Coronal properties of low-accreting AGNs using <i>Swift, XMM</i>–<i>Newton</i>, and <i>NuSTAR</i> observations
Bibliographic record
Abstract
ABSTRACT We studied the broad-band X-ray spectra of Swift/Burst Alert Telescope selected low-accreting active galactic nuclei (AGNs) using the observations from XMM–Newton, Swift, and NuSTAR in the energy range of 0.5–150 keV. Our sample consists of 30 AGNs with Eddington ratio, λEdd < 10−3. We extracted several coronal parameters from the spectral modelling, such as the photon index, hot electron plasma temperature, cutoff energy, and optical depth. We tested whether there exist any correlation/anticorrelation among different spectral parameters. We observe that the relation of hot electron temperature with the cutoff energy in the low accretion domain is similar to what is observed in the high accretion domain. We did not observe any correlation between the Eddington ratio and the photon index. We studied the compactness–temperature diagram and found that the cooling process for extremely low-accreting AGNs is complex. The jet luminosity is calculated from the radio flux, and observed to be related to the bolometric luminosity as $L_{\rm jet} \propto L_{\rm bol}^{0.7}$, which is consistent with the standard radio-X-ray correlation.
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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 | 0.001 |
| 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".