The fate of the interstellar medium in early-type galaxies. III. The mechanism of ISM removal and quenching of star formation
Bibliographic record
Abstract
Understanding how galaxies quench their star formation is crucial for studies of galaxy evolution. Quenching is related to the cold gas decrease. In the first paper we showed that the dust removal timescale in early-type galaxies (ETGs) is about 2.5 Gyr. Here we present carbon monoxide (CO) and 21 cm hydrogen (H I) line observations of these galaxies and measure the timescale of removal of the cold interstellar medium (ISM). We find that all the cold ISM components (dust, molecular and atomic gas) decline at similar rates. This allows us to rule out a wide range of potential ISM removal mechanisms (including starburst-driven outflows, astration, a decline in the number of asymptotic giant branch stars), and artificial effects like stellar mass-age correlation, environmental influence, mergers, and selection bias, leaving ionization by evolved low-mass stars and ionization/outflows by supernovae Type Ia or active galactic nuclei as viable mechanisms. We also provide evidence for an internal origin of the detected ISM. Moreover, we find that the quenching of star formation in these galaxies cannot be explained by a reduction in gas amount alone, because the star formation rates (SFRs) decrease faster (on a timescale of about 1.8 Gyr) than the amount of cold gas. Furthermore, the star formation efficiency of the ETGs (SFE = SFR/MH2) is lower than that of star-forming galaxies, whereas their gas mass fractions (fH2 = MH2/M*) are normal. This may be explained by the stabilization of gas against fragmentation, for example due to morphological quenching, turbulence, or magnetic fields.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".