Galaxy And Mass Assembly (GAMA): the effect of galaxy group environment on active galactic nuclei
Bibliographic record
Abstract
In galaxy clusters, efficiently accreting active galactic nuclei (AGNs) are preferentially located in the infall regions of the cluster projected phase-space, and are rarely found in the cluster core. This has been attributed to both an increase in triggering opportunities for infalling galaxies, and a reduction of those mechanisms in the hot, virialized, cluster core. Exploiting the depth and completeness (98 per cent at r < 19.8 mag) of the Galaxy And Mass Assembly survey (GAMA), we probe down the group halo mass function to assess whether AGNs are found in the same regions in groups as they are in clusters. We select 451 optical AGNs from 7498 galaxies with log10(M*/M⊙) > 9.9 in 695 groups with 11.53 ≤ log10(M200/M⊙) ≤ 14.56 at z < 0.15. By analysing the projected phase-space positions of these galaxies, we demonstrate that when split both radially, and into physically derived infalling and core populations, AGN position within group projected phase-space is dependent on halo mass. For groups with log10(M200/M⊙) > 13.5, AGNs are preferentially found in the infalling galaxy population with 3.6σ confidence. At lower halo masses, we observe no difference in AGN fraction between core and infalling galaxies. These observations support a model where a reduced number of low-speed interactions, ram pressure stripping and intra-group/cluster medium temperature, the dominance of which increase with halo mass, work to inhibit AGN in the cores of groups and clusters with log10(M200/M⊙) > 13.5, but do not significantly affect nuclear activity in cores of less massive structures.
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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 | 0.001 | 0.002 |
| 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".