<i>NuSTAR</i> and <i>Swift</i> observations of two supergiant fast X-ray transients: AX J1841.0−0536 and SAX J1818.6−1703
Bibliographic record
Abstract
ABSTRACT Supergiant fast X-ray transients are wind-fed binaries hosting neutron star accretors, which display a peculiar variability in the X-ray domain. Different models have been proposed to explain this variability and the strength of the compact object magnetic field is generally considered a key parameter to discriminate among possible scenarios. We present here the analysis of two simultaneous observational campaigns carried out with Swift and NuSTAR targeting the supergiant fast X-ray transient sources AX J1841.0−0536 and SAX J1818.6−1703. A detailed spectral analysis is presented for both sources, with the main goal of hunting for cyclotron resonant scattering features that can provide a direct measurement of the neutron star magnetic field intensity. AX J1841.0−0536 was caught during the observational campaign at a relatively low flux. The source broad-band spectrum was featureless and could be well-described by using a combination of a hot blackbody and a power-law component with no measurable cut-off energy. In the case of SAX J1818.6−1703, the broad-band spectrum presented a relatively complex curvature which could be described by an absorbed cut-off power law (including both a cut-off and a folding energy) and featured a prominent edge at ∼7 keV, compatible with being associated to the presence of a ‘screen’ of neutral material partly obscuring the X-ray source. The fit to the broad-band spectrum also required the addition of a moderately broad (∼1.6 keV) feature centred at ∼14 keV. If interpreted as a cyclotron resonant scattering feature, our results would indicate for SAX J1818.6−1703 a relatively low-magnetized neutron star (∼1.2 × 1012 G).
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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 | 0.001 | 0.001 |
| 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".