Star Counts in the Globular Cluster ω Centauri. I. Bright Stellar Components
Bibliographic record
Abstract
We present a photometric investigation on HB, RGB, and MSTO stars in ω Cen=NGC 5139. The center of the cluster was covered with a mosaic of F435W, F625W, and F658N band data collected with HST ACS. The outer reaches were covered with a mosaic of U -, B -, V -, and I -band data collected with the 2.2 m ESO/MPI telescope. The final catalog includes ~1.7 million stars. We identified more than 3200 likely HB stars, the largest sample ever collected in a globular cluster. We found that the HB morphology changes with the radial distance from the cluster center. The relative number of extreme HB stars decreases from ~30% to ~21% when moving from the center toward the outer reaches of the cluster, while the fraction of less hot HB stars increases from ~62% to ~72%. The comparison between theory and observations indicates that the empirical star counts of HB stars are on average larger (30%-40%) than predicted by canonical evolutionary models. Moreover, the rate of HB stars is ~43% larger than the MSTO rate. We also compared theory and observations by assuming a mix of stellar populations made with 70% of canonical He ( Y = 0.23) stars and 30% of He-enhanced ( Y = 0.33, 0.42) stars. We found that the observed RG/MSTO ratio agrees with the predicted lifetimes of He-mixed stellar populations. The discrepancy between theory and observations decreases by a factor of 2 when compared with rates predicted by canonical He content models, but still 15%-25% ( Y = 0.42) and 15%-20% ( Y = 0.33) higher than observed. Furthermore, the ratios between HB and MSTO star counts are ~24% ( Y = 0.42) and 30% ( Y = 0.33) larger than predicted lifetime ratios.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".