A definitive merger-AGN connection at z ∼ 0 with CFIS: mergers have an excess of AGN and AGN hosts are more frequently disturbed
Bibliographic record
Abstract
The question of whether galaxy mergers are linked to the triggering of active galactic nuclei (AGN) continues to be a topic of considerable debate. The issue can be broken down into two distinct questions: (1) Can galaxy mergers trigger AGN? (2) Are galaxy mergers the dominant AGN triggering mechanism? A complete picture of the AGN-merger connection requires that both of these questions are addressed with the same data set. In previous work, we have shown that galaxy mergers selected from the Sloan Digital Sky Survey (SDSS) show an excess of both optically selected, and mid-IR colour-selected AGN, demonstrating that the answer to the first of the above questions is affirmative. Here, we use the same optical and mid-IR AGN selection to address the second question, by quantifying the frequency of morphological disturbances in low-surface brightness r-band images from the Canada France Imaging Survey (CFIS). Only ∼30 per cent of optical AGN host galaxies are morphologically disturbed, indicating that recent interactions are not the dominant trigger. However, almost 60 per cent of mid-IR AGN hosts show signs of visual disturbance, indicating that interactions play a more significant role in nuclear feeding. Both mid-IR and optically selected AGN have interacting fractions that are a factor of two greater than a mass and redshift matched non-AGN control sample, an excess that increases with both AGN luminosity and host galaxy stellar mass.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".