Testing the Correlation between Bending Angle and Polarization Properties of Bent Radio Galaxies
Bibliographic record
Abstract
Abstract The bending of radio galaxies in galaxy clusters is expected to be caused by interactions with the local environment. The physical processes responsible for jet bending, and their influence on the polarization properties of radio galaxies, remain poorly understood, leading to the question of whether the jet properties in bent radio galaxies differ from those in linear radio galaxies. Using a sample of 24 polarized bent radio galaxies, observed with the Karl G. Jansky Very Large Array at 1–2 GHz, we test for correlation of the bending angle with polarization parameters, measuring Faraday rotation, intrinsic fractional polarization, and Faraday rotation dispersion, used here as a measure of turbulence along the line of sight. We find no statistically significant correlations. At the spatial resolution of our dataset (3–46 kpc, median = 18.4 kpc), our results indicate that we are primarily probing larger-scale intracluster medium effects not related to bending angle. The absence of a statistically significant correlation suggests that bent radio galaxies are reliable probes of intracluster magnetic fields, because their intrinsic properties do not appear to introduce systematic biases into measured polarization parameters. We do detect a preference for source magnetic field vectors to align with the direction of jet bending. Finally, we estimate that the POSSUM and Square Kilometre Array surveys will contain ≳300 and ≳1000 polarized radio galaxies, respectively, providing large future samples with a range of bending angles and similar redshift distribution and number of beams per source as in our sample, enabling our results to be tested with greater statistical power.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".