The molecular gas properties in local Seyfert 2 galaxies
Bibliographic record
Abstract
Aims.We present a multiwavelength study of the molecular gas properties of a sample of local Seyfert 2 galaxies to assess if, and to what extent, the presence of an active galactic nucleus (AGN) can affect the interstellar medium (ISM) properties in a sample of 33 local Seyfert 2 galaxies. Methods.We compare the molecular gas content (MH2) derived from new and archival low-J CO line measurements of a sample of AGN and a control sample of star-forming galaxies (SFGs). Both the AGN and the control sample are characterized in terms of host-galaxy properties, for example stellar and dust masses (M⋆andMdust, respectively) and the star formation rate (SFR). We also investigate the effect of AGN activity on the emission of polycyclic aromatic hydrocarbon (PAH) molecules in the mid-infrared (MIR), a waveband where the dust-reprocessed emission from the obscured AGN contributes the most. Result.The AGN hosted in less massive galaxies (i.e.,M⋆ < 1010.5 M⊙;Mdust < 107.5 M⊙) show larger molecular gas contents with respect to SFGs that have the same stellar and dust masses. When comparing their depletion times (tdep ∝ MH2/SFR), AGN showtdep ∼ 0.3 − 1.0 Gyr, similar to the times observed in the control sample of SFGs. Seyfert 2 galaxies show fainter PAH luminosity the larger the dominance of the nuclear activity in the MIR. Conclusions.We find no clear evidence for a systematic reduction in the molecular gas reservoir at galactic scales in Seyfert galaxies with respect to SFGs. This is in agreement with recent studies that show that molecular gas content is only reduced in sub-kiloparsec-sized regions, where emission from the accreting supermassive black hole dominates. Nonetheless, we show that the impact of AGN activity on the ISM is clearly visible as a suppression of the PAH luminosity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".