Overconsumption, outflows and the quenching of satellite galaxies
Bibliographic record
Abstract
Abstract The baryon cycle of galaxies is a dynamic process involving the intake, consumption and ejection of vast quantities of gas. In contrast, the conventional picture of satellite galaxies has them methodically turning a large gas reservoir into stars until this reservoir is forcibly removed due to external ram pressure. This picture needs revision. Our modern understanding of the baryon cycle suggests that in some regimes the simple interruption of the fresh gas supply may quench satellite galaxies long before stripping events occur, a process we call overconsumption. We compile measurements from the literature of observed satellite quenching times at a range of redshifts to determine if satellites are principally quenched through orbit-based gas stripping events – either direct stripping of the disc (ram pressure stripping) or the extended gas halo (strangulation) – or from internally driven star formation outflows via overconsumption. These time-scales show significant deviations from the evolution expected for gas stripping mechanisms and suggest that either ram pressure stripping is much more efficient at high redshift, or that secular outflows quench satellites before orbit-based stripping occurs. Given the strong redshift evolution of star formation rates, at high redshift even moderate outflow rates will lead to extremely short delay times with the expectation that high-redshift (z > 1.5) satellites will be quenched almost immediately following the cessation of cosmological inflow. Observations of high-redshift satellites give an indirect but sensitive measure of the outflow rate, with current measurements suggesting that outflows are no larger than 2.5 times the star formation rate for galaxies with a stellar mass of 1010.5 M⊙.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".