The SLUGGS Survey: stellar kinematics, kinemetry and trends at large radii in 25 early-type galaxies
Bibliographic record
Abstract
Due to longer dynamical time-scales, the outskirts of early-type galaxies retain the footprint of their formation and assembly. Under the popular two-phase galaxy formation scenario, an initial in situ phase of star formation is followed by minor merging and accretion of ex situ stars leading to the expectation of observable transitions in the kinematics and stellar populations on large scales. However, observing the faint galactic outskirts is challenging, often leaving the transition unexplored. The large-scale, spatially resolved stellar kinematic data from the SAGES Legacy Unifying Galaxies and GlobularS (SLUGGS) survey are ideal for detecting kinematic transitions. We present kinematic maps out to 2.6 effective radii on average, kinemetry profiles, measurement of kinematic twists and misalignments, and the average outer intrinsic shape of 25 SLUGGS galaxies. We find good overall agreement in the kinematic maps and kinemetry radial profiles with literature. We are able to confirm significant radial modulations in rotational versus pressure support of galaxies with radius so that the central and outer rotational properties may be quite different. We also test the suggestion that galaxies may be more triaxial in their outskirts and find that while fast rotating galaxies were already shown to be axisymmetric in their inner regions, we are unable to rule out triaxiality in their outskirts. We compare our derived outer kinematic information to model predictions from a two-phase galaxy formation scenario. We find that the theoretical range of local outer angular momentum agrees well with our observations, but that radial modulations are much smaller than predicted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".