The nature of the soft excess and spectral variability in the Seyfert 1 galaxy Zw 229.015
Bibliographic record
Abstract
ABSTRACT We have carried out a systematic analysis of the nearby (z = 0.0279) active galaxy Zw 229.015 using multi-epoch, multi-instrument, and deep pointed observations with XMM–Newton, Suzaku, Swift,and NuSTAR. Spectral and temporal variability are examined in detail on both the long (weeks-to-years) and short (hours) time-scales. A deep Suzaku observation of the source shows two distinct spectral states; a bright-soft state and a dim-hard state in which changes in the power-law component account for the differences. Partial covering, blurred reflection, and soft Comptonization models describe the X-ray spectra comparably well, but the smooth, rather featureless, spectrum may be favouring the soft Comptonization scenario. Moreover, independent of the spectral model, the observed spectral variability is ascribed to the changes in the power-law continuum only and do not require changes in the properties of the absorber or blurred reflector incorporated in the other scenarios. The multi-epoch observations between 2009 and 2018 can be described in similar fashion. This could be understood if the primary emission is originating at a large distance from a standard accretion disc or if the disc is optically thin and geometrically thick as recently proposed for Zw 229.015. Our investigation shows that Zw 229.015 behaves similar to sources like Akn 120 and Mrk 530 that exhibit a strong soft excess, but weak Compton hump and Fe Kα emission.
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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 | 0.000 |
| 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 | 0.001 | 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".