X-ray bounds on cooling, composition, and magnetic field of the Cassiopeia A neutron star and young central compact objects
Bibliographic record
Abstract
ABSTRACT We present analysis of multiple Chandra and XMM–Newton spectra, separated by 9–19 yr, of four of the youngest central compact objects (CCOs) with ages <2500 yr: CXOU J232327.9+584842 (Cassiopeia A), CXOU J160103.1−513353 (G330.2+1.0), 1WGA J1713.4−3949 (G347.3−0.5), and XMMU J172054.5−372652 (G350.1−0.3). By fitting these spectra with thermal models, we attempt to constrain each CCO’s long-term cooling rate, composition, and magnetic field. For the CCO in Cassiopeia A, 14 measurements over 19 yr indicate a decreasing temperature at a 10-yr rate of 2.2 ± 0.2 or 2.8 ± 0.3 per cent (1σ error) for a constant or changing X-ray absorption, respectively. We obtain cooling rate upper limits of 17 per cent for CXOU J160103.1−513353 and 6 per cent for XMMU J172054.5−372652. For the oldest CCO, 1WGA J1713.4−3949, its temperature seems to have increased by 4 ± 2 per cent over a 10-yr period. Assuming each CCO’s preferred distance and an emission area that is a large fraction of the total stellar surface, a non-magnetic carbon atmosphere spectrum is a good fit to spectra of all four CCOs. If distances are larger and emission areas are somewhat smaller, then equally good spectral fits are obtained using a hydrogen atmosphere with B ≤ 7 × 1010 G or B ≥ 1012 G for CXOU J160103.1−513353 and B ≤ 1010 G or B ≥ 1012 G for XMMU J172054.5−372652 and non-magnetic hydrogen atmosphere for 1WGA J1713.4−3949. In a unified picture of CCO evolution, our results suggest most CCOs, and hence a sizable fraction of young neutron stars, have a surface magnetic field that is low early in their life but builds up over several thousand years.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".