The fate of the interstellar medium in early-type galaxies
Bibliographic record
Abstract
Context.An important aspect of quenching star formation is the removal of the cold interstellar medium (ISM; non-ionised gas and dust) from a galaxy. In addition, dust grains can be destroyed in a hot or turbulent medium. The adopted timescale of dust removal usually relies on uncertain theoretical estimates. It is tricky to track dust removal because the dust is constantly being replenished by consecutive generations of stars. Aims.Our objective is to carry out an observational measurement of the timescale of dust removal. Methods.We explored an approach to select galaxies that demonstrate detectable amounts of dust and cold ISM coupled with a low current dust production rate. Any decrease of the dust and gas content as a function of the age of such galaxies must, therefore, be attributed to processes governing ISM removal. We used a sample of the galaxies detected byHerschelin the far-infrared with visually assigned early-type morphology or spirals with red colours. We also obtained JCMT/SCUBA-2 observations for five of these galaxies. Results.We discovered an exponential decline of the dust-to-stellar mass ratio with age, which we interpret as an evolutionary trend for the dust removal of these galaxies. For the first time, we have directly measured the dust removal timescale for such galaxies, with a result ofτ = (2.5 ± 0.4) Gyr (the corresponding half-life time is (1.75 ± 0.25) Gyr). This quantity may be applied to models in which it must be assumed a priori and cannot be derived. Conclusions.Any process which removes dust in these galaxies, such as dust grain destruction, cannot happen on shorter timescales. The timescale is comparable to the quenching timescales found in simulations for galaxies with similar stellar masses. The dust is likely of internal, not external origin. It was either formed in the past directly by supernovae (SNe) or from seeds produced by SNe, and with grain growth in the ISM contributing substantially to the dust mass accumulation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".