Extended X-Ray Emission Associated with the Radio Lobes and the Environments of 60 Radio Galaxies
Bibliographic record
Abstract
Abstract This paper studied the faint, diffuse extended X-ray emission associated with the radio lobes and the hot gas in the intracluster medium (ICM) environment for a sample of radio galaxies. We used shallow (∼10 ks) archival Chandra observations for 60 radio galaxies (7 FR I and 53 FR II) with 0.0222 ≤ z ≤ 1.785 selected from the 298 extragalactic radio sources identified in the 3CR catalog. We used Bayesian statistics to look for any asymmetry in the extended X-ray emission between regions that contain the radio lobes and regions that contain the hot gas in the ICM. In the Chandra broad band (0.5–7.0 keV), which has the highest detected X-ray flux and the highest signal-to-noise ratio, we found that the nonthermal X-ray emission from the radio lobes dominates the thermal X-ray emission from the environment for ∼77% of the sources in our sample. We also found that the relative amount of on-jet axis nonthermal emission from the radio lobes tends to increase with redshift compared to the off-jet axis thermal emission from the environment. This suggests that the dominant X-ray mechanism for the nonthermal X-ray emission in the radio lobes is due to the inverse Compton upscattering of cosmic microwave background (CMB) seed photons by relativistic electrons in the radio lobes, a process for which the observed flux is roughly redshift independent due to the increasing CMB energy density with increasing redshift.
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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".