A STUDY OF BROADBAND FARADAY ROTATION AND POLARIZATION BEHAVIOR OVER 1.3–10 GHz IN 36 DISCRETE RADIO SOURCES
Bibliographic record
Abstract
ABSTRACT We present a broadband polarization analysis of 36 discrete polarized radio sources over a very broad, densely sampled frequency band. Our sample was selected on the basis of polarization behavior apparent in narrowband archival data at 1.4 GHz: half the sample shows complicated frequency-dependent polarization behavior (i.e., Faraday complexity) at these frequencies, while half shows comparatively simple behavior (i.e., they appear Faraday simple ). We re-observed the sample using the Australia Telescope Compact Array in full polarization, with 6 GHz of densely sampled frequency coverage spanning 1.3–10 GHz. We have devised a general polarization modeling technique that allows us to identify multiple polarized emission components in a source, and to characterize their properties. We detect Faraday complex behavior in almost every source in our sample. Several sources exhibit particularly remarkable polarization behavior. By comparing our new and archival data, we have identified temporal variability in the broadband integrated polarization spectra of some sources. In a number of cases, the characteristics of the polarized emission components, including the range of Faraday depths over which they emit, their temporal variability, spectral index, and the linear extent of the source, allow us to argue that the spectropolarimetric data encode information about the magneto-ionic environment of active galactic nuclei themselves. Furthermore, the data place direct constraints on the geometry and magneto-ionic structure of this material. We discuss the consequences of restricted frequency bands on the detection and interpretation of polarization structures, and the implications for upcoming spectropolarimetric surveys.
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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 | 0.002 | 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".