The <i>HST</i> large programme on NGC 6752 – IV. The White Dwarf sequence
Bibliographic record
Abstract
ABSTRACT We present our final study of the white dwarf cooling sequence (WD CS) in the globular cluster NGC 6752. The investigation is the main goal of a dedicated Hubble Space Telescope large program, for which all the observations are now collected. The WD CS luminosity function (LF) is confirmed to peak at mF606W ≃ 29.3 ± 0.1, consistent within uncertainties with what has been previously reported, and is now complete down to mF606W ≃ 29.7. We have performed robust and conclusive comparisons with model predictions that show how the theoretical LF for hydrogen envelope WD models closely follow the shape of the empirical LF. The magnitude of the peak of the observed LF is matched with ages between 12.7 and 13.5 Gyr, consistent with the cluster age derived from the main sequence turn off and subgiant branch. We also find that the impact of multiple populations within the cluster on the WD LF for mF606W below 27.3 is negligible, and that the presence of a small fraction of helium envelope objects is consistent with the data. Our analysis reveals a possible hint of an underestimate of the cooling time-scales of models in the magnitude range 28.1 < mF606W < 28.9. Finally, we find that hydrogen envelope models calculated with a new tabulation of electron conduction opacities in the transition between moderate and strong degeneracy provide WD ages that are too small in comparison to the main sequence turnoff age.
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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 | 0.000 | 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) | 0.003 | 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".