Particle content, radio-galaxy morphology, and jet power: all radio-loud AGN are not equal
Bibliographic record
Abstract
Ongoing and future radio surveys aim to trace the evolution of black hole growth and feedback from active galactic nuclei (AGNs) throughout cosmic time; however, there remain major uncertainties in translating radio luminosity functions into a reliable assessment of the energy input as a function of galaxy and/or dark matter halo mass. A crucial and long-standing problem is the composition of the radio-lobe plasma that traces AGN jet activity. In this paper, we carry out a systematic comparison of the plasma conditions in Fanaroff & Riley class I and II radio galaxies to demonstrate conclusively that their internal composition is systematically different. This difference is best explained by the presence of an energetically dominant proton population in the FRI, but not the FRII radio galaxies. We show that, as expected from this systematic difference in particle content, radio morphology also affects the jet-power/radio-luminosity relationship, with FRII radio galaxies having a significantly lower ratio of jet power to radio luminosity than the FRI cluster radio sources used to derive jet-power scaling relations via X-ray cavity measurements. Finally, we also demonstrate conclusively that lobe composition is unconnected to accretion mode (optical excitation class): the internal conditions of low- and high-excitation FRII radio lobes are indistinguishable. We conclude that inferences of population-wide AGN impact require careful assessment of the contribution of different jet subclasses, particularly given the increased diversity of jet evolutionary states expected to be present in deep, low-frequency radio surveys such as the LOFAR Two-Metre Sky Survey.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 0.001 |
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".