The origin of ionized gas in retired galaxies: dynamical clues
Bibliographic record
Abstract
ABSTRACT We investigate the kinematical and dynamical properties of quiescent cluster galaxies with weak emission lines, referred to as retired (R), and those without emission lines, dubbed passive (P), to better understand the origin of the ionized gas in R galaxies and what drives the differences between these populations. We stack 2907 P and 2387 R galaxies from 336 relaxed galaxy clusters to build an ensemble cluster and estimate their projected number density and velocity dispersion profiles, $\sigma _P(R)$, as well as their projected phase-space (PPS) distributions. Additionally, we apply the MAMPOSSt code and the Jeans equation inversion technique to constrain the velocity anisotropy profiles, $\beta (r)$. We find that P galaxies tend to reside closer to the cluster centres than R galaxies, and that both populations exhibit similar $\sigma _P(R)$ and $\beta (r)$ profiles, regardless of their stellar mass, stellar age, or morphology. The only exception is elliptical R galaxies, which are marginally more concentrated and display more radial orbits than their P counterparts. PPS analyses indicate that R galaxies were, on average, accreted later than P galaxies, except for those with $D_n4000 > 1.86$ or elliptical morphology. These results suggest that R galaxies, though accreted more recently, have already had enough time to evolve towards a dynamical state more consistent with that of the dynamically relaxed P population. Finally, our findings suggest that the ionized gas in early-type R galaxies likely originates from accretion from their own hot gas haloes, and that its removal triggers the transition towards the P phase over relatively long time-scales.
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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 | 0.001 |
| 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 | 0.001 |
| 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".