CALIBRATION OF THE <i>NuSTAR</i> HIGH-ENERGY FOCUSING X-RAY TELESCOPE
Bibliographic record
Abstract
We present the calibration of the Nuclear Spectroscopic Telescope Array ( NuSTAR ) X-ray satellite. We used the Crab as the primary effective area calibrator and constructed a piece-wise linear spline function to modify the vignetting response. The achieved residuals for all off-axis angles and energies, compared to the assumed spectrum, are typically better than ±2% up to 40 keV and 5%–10% above due to limited counting statistics. An empirical adjustment to the theoretical two-dimensional point-spread function (PSF) was found using several strong point sources, and no increase of the PSF half-power diameter has been observed since the beginning of the mission. We report on the detector gain calibration, good to 60 eV for all grades, and discuss the timing capabilities of the observatory, which has an absolute timing of ±3 ms. Finally, we present cross-calibration results from two campaigns between all the major concurrent X-ray observatories ( Chandra , Swift , Suzaku, and XMM-Newton ), conducted in 2012 and 2013 on the sources 3C 273 and PKS 2155-304, and show that the differences in measured flux is within ∼10% for all instruments with respect to NuSTAR .
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".