Radio jet–ISM interaction and positive radio-mechanical feedback in Abell 1795
Bibliographic record
Abstract
ABSTRACT We present XSHOOTER observations with previous ALMA, MUSE, and HST observations to study the nature of radio jet triggered star formation and the interaction of radio jets with the interstellar medium in the brightest cluster galaxy (BCG) in the Abell 1795 cluster. Using HST UV data, we determined an ongoing star formation rate of 9.3 M⊙ yr−1. The star formation follows the global Kennicutt–Schmidt law; however, it has a low efficiency compared to circumnuclear starbursts in nearby galaxies with an average depletion time of ∼1 Gyr. The star formation and molecular gas are offset by ∼1 kpc indicating that stars have decoupled from the gas. We detected an arc of high linewidth in ionized gas where electron densities are elevated by a factor of ∼4 suggesting a shock front driven by radio jets or peculiar motion of the BCG. An analysis of nebular emission line flux ratios suggests that the gas is predominantly ionized by star formation with a small contribution from shocks. We also calculated the velocity structure function (VSF) of the ionized and molecular gases using velocity maps to characterize turbulent motion in the gas. The ionized gas VSF suggests that the radio jets are driving supersonic turbulence in the gas. Thus radio jets cannot only heat the atmosphere on large scales and may quench star formation on longer time-scales while triggering star formation in positive feedback on short time-scales of a few million years.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".