The impact of galactic properties and environment on the quenching of central and satellite galaxies: a comparison between SDSS, Illustris and L-Galaxies
Bibliographic record
Abstract
We quantify the impact that a variety of galactic and environmental properties have on the quenching of star formation. We collate a sample of ∼400 000 central and ∼100 000 satellite galaxies from the Sloan Digital Sky Survey Data Release 7 (SDSS DR7). Specifically, we consider central velocity dispersion (σ<inf>c</inf>), stellar, halo, bulge and disc mass, local density, bulge-to-total ratio, groupcentric distance and galaxy–halo mass ratio. We develop and apply a new statistical technique to quantify the impact on the quenched fraction (<it>f</it><inf>Quench</inf>) of varying one parameter, while keeping the remaining parameters fixed. For centrals, we find that the <it>f</it><inf>Quench</inf>–σ<inf>c</inf> relationship is tighter and steeper than for any other variable considered. We compare to the Illustris hydrodynamical simulation and the Munich semi-analytic model (L-Galaxies), finding that our results for centrals are qualitatively consistent with their predictions for quenching via radio-mode AGN feedback, hinting at the viability of this process in explaining our observational trends. However, we also find evidence that quenching in L-Galaxies is too efficient and quenching in Illustris is not efficient enough, compared to observations. For satellites, we find strong evidence that environment affects their quenched fraction at fixed central velocity dispersion, particularly at lower masses. At higher masses, satellites behave identically to centrals in their quenching. Of the environmental parameters considered, local density affects the quenched fraction of satellites the most at fixed central velocity dispersion.
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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 | 0.001 |
| 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".