Determining the Halo Mass Scale Where Galaxies Lose Their Gas<sup>*</sup>
Bibliographic record
Abstract
Abstract A major question in galaxy formation is how the gas supply that fuels activity in galaxies is modulated by their environment. We use spectroscopy of a set of well-characterized clusters and groups at 0.4 < z < 0.8 from the ESO Distant Cluster Survey and compare it to identically selected field galaxies. Our spectroscopy allows us to isolate galaxies that are dominated by old stellar populations. Here we study a stellar-mass-limited sample ( ) of these old galaxies with weak [O ii] emission. We use line ratios and compare to studies of local early-type galaxies to conclude that this gas is likely excited by post-AGB stars and hence represents a diffuse gas component in the galaxies. For cluster and group galaxies the fraction with EW([O ii]) > 5 Å is f [O II] = and f [O II] = , respectively. For field galaxies we find f [O II] = , representing a 2.8σ difference between the [O ii] fractions for old galaxies between the different environments. We conclude that a population of old galaxies in all environments has ionized gas that likely stems from stellar mass loss. In the field galaxies also experience gas accretion from the cosmic web, and in groups and clusters these galaxies have had their gas accretion shut off by their environment. Additionally, galaxies with emission preferentially avoid the virialized region of the cluster in position–velocity space. We discuss the implications of our results, among which is that gas accretion shutoff is likely effective at group halo masses (log / > 12.8) and that there are likely multiple gas removal processes happening in dense environments.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".