<i>Swift</i>/XRT–NuSTAR spectra of type 1 AGN: confirming<i>INTEGRAL</i>results on the high-energy cut-off
Bibliographic record
Abstract
We present the 0.5-78 keV spectral analysis of 18 broad-line AGN belonging to the INTEGRAL complete sample. Using simultaneous Swift-XRT and NuSTAR observations and employing a simple phenomenological model to fit the data, we measure with a good constraint the high-energy cut-off in 13 sources, while we place lower limits on five objects. We found a mean high-energy cut-off of 111 keV (σ = 45 keV) for the whole sample, in perfect agreement with what found in our previous work using non-simultaneous observations and with what recently published using NuSTAR data. This work suggests that simultaneity of the observations in the soft and hard X-ray band is important but not always essential, especially if flux and spectral variability are properly accounted for. A lesser agreement is found when we compare our cut-off measurements with the ones obtained by Ricci et al. (2017) using Swift-BAT high-energy data, finding that their values are systematically higher than ours. We have investigated whether a linear correlation exists between photon index and the cut-off and found a weak one, probably to be ascribed to the non-perfect modelling of the soft part of the spectra, due to the poor statistical quality of the 2-10 keV X-ray data. No correlation is also found between the Eddington ratio and the cut-off, suggesting that only using high statistical quality broad-band spectra is it possible to verify the theoretical predictions and study the physical characteristics of the hot corona and its geometry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".