Are Am stars and hot-Jupiter planets related?
Bibliographic record
Abstract
Context. Metallic-lined A stars (Am stars) are often components of short-period binary systems, where tidal interactions would result in low rotational velocities and help to develop the chemical peculiarities observed. However, the origin of single Am stars and Am stars that belong to wide binary systems is unclear. Aims. There is very recent evidence of an Am star hosting a likely synchronized hot brown dwarf (hot BD) and other possible Am stars hosting hot Jupiter planets. Following literature suggestions, we wonder if these hot low-mass companions could play a role in the development of an Am star, that is to say, if they could help to mitigate the “single Am” problem. Methods. We carried out a detailed abundance determination via spectral synthesis of 19 early-type stars hosting hot BDs and hot Jupiter planets, in order to determine the possible presence of Am stars in this sample. The abundances were determined iteratively for 25 different species by fitting synthetic spectra using the SYNTHE program together with local thermodynamic equilibrium (LTE) ATLAS12 model atmospheres. The abundances of C I, O I, and Mg I were corrected by non-LTE effects. The complete chemical patterns of the stars were then compared to those of Am stars and other chemically peculiar stars. Results. We studied a sample of 19 early-type stars, seven of them hosting hot BDs and 12 of them hosting hot Jupiter planets. We detected four Am stars in our sample (KELT-19A, KELT-17, HATS-70, and TOI-503) and two possible Am stars (TOI-681 and HAT-P-69). In particular, we detected the new Am star HATS-70, which hosts a hot BD, and we ruled out this class for the hot Jupiter host, WASP-189. Both stars show a different composition than previously reported. For the first time, we estimated the incidence of Am stars among stars hosting hot BDs (50−75%) and among stars hosting hot Jupiters (20−42%). The incidence of Am stars hosting hot BDs has shown to be higher than the frequency of Am stars in general. This would imply that the presence of hot BDs could play a role in the development of Am stars and possibly help to mitigate the single Am problem, which is different for the case of hot Jupiter planets. Notably, these results also indicate that the search for hot BDs may benefit from the targeting of single Am stars or Am stars in wide binary systems. We encourage the analysis of additional early-type stars hosting hot companions in order to improve the significance of the initial trends found here.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".