The Peculiar Radial Distribution of Multiple Populations in the Massive Globular Cluster M80
Bibliographic record
Abstract
Abstract We present a detailed analysis of the radial distribution of light-element multiple populations (LE-MPs) in the massive and dense globular cluster M80, based on a combination of UV and optical Hubble Space Telescope data. Surprisingly, we find that first-generation (FG) stars (FG) are significantly more centrally concentrated than extreme second-generation (SG) stars out to ∼2.5r h from the cluster center. To understand the origin of such peculiar behavior, we used a set of N-body simulations following the long-term dynamical evolution of LE-MPs. We find that, given the advanced dynamical state of the cluster, the observed difference does not depend on the primordial relative distributions of FG and SG stars. On the contrary, a difference of ∼0.05–0.10 M ⊙ between the average masses of the two subpopulations is needed to account for the observed radial distributions. We argue that such a mass difference might be the result of the higher He abundance of SG stars (of the order of ΔY ∼ 0.05–0.06) with respect to FG stars. Interestingly, we find that a similar He variation is necessary to reproduce the horizontal branch morphology of M80. These results demonstrate that differences in mass among LE-MPs, due to different He content, should be properly taken into account for a correct interpretation of their radial distribution, at least in dynamically evolved systems.
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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".