Prospects for gamma-ray observations of narrow-line Seyfert 1 galaxies with the Cherenkov Telescope Array
Bibliographic record
Abstract
Gamma-ray-emitting narrow-line Seyfert 1 (γ-NLS1) galaxies are thought to harbour relatively low-mass black holes (106–108 M|$\odot$|) accreting close to the Eddington limit. They show characteristics similar to those of blazars, such as flux and spectral variability in the gamma-ray energy band and radio properties which point towards the presence of a relativistic jet. These characteristics make them an intriguing class of sources to be investigated with the Cherenkov Telescope Array (CTA), the next-generation ground-based gamma-ray observatory. We present our extensive set of simulations of all currently known γ-ray emitters identified as NLS1s (20 sources), investigating their detections and spectral properties, taking into account the effect of both the extragalactic background light in the propagation of gamma-rays and intrinsic absorption components. We find that the prospects for observations of γ-NLS1 with CTA are promising. In particular, the brightest sources of our sample, SBS 0846+513, PMN J0948+0022, and PKS 1502+036, can be detected during high/flaring states, the former two even in the case in which the emission occurs within the highly opaque central regions, which prevent gamma-rays above a few tens of GeV to escape. In this case, the low-energy threshold of CTA will play a key role. If, on the other hand, high-energy emission occurs outside the broad-line region, we can detect the sources up to several hundreds of GeV – depending on the intrinsic shape of the emitted spectrum. Therefore, CTA observations will provide valuable information on the physical conditions and emission properties of their jets.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.000 |
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".