Wide‐Field Survey of Globular Clusters in M31. II. Kinematics of the Globular Cluster System
Bibliographic record
Abstract
We present a kinematic analysis of the globular cluster (GC) system in M31, using the velocity data for 504 GCs including those for 150 GCs in our wide-field survey. The all GC system shows strong rotation, with rotation amplitude of v rot ∼ 190 km s −1 , and weak rotation persists even for the outermost samples at | Y| ⩾ 5 kpc, where Y represents the projected distance from the major axis. The rotation-corrected velocity dispersion for the GC system is estimated to be σ p,r ∼ 130 km s −1 , and it increases from σ p,r ∼ 120 km s −1 at | Y| < 1 kpc to σ p,r ∼ 150 km s −1 at | Y| ⩾ 5 kpc. These results are very similar to those for the metal-poor GCs. This shows that there is a dynamically hot halo in M31 that is rotating but primarily pressure-supported. We have identified 50 "friendless" GCs, and they appear to rotate around the major axis of M31. Both metal-rich GCs and metal-poor GCs show strong rotation in the inner region. The rotation for the faint GCs is stronger than that for the bright GCs. We have identified 56 GCs and GC candidates with X-ray detection including 39 GCs with measured velocities. The majority of X-ray-emitting GCs follow the disk rotation. We have derived a rotation curve of M31 using the GCs at | Y| ⩽ 0.6 kpc. We have estimated the dynamical mass of M31 using "Projected Mass Estimator (PME)" and "Tracer Mass Estimator (TME)" as M PME = 5.5 + 0.4 −0.3 × 10 11 M ☉ out to a radius of ~55 kpc and M TME = 19.2 + 1.4 −1.3 × 10 11 M ☉ for a radius of ~100 kpc, respectively. We finally discuss the implication of these results and compare the kinematics of GCs with that of planetary nebulae in M31.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".