Magnetic field transport from AGN cores to jets, lobes, and the IGM
Bibliographic record
Abstract
Abstract I describe various stages of energy flow along an extragalactic jet, which subsequently evolves into an extended lobe which is visible in radio and X-rays. The sizes of the lobes vary from kpc scales to several megaparsec, so that the largest lobes are clearly injecting back hole energy into the IGM on scales comparable with a galaxy-galaxy separation. This is sometimes loosely referred to as Black hole-IGM “feedback”. My talk begins with a well-formed jet, and avoids the complex and unclarified physics at less than a few Schwarzschild radii that cause the initial launching the jet. This presentation focuses on recent thinking and supercomputer simulations that appear to clarify the fundamental nature of these remarkable jets and lobes. The energy transport process appears to be electrodynamic, rather than particle beam–driven. A new observational verification of a 1018 Ampère current in an actual jet is concordant with the predictions and simulations of poynting flux-dominated electromagnetic jets. In this model the current is tightly related to the BH mass and angular energy. The magneto-plasma properties of the lobes must obviously match to the jets which feed them. The “energy sink” phase is when BH energy is ultimately deposited on supra-galactic scales. The process from the BH to the lobe production happens with remarkable efficiency. The presence or absence of a galaxy cluster environment creates laboratory conditions that help to calibrate the energy flow paths, and the magnetic rigidity of these jet-lobe systems. I conclude by describing recent, sensitive radio observations on supra-cluster scales that test for final magnetic energy deposition - the “sink” phase - into the intergalactic medium.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".