Spatially resolved X-ray study of supernova remnants that host magnetars: Implication of their fossil field origin
Bibliographic record
Abstract
Magnetars are regarded as the most magnetized neutron stars in the Universe. Aiming to unveil what kinds of stars and supernovae can create magnetars, we have performed a state-of-the-art spatially resolved spectroscopic X-ray study of the supernova remnants (SNRs) Kes 73, RCW 103, and N49, which host magnetars 1E 1841−045, 1E 161348−5055, and SGR 0526−66, respectively. The three SNRs are O- and Ne-enhanced and are evolving in the interstellar medium with densities of > 1 − 2 cm−3. The metal composition and dense environment indicate that the progenitor stars are not very massive. The progenitor masses of the three magnetars are constrained to be < 20 M⊙(11–15 M⊙for Kes 73, ≲13 M⊙for RCW 103, and ∼13 − 17 M⊙for N49). Our study suggests that magnetars are not necessarily made from very massive stars, but originate from stars that span a large mass range. The explosion energies of the three SNRs range from 1050erg to ∼2 × 1051erg, further refuting that the SNRs are energized by rapidly rotating (millisecond) pulsars. We report that RCW 103 is produced by a weak supernova explosion with significant fallback, as such an explosion explains the low explosion energy (∼1050erg), small observed metal masses (MO ∼ 4 × 10−2 M⊙andMNe ∼ 6 × 10−3 M⊙), and sub-solar abundances of heavier elements such as Si and S. Our study supports the fossil field origin as an important channel to produce magnetars, given the normal mass range (MZAMS < 20 M⊙) of the progenitor stars, the low-to-normal explosion energy of the SNRs, and the fact that the fraction of SNRs hosting magnetars is consistent with the magnetic OB stars with high fields.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".