Calcium in a supernova remnant as a fingerprint of a sub-Chandrasekhar-mass explosion
Bibliographic record
Abstract
Type Ia supernovae play a fundamental role as cosmological probes of dark energy and produce more than half of the iron in our Galaxy. Despite their central importance, a comprehensive understanding of their progenitor systems and triggering mechanism is still a long-standing fundamental problem. Here we present high-resolution integral field spectroscopic observations of the young supernova remnant SNR 0509-67.5 in the Large Magellanic Cloud. We uncover a double-shell morphology of highly ionized calcium [Ca XV] and a single shell of sulphur [S XII], observed in the reverse shocked ejecta. Our analysis reveals that the outer calcium shell originates from the helium detonation at the base of the outer envelope, while the inner shell is associated with the carbon-oxygen core detonation. This morphological distribution of intermediate-mass elements agrees qualitatively with the predicted signature of the double detonation of a sub-Chandrasekhar-mass white dwarf from a hydrodynamical explosion simulation. Our observations reveal two distinct, spatially separated peaks in surface brightness of [Ca XV] from the supernova remnant phase, providing substantial evidence that sub-Chandrasekhar-mass explosions through the double-detonation mechanism could occur in nature. They also highlight the importance of remnant tomography in understanding explosion mechanisms from the remnant phase.
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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".