DISCRIMINATING THE PROGENITOR TYPE OF SUPERNOVA REMNANTS WITH IRON K-SHELL EMISSION
Bibliographic record
Abstract
Supernova remnants (SNRs) retain crucial information about both their parent explosion and circumstellar material left behind by their progenitor. However, the complexity of the interaction between supernova ejecta and ambient medium often blurs this information, and it is not uncommon for the basic progenitor type (Ia or core-collapse) of well-studied remnants to remain uncertain. Here we present a powerful new observational diagnostic to discriminate between progenitor types and constrain the ambient medium density of SNRs using solely Fe K-shell X-ray emission. We analyze all extant Suzaku observations of SNRs and detect Fe Kα emission from 23 young or middle-aged remnants, including five first detections (IC 443, G292.0+1.8, G337.2–0.7, N49, and N63A). The Fe Kα centroids clearly separate progenitor types, with the Fe-rich ejecta in Type Ia remnants being significantly less ionized than in core-collapse SNRs. Within each progenitor group, the Fe Kα luminosity and centroid are well correlated, with more luminous objects having more highly ionized Fe. Our results indicate that there is a strong connection between explosion type and ambient medium density, and suggest that Type Ia supernova progenitors do not substantially modify their surroundings at radii of up to several parsecs. We also detect a K-shell radiative recombination continuum of Fe in W49B and IC 443, implying a strong circumstellar interaction in the early evolutionary phases of these core-collapse remnants.
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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 | 0.001 |
| 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 | 0.001 | 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".