The High-redshift Clusters Occupied by Bent Radio AGN (COBRA) Survey: Investigating the Role of Environment on Bent Radio AGNs Using LOFAR
Bibliographic record
Abstract
Abstract Bent radio active galactic nucleus (AGN) morphology depends on the density of the surrounding gas. However, bent sources are found inside and outside clusters, raising the question of how environment impacts bent AGN morphology. We analyze new LOw-Frequency Array the LOFAR Two-metre Sky Survey (LoTSS) Data Release II observations of 20 bent AGNs in clusters and 15 not in clusters from the high-z Clusters Occupied by Bent Radio AGN (COBRA) survey (0.35 < z < 2.35). We measure the impact of environment on size, lobe symmetry, and radio luminosity. We find that the most asymmetric radio lobes lie outside of clusters, and we uncover a tentative anticorrelation between the total projected physical area and cluster overdensity. Additionally, we, for the first time, present spectral index measurements of a large sample of high-z bent sources using LoTSS and Very Large Array Faint Images of the Radio Sky at Twenty-centimeters (VLA FIRST) observations. We find that the median spectral index for the cluster sample is −0.76 ± 0.01, while the median spectral index for the noncluster sample is −0.81 ± 0.02. Furthermore, 13 of 20 cluster bent AGNs have flat cores (α ≥ −0.6) compared to 4 of 15 of noncluster bent AGNs, indicating a key environmental signature. Beyond core spectral index, bent AGNs inside and outside clusters are remarkably similar. We conclude that the noncluster sample may be more representative of bent AGNs at large offsets from the cluster center (> 1.2 Mpc) or bent AGNs in weaker groups rather than the field.
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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 | 0.001 | 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) | 0.001 | 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".