Searching for Nuclear Obscuration in the Infrared Spectra of Nearby FR I Radio Galaxies
Bibliographic record
Abstract
Abstract How do active galactic nuclei with low optical luminosities produce powerful radio emission? Recent studies of active galactic nuclei with moderate radio and low optical luminosities (Fanaroff & Riley class I, FR I) searching for broad nuclear emission lines in polarized light, as predicted by some active galactic nucleus unification models, have found heterogeneous results. These models typically consist of a central engine surrounded by a torus of discrete dusty clouds. These clouds would absorb and scatter optical emission, blocking broad nuclear emission lines, and reradiate in mid-infrared. Some scattered broad-line emission may be observable, depending on geometry, which would be polarized. We present a wide-band infrared spectroscopic analysis of 10 nearby FR I radio galaxies to determine whether there is significant emission from a dusty obscuring structure. We used Markov Chain Monte Carlo algorithms to decompose Spitzer/IRS spectra of our sample. We constrained the wide-band behavior of our models with photometry from the Two Micron All Sky Survey, Spitzer/IRAC, Spitzer/MIPS, and Herschel/SPIRE. We find that one galaxy is best fit by a clumpy torus and three others show some thermal mid-infrared component. This suggests that in those three there is likely some obscuring dust structure that is inconsistent with our torus models and there must be some source of photons heating the dust. We conclude that 40% of our FR I radio galaxies show evidence of obscuring dusty material, possibly some other form of hidden broad-line nucleus, but only 10% favor the clumpy torus model specifically.
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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 | 0.002 |
| 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 | 0.000 | 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".