The dual role of outflows in quenching satellites of low-mass hosts: NGC 3109
Bibliographic record
Abstract
ABSTRACT While dwarf galaxies observed in the field are overwhelmingly star forming, dwarf galaxies in environments as dense or denser than the Milky Way are overwhelmingly quenched. In this paper, we explore quenching in the lower density environment of the Small-Magellanic-Cloud-mass galaxy NGC 3109 (M$_* \sim 10^8 \, \text{M}_\odot$), which hosts two known dwarf satellite galaxies (Antlia and Antlia B), both of which are ${\rm H}\, \rm{\small I}$ deficient compared to similar galaxies in the field and have recently stopped forming stars. Using a new semi-analytic model in concert with the measured star formation histories and gas masses of the two dwarf satellite galaxies, we show that they could not have been quenched solely by direct ram pressure stripping of their interstellar media, as is common in denser environments. Instead, we find that separation of the satellites from pristine gas inflows, coupled with stellar-feedback-driven outflows from the satellites (jointly referred to as the starvation quenching model), can quench the satellites on time-scales consistent with their likely infall times into NGC 3109’s halo. It is currently believed that starvation is caused by ‘weak’ ram pressure that prevents low-density, weakly bound gas from being accreted on to the dwarf satellite, but cannot directly remove the denser interstellar medium. This suggests that star-formation-driven outflows serve two purposes in quenching satellites in low-mass environments: outflows from the host form a low-density circumgalactic medium that cannot directly strip the interstellar media from its satellites, but is sufficient to remove loosely bound gaseous outflows from the dwarf satellites driven by their own star formation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".