Dependence of galaxy quenching on halo mass and distance from its centre
Bibliographic record
Abstract
We study the dependence of star formation quenching on galaxy mass and environment, in the Sloan Digital Sky Survey (SDSS; z ∼ 0.1) and the All-Wavelength Extended Groth Strip International Survey (AEGIS; z ∼ 1). It is crucial that we define quenching by low star formation rate rather than by red colour, given that one-third of the red galaxies are star forming. We address stellar mass M*, halo mass Mh, density over the nearest N neighbours δN and distance to the halo centre D. The fraction of quenched galaxies appears more strongly correlated with Mh at fixed M* than with M* at fixed Mh, while for satellites quenching also depends on D. We present the M*–Mh relation for centrals at z ∼ 1. At z ∼ 1, the dependence of quenching on M* at fixed Mh is somewhat more pronounced than at z ∼ 0, but the quenched fraction is low (10 per cent) and the haloes are less massive. For satellites, M*-dependent quenching is noticeable at high D, suggesting a quenching dependence on subhalo mass for recently captured satellites. At small D, where satellites likely fell in more than a few Gyr ago, quenching strongly depends on Mh and not on M*. The Mh dependence of quenching is consistent with theoretical wisdom where virial shock heating in massive haloes shuts down accretion and triggers ram-pressure stripping, causing quenching. The interpretation of δN is complicated by the fact that it depends on the number of observed group members compared to N, motivating the use of D as a better measure of local environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".