlier star formation events similar to these in all fast-rotating early-type galaxies suggests that this mode of star formation may be common to all such galaxies, with a duty cycle of roughly 1/10, and likely contributes to the embedded, corotating inner stellar discs ubiquitous in this population.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".