A REMARKABLE LONG-TERM LIGHT CURVE AND DEEP, LOW-STATE SPECTROSCOPY: SWIFT AND XMM-NEWTON MONITORING OF THE NLS1 GALAXY Mkn 335
Bibliographic record
Abstract
The narrow-line Seyfert 1 galaxy (NLS1) Mkn 335 is remarkable because it has repeatedly shown deep, long X-ray low states that show pronounced spectral structure. It has become one of the prototype active galactic nuclei (AGNs) in deep minimum X-ray states. Here we report on the continuation of our ongoing monitoring campaign with Swift and the examination of the low-state X-ray spectra based on a 200 ks triggered observation with XMM-Newton in 2009 June. Swift has continuously monitored Mkn 335 since 2007 May typically on a monthly basis. This is one of the longest simultaneous UV/X-ray light curves so far obtained for an AGN. Mkn 335 has shown strong X-ray variability even on timescales of hours. In the UV, it turns out to be one of the most variable among NLS1s. Long-term Swift monitoring allows us to examine correlations between the UV, X-rays, and X-ray hardness ratios. We find no significant correlation or lag between the UV and X-ray variability; however, we do find distinct trends in the behavior of the hardness ratio variability. The hardness ratio and count rate are correlated in the low-flux state, but no correlation is seen in the high state. The X-ray low-state spectra of the 2007 and 2009 XMM-Newton observations display significant spectral variability. We fit the X-ray spectra with a suite of phenomenological models in order to characterize the data. The broadband CCD spectrum can be fitted equally well with partial absorption and blurred reflection models. These more complicated models are explored in further detail in upcoming work.
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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 | 0.001 |
| 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".