Canada-France-Hawaii Telescope Adaptive Optics Observations of the Central Kinematics in M15
Bibliographic record
Abstract
We have used an Imaging Fabry-Perot Spectrophotometer with the Adaptive Optics Bonnette on the Canada-France-Hawaii Telescope to measure stellar radial velocities in the globular cluster M15 (NGC 7078). An average seeing of 0 15 FWHM, with the best-seeing image having 0 09, allowed us to measure accurately the velocities for five stars within 1'' of the center of M15. Our estimate of the second moment of the velocity distribution (i.e., the dispersion, ignoring rotation) inside a radius of 2'' is 11.5 km s -1 , the same value we find out to a radius of about 6''. However, the projected net rotation does increase dramatically at small radii, as our previous observations led us to suspect. The rotation amplitude inside a radius of 3 4 is v = 10.4 ± 2.7 km s -1 and the dispersion after removing the rotation is σ = 10.3 ± 1.4 km s -1 , so v /σ ≃ 1 in this region. In addition, the position angle of the projected rotation axis differs by 100° from that of the net cluster rotation at larger radii. Current theoretical models do not predict either this large an increase in the rotation amplitude or such a change in the position angle. However, a central mass concentration, such as a black hole, could possibly sustain such a configuration. The rotation increase is consistent with the existence of a central dark mass concentration equal to 2500 M ⊙ . The Strehl ratio is 1% in our worst images and 6% in our best. Despite these low values, the images allow us to resolve the brighter stars with an angular resolution close to the diffraction limit and to perform photometry on these stars accurate to a few percent. Thus, these adaptive optics observations provide us with crucial information on the central kinematics of M15.
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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 | 0.001 | 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 | 0.000 |
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".