Dual Active Galactic Nuclei: Precursors of Binary Supermassive Black Hole Formation and Mergers
Bibliographic record
Abstract
Abstract The presence of dual active galactic nuclei (AGNs) on scales of a few tens of kiloparsecs can be used to study merger-induced accretion on supermassive black holes (SMBHs) and offer insights about SMBH mergers, using dual AGNs as merger precursors. This study uses the Romulus25 cosmological simulation to investigate the properties and evolution of dual AGNs. We first analyze the properties of AGNs ( L bol > 10 43 erg s −1 ) and their neighboring SMBHs (any SMBHs closer than 30 pkpc to an AGN) at z ≤ 2. This is our underlying population. We then applied the luminosity threshold of L bol > 10 43 erg s −1 to the neighboring SMBHs thereby identifying dual and multiple AGNs. Our findings indicate an increase in the number of both single and dual AGNs from lower to higher redshifts. We also find that the number of dual AGNs with separations of 0.5–4 kpc is twice the number of duals with separations of 4–30 kpc. All dual AGNs in our sample resulted from major mergers. Compared to single AGNs, duals have a lower black hole-to-halo mass ratio. We found that the properties of dual AGN host halos, including halo mass, stellar mass, star formation rate, and gas mass, are generally consistent with those of single AGN halos, albeit tending toward the higher end of their respective property ranges. Our analysis uncovered a diverse array of evolutionary patterns among dual AGNs, including rapidly evolving systems, slower ones, and instances where SMBH mergers are ineffective.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".