Buried AGNs in Advanced Mergers: Mid-infrared Color Selection as a Dual AGN Candidate Finder
Bibliographic record
Abstract
Abstract A direct consequence of hierarchical galaxy formation is the existence of dual supermassive black holes, which may be preferentially triggered as active galactic nuclei (AGNs) during galaxy mergers. Despite decades of searching, however, dual AGNs are extremely rare, and most have been discovered serendipitously. Using the all-sky WISE survey, we identified a population of over 100 morphologically identified interacting galaxies or mergers that display red mid-infrared colors often associated in extragalactic sources with powerful AGNs. The vast majority of these advanced mergers are optically classified as star-forming galaxies, which suggests that they may represent an obscured population of AGNs that cannot be found through optical studies. In this work, we present Chandra/ACIS observations and near-infrared spectra with the Large Binocular Telescope of six advanced mergers with projected pair separations less than ∼10 kpc. The combined X-ray, near-infrared, and mid-infrared properties of these mergers provide confirmation that four out of the six mergers host at least one AGN, with four of the mergers possibly hosting dual AGNs with projected separations less than ∼10 kpc, despite showing no firm evidence for AGNs based on optical spectroscopic studies. Our results demonstrate that (1) optical studies miss a significant fraction of single and dual AGNs in advanced mergers, and (2) mid-infrared pre-selection is extremely effective in identifying dual AGN candidates in late-stage mergers. Our multi-wavelength observations suggest that the buried AGNs in these mergers are highly absorbed, with intrinsic column densities in excess of cm−2, consistent with hydrodynamic simulations.
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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 | 0.002 | 0.000 |
| 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".