NuSTAR Results and Future Plans for Magnetar and Rotation-Powered Pulsar Observations
Bibliographic record
Abstract
The Nuclear Spectroscopic Telescope Array (NuSTAR) is the first focusing hard X-ray mission in orbit and operates in the 3-79 keV range. NuSTAR's sensitivity is roughly two orders of magnitude better than previous missions in this energy band thanks to its superb angular resolution. Since its launch in 2012 June, NuSTAR has performed excellently and observed many interesting sources including four magnetars, two rotation-powered pulsars and the cataclysmic variable AE Aquarii. NuSTAR also discovered 3.76-s pulsations from the transient source SGR J1745-29 recently found by Swift very close to the Galactic center, clearly identifying the source as a transient magnetar. For magnetar 1E 1841-045, we show that the spectrum is well fit by an absorbed blackbody plus broken power-law model with a hard power-law photon index of approximately 1.3. This is consistent with previous results by INTEGRAL and RXTE. We also find an interesting double-peaked pulse profile in the 25-35 keV band. For AE Aquarii, we show that the spectrum can be described by a multi-temperature thermal model or a thermal plus non-thermal model; a multi-temperature thermal model without a non-thermal component cannot be ruled out. Furthermore, we do not see a spiky pulse profile in the hard X-ray band, as previously reported based on Suzaku observations. For other magnetars and rotation-powered pulsars observed with NuSTAR, data analysis results will be soon available.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.017 |
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".