Investigating the spectra and physical nature of galaxy scale jets
Bibliographic record
Abstract
ABSTRACT Previous studies have shown that physically small, low-luminosity radio galaxies, which we refer to as galaxy scale jets (GSJ), could potentially have a significant effect upon the host galaxy’s evolution. Using 6-arcsec resolution images taken from the first release of the LOFAR Two Metre Sky Survey (LoTSS DR1), we identified a representative sample of nine potential GSJ for which we obtained high-resolution, 2–4 GHz data using the Karl G. Jansky Very Large Array (VLA). Using these data, we aim to verify the GSJ nature of these sources as well as investigating the potential role of feedback. Our VLA images reveal a diversity of structures, confirm the hosts for four of the sources and find that a fifth is the first known example of a galaxy-scale remnant showing that some radio galaxies never grow beyond the GSJ stage. We also derive spectral ages and the first estimates of the lobe expansion speeds of GSJ. We find our GSJ have maximum spectral ages of 60 Myr with most between about 5 and 20 Myr, consistent with being located along an evolutionary path joining compact sources and larger radio galaxies. We find lobe advance speeds a few times the local sound speed, with most GSJ predicted to be driving strong shocks into their environment and having a significant impact upon the host’s evolution. Our discovery of a remnant GSJ, which will eventually transfer all of its energy directly into the local environment, represents an important and previously hidden aspect of AGN life cycles.
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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 | 0.000 |
| 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".