A SEARCH FOR RAPIDLY ACCRETING WHITE DWARFS IN THE SMALL MAGELLANIC CLOUD
Bibliographic record
Abstract
The nature of the progenitors of Type Ia supernovae (SNe Ia) is still a mystery. While plausible candidates are known for both the single-degenerate and double-degenerate models, the observed numbers fall significantly short of what is required to reproduce the SNe Ia rate. Some of the most promising single-degenerate Type Ia progenitors are recurrent novae and super-soft sources (SSS). White dwarfs (WDs) with higher mass transfer rates can also be SN Ia progenitors. For these rapidly accreting white dwarfs (RAWDs), more material than is needed for steady burning accretes on the WD, and extends the WD's photosphere. Unlike SSS, such objects will likely not be detectable at soft X-ray energies, but will be bright at longer wavelengths, such as the far-ultraviolet (UV). Possible examples include LMC N66 and the V Sagittae stars. We present a survey using multi-object spectrographs looking for RAWDs in the central core of the Small Magellanic Cloud (SMC), from objects selected to be bright in the far-UV and with blue far UV − V colors. While we find some unusual objects, and recover known planetary nebula and Wolf–Rayet (WR) stars, we detect no candidate RAWD. The upper limits from this non-detection depend on our expectations of what an RAWD should look like, as well assumptions about the internal extinction of the SMC. Assuming they resemble LMC N66 or fainter versions of WR stars we set an upper limit of 10–14 RAWDs in the SMC. However, our survey is unlikely to detect objects like V Sge, and hence we cannot set meaningful upper limits if RAWDs generally resemble V Sge.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".