AN ANALYSIS OF THE PULSATING STAR SDSS J160043.6+074802.9 USING NEW NON-LTE MODEL ATMOSPHERES AND SPECTRA FOR HOT O SUBDWARFS
Bibliographic record
Abstract
We first present our new grids of model atmospheres and spectra for hot subdwarf O (sdO) stars: standard non-LTE (NLTE) H+He models with no metals, NLTE line-blanketed models with C+N+O, and NLTE line-blanketed models with C+N+O+Fe. Using hydrogen and helium lines in the optical range, we make detailed comparisons between theoretical spectra of different grids in order to characterize the line-blanketing effects of metals. We find these effects to be dependent on both the effective temperature and the surface gravity. Moreover, we find that the helium abundance also influences in an important way the effects of line blanketing on the resulting spectra. We further find that the addition of Fe (solar abundance) leads only to incremental effects on the atmospheric structure as compared with the case where the metallicity is defined by C+N+O (solar abundances). We use our grids to perform fits on a 9 Å resolution, high signal-to-noise ratio (∼300 blueward of 5000 Å) optical spectrum of SDSS J160043.6+074802.9, the only known pulsating sdO star. Our best and most reliable result is based on the fit achieved with NLTE synthetic spectra that include C, N, O, and Fe in solar abundances, leading to the following parameters : T eff = 68,500 ± 1770 K, log g = 6.09 ± 0.07, and log N (He)/ N (H) = −0.64 ± 0.05 (formal fitting errors only). This combination of parameters, particularly the comparatively high helium abundance, implies that line-blanketing effects due to metals are not very large in the atmosphere of this sdO star.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".