Dynamical masses of brightest cluster galaxies I: stellar velocity anisotropy and mass-to-light ratios
Bibliographic record
Abstract
ABSTRACT We investigate the stellar and dynamical mass profiles in the centres of 25 brightest cluster galaxies (BCGs) at redshifts of 0.05 ≤ z ≤ 0.30. Our spectroscopy enables us to robustly measure the Gauss–Hermite higher order velocity moments h3 and h4, which we compare to measurements for massive early-type galaxies, and central group galaxies. We measure positive central values for h4 for all the BCGs. We derive the stellar mass-to-light ratio ($\Upsilon _{\star \rm DYN}$), and velocity anisotropy (β) based on a multi-Gaussian expansion (MGE) and axisymmetric Jeans Anisotropic Methods (cylindrically and spherically aligned). We explicitly include a dark matter halo mass component, which is constrained by weak gravitational lensing measurements for these clusters. We find a strong correlation between anisotropy and velocity dispersion profile slope, with rising velocity dispersion profiles corresponding to tangential anisotropy and decreasing velocity dispersion profiles corresponding to radial anisotropy. The rising velocity dispersion profiles can also indicate a significant contribution from the intracluster light (ICL) to the total light (in projection) in the centre of the galaxy. For a small number of BCGs with rising velocity dispersion profiles, a variable stellar mass-to-light ratio can also account for the profile shape, instead of tangential anisotropy or a significant ICL contribution. We note that, for some BCGs, a variable βz(r) (from radial to tangential anisotropy) can improve the model fit to the observed kinematic profiles. The observed diversity in these properties illustrates that BCGs are not the homogeneous class of objects they are often assumed to be.
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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 | 0.000 |
| 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".