Revisiting dual AGN candidates with spatially resolved LBT spectroscopy
Bibliographic record
Abstract
Context.The merging of supermassive black holes (SMBHs) is a direct consequence of our hierarchical picture of galaxy evolution. It is difficult to track the merging process of SMBHs during mergers of galaxies as SMBHs are naturally difficult to observe. Aims.We want to characterise and confirm the presence of two independent active galactic nuclei (AGN) separated by a few kiloparsec in seven strongly interacting galaxies previously selected from the Sloan Digital Sky Survey (SDSS) as Seyfert-Seyfert pairs based on emission-line ratio diagnostics. Methods.Optical slit spectra taken with MODS at the Large Binocular Telescope are presented to infer the detailed spatial distribution of optical emission lines, and their line ratios and AGN signatures with respect to the host galaxies, thereby quantifying the impact of beam smearing and large fibre apertures on the spectra captured by the SDSS. Results.We find that at most two of the seven targets actually retain a Seyfert-Seyfert dual AGN, whereas the others may be more likely powered by post-AGB stars in retired galaxies or through shocks in the ISM based on spatially resolved optical line diagnostics. The major cause of this discrepancy is a bias caused by the spillover of flux from the primary source in the secondary SDSS fibre which can be more than an order of magnitude at < 3″ separations. Previously reported extremely low X-ray–to–[O III] luminosity ratios may be explained by this misclassification, as can heavily obscured AGN for the primaries. We also find that the nuclei with younger stellar ages host the primary AGN. Conclusions.Studies of close dual AGN selected solely from fibre-based spectroscopy can create severe biases in the sample selection and interpretation of the results. Spatially resolved spectroscopy should ideally be used in the future to characterise such compact systems together with multi-wavelength follow-up observations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".