On the RR Lyrae Stars in Globulars. V. The Complete Near-infrared (JHK<sub>s</sub>) Census of ω Centauri RR Lyrae Variables*
Bibliographic record
Abstract
Abstract We present a new complete near-infrared (NIR, JHK s ) census of RR Lyrae stars (RRLs) in the globular ω Cen (NGC 5139). We collected 15,472 JHK s images with 4–8 m class telescopes over 15 years (2000–2015) covering a sky area around the cluster center of 60 × 34 arcmin2. These images provided calibrated photometry for 182 out of the 198 cluster RRL candidates with 10 to 60 measurements per band. We also provide new homogeneous estimates of the photometric amplitude for 180 (J), 176 (H) and 174 (K s ) RRLs. These data were supplemented with single-epoch JK s magnitudes from VHS and with single-epoch H magnitudes from 2MASS. Using proprietary optical and NIR data together with new optical light curves (ASAS-SN) we also updated pulsation periods for 59 candidate RRLs. As a whole, we provide JHK s magnitudes for 90 RRab (fundamentals), 103 RRc (first overtones) and one RRd (mixed-mode pulsator). We found that NIR/optical photometric amplitude ratios increase when moving from first overtone to fundamental and to long-period (P > 0.7 days) fundamental RRLs. Using predicted period–luminosity–metallicity relations, we derive a true distance modulus of 13.674 ± 0.008 ± 0.038 mag (statistical error and standard deviation of the median) based on spectroscopic iron abundances, and of 13.698 ± 0.004 ± 0.048 mag based on photometric iron abundances. We also found evidence of possible systematics at the 5%–10% level in the zero-point of the period–luminosity relations based on the five calibrating RRLs whose parallaxes had been determined with the HST.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".