<i>SWIFT</i> STUDY OF THE FIRST SOFT γ-RAY REPEATER LIKE BURST FROM AXP 1E 1841-045 IN SNR Kes 73
Bibliographic record
Abstract
We report the study of the short (32 ms) and first soft γ-ray repeater like burst observed from the anomalous X-ray pulsar (AXP) 1E 1841–045 associated with the supernova remnant Kes 73, discovered on 2010 May 6 by the Burst Alert Telescope on board the Swift γ-ray observatory. The 15–100 keV time-averaged burst spectrum is modeled by a single power law (PL) with a photon index Γ = 3.2 +1.8 −1.0 and has a fluence of 1.1 +0.4 −0.6 × 10 −8 erg cm −2 , a luminosity of 2.9 +1.1 −1.6 × 10 39 erg s −1 , and an energy of 7.2 +0.4 −0.6 × 10 36 erg. The prompt after-burst 0.5–10 keV quiescent spectrum obtained with the Swift X-ray Telescope (XRT) is best fit by an absorbed PL model with Γ = 2.6 ± 0.2 and an unabsorbed flux of 9.1 +1.2 −1.4 × 10 −11 erg cm −2 s −1 . To investigate the pre-burst 0.5–10 keV persistent emission, we analyzed the archival XMM-Newton observations, and the spectra are well fitted by a two-component blackbody plus PL model with a temperature kT = 0.45 ± 0.03 keV, Γ = 1.9 ± 0.2, and an unabsorbed flux of 4.3 +0.9 −1.2 × 10 −11 erg cm −2 s −1 . Comparing the Swift -XRT spectrum with the XMM-Newton spectrum, spectral softening post-burst is evident with a 2.1 times increase in the unabsorbed flux. We discuss the burst activity and the persistent emission properties of AXP 1E 1841–045 in comparison with other magnetars and in the context of the magnetar model.
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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 | 0.000 | 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".