Progenitors and explosion properties of supernova remnants hosting central compact objects: I. RCW 103 associated with the peculiar source 1E 161348−5055
Bibliographic record
Abstract
ABSTRACT We present a Chandra and XMM–Newton imaging and spectroscopic study of the supernova remnant (SNR) RCW 103 (G332.4−00.4) containing the central compact object 1E 161348−5055. The high-resolution Chandra X-ray images reveal enhanced emission in the south-eastern and north-western regions. Equivalent width line images of Fe L, Mg, Si, and S using XMM–Newton data were used to map the distribution of ejecta. The SNR was sectioned into 56 regions best characterized by two-component thermal models. The harder component (kT ∼ 0.6 keV) is adequately fitted by the VPSHOCK non-equilibrium ionization model with an ionization time-scale net ∼ 1011–1012 cm−3 s, and slightly enhanced abundances over solar values. The soft component (kT ∼ 0.2 keV), fitted by the APEC model, is well described by plasma in collisional ionization equilibrium with abundances consistent with solar values. Assuming a distance of 3.1 kpc and a Sedov phase of expansion into a uniform medium, we estimate an SNR age of 4.4 kyr, a swept-up mass Msw = 16$f_\mathrm{ s}^{-1/2}$ D$_{3.1}^{5/2}$ M⊙, and a low explosion energy E* = 3.7 × 1049 $f_\mathrm{ s}^{-1/2}$ D$_{3.1}^{5/2}$ erg. This energy could be an order of magnitude higher if we relax the Sedov assumption, the plasma has a low filling factor, the plasma temperature is underestimated, or if the SNR is expanding into the progenitor’s wind-blown bubble. Standard explosion models did not match the ejecta yields. By comparing the fitted abundances to the most recent core-collapse nucleosynthesis models, our best estimate yields a low-mass progenitor of around 12–13 M⊙, lower than previously reported. We discuss degeneracies in the model fitting, particularly the effect of altering the explosion energy on the progenitor mass estimate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".