THE NEXT GENERATION VIRGO CLUSTER SURVEY. V. MODELING THE DYNAMICS OF M87 WITH THE MADE-TO-MEASURE METHOD
Bibliographic record
Abstract
We study the dynamics of the giant elliptical galaxy M87 from the central to the outermost regions with the made-to-measure (M2M) method. We use a new catalog of 922 globular cluster line-of-sight velocities extending to a projected radius of 180 kpc (equivalent to 25 M87 effective radii), and SAURON integral field unit data within the central 2.4 kpc. There are 263 globular clusters, mainly located beyond 40 kpc, newly observed by the Next Generation Virgo Survey. For the M2M modeling, the gravitational potential is taken as a combination of a luminous matter potential with a constant stellar mass-to-light ratio and a dark matter potential modeled as a logarithmic potential. Our best-fit dynamical model returns a stellar mass-to-light ratio in the I band of M / L I = 6.0 ± 0.3 with a dark matter potential scale velocity of 591 ± 50 km s −1 and scale radius of 42 ± 10 kpc. We determine the total mass of M87 within 180 kpc to be (1.5 ± 0.2) × 10 13 M ☉ . The mass within 40 kpc is smaller than previous estimates determined using globular cluster kinematics that did not extend beyond ∼45 kpc. With our new globular cluster velocities at much larger radii, we see that globular clusters around 40 kpc show an anomalously large velocity dispersion which affected previous results. The mass we derive is in good agreement with that inferred from ROSAT X-ray observation out to 180 kpc. Within 30 kpc our mass is also consistent with that inferred from Chandra and XMM-Newton X-ray observations, while within 120 kpc it is about 20% smaller. The model velocity dispersion anisotropy β parameter for the globular clusters in M87 is small, varying from −0.2 at the center to 0.2 at ∼40 kpc, and gradually decreasing to zero at ∼120 kpc.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".