Field blue straggler stars: discovery of white dwarf companions to blue metal-poor stars using UVIT/AstroSat
Bibliographic record
Abstract
ABSTRACT Blue metal-poor (BMP) stars are the main-sequence stars that appear bluer and more luminous than normal turn-off stars of metal-poor globular clusters. They are believed to be either field blue straggler stars (FBSS) formed via post-mass transfer mechanism or accreted from dwarf satellite galaxies of the Milky Way. A significant fraction of BMP stars are discovered to be potential binaries. We observed 27 BMP stars using UVIT/AstroSat in two FUV filters, F148W and F169M. We report the discovery of white dwarf (WD) companions of 12 BMP stars for the first time. The WD companions have estimated temperatures Teff ∼10 500–18 250 K, and masses 0.17–0.8 M⊙. Based on [Fe/H] and space velocity, we group the 12 BMP/FBSS stars as the thick disc (5) and halo (5), whereas two stars appear to be in-between. All the 5 thick disc BMP/FBSS have extremely low-mass (M < 0.2 M⊙) WDs as companions, whereas the 5 halo BMP/FBSS have low (0.2 M⊙ < M < 0.4 M⊙), normal (0.4 M⊙ < M < 0.6 M⊙), and high mass (M > 0.6 M⊙) WD companions. Our analysis suggests that at least ∼44 ${{\ \rm per\ cent}}$ of BMP stars are FBSS, and these stars hold the key to understand the details of mass transfer, binary properties, and chemical enrichment among the FBSS.
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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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".