Discovery of an ∼30-yr-duration post-nova pulsating supersoft source in the Large Magellanic Cloud
Bibliographic record
Abstract
ABSTRACT Supersoft X-ray sources (SSS) have been identified as white dwarfs accreting from binary companions and undergoing nuclear burning of the accreted material on their surface. Although expected to be a relatively numerous population from both binary evolution models and their identification as type Ia supernova progenitor candidates, given the very soft spectrum of SSSs relatively few are known. Here we report on the X-ray and optical properties of 1RXS J050526.3−684628, a previously unidentified accreting nuclear-burning white dwarf located in the Large Magellanic Cloud (LMC). XMM–Newton observations enabled us to study its X-ray spectrum and measure for the first time short-period oscillations of ∼170 s. By analysing newly obtained X-ray data by eROSITA, together with Swift observations and archival ROSAT data, we have followed its long-term evolution over the last 3 decades. We identify 1RXS J050526.3−684628 as a slowly evolving post-nova SSS undergoing residual surface nuclear burning, which finally reached its peak in 2013 and is now declining. Though long expected on theoretical grounds, such long-lived residual-burning objects had not yet been found. By comparison with existing models, we find that the effective temperature and luminosity evolution are consistent with an ∼0.7 M⊙ carbon–oxygen white dwarf accreting ${\sim} 10^{-9}~\rm {M}_{\odot }$ yr−1. Our results suggest that there may be many more undiscovered SSSs and ‘missed’ novae awaiting dedicated deep X-ray searches in the LMC and elsewhere.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".