Dissecting star formation in the “Atoms-for-Peace” galaxy
Bibliographic record
Abstract
Context. The tidal tails of post-merger galaxies exhibit ongoing star formation far from their disks. The study of such systems can be useful for our understanding of gas condensation in diverse environments. Aims. The ongoing star formation in the tidal tails of post-merger galaxies can be directly studied from ultraviolet (UV) imaging observations. Methods. The post merger galaxy NGC7252 (“Atoms-for-Peace” galaxy) is observed with the Astrosat UV imaging telescope (UVIT) in broadband NUV and FUV filters to isolate the star-forming regions in the tidal tails and study the spatial variation in star formation rates. Results. Based on ultraviolet imaging observations, we discuss star-forming regions of ages <200 Myr in the tidal tails. We measure star formation rates in these regions and in the main body of the galaxy. The integrated star formation rate (SFR) of NGC7252 (i.e., that in the galaxy and tidal tails combined) without correcting for extinction is found to be 0.81 ± 0.01 M⊙ yr−1. We show that the integrated SFR can change by an order of magnitude if the extinction correction used in SFR derived from other proxies are taken into consideration. The star formation rates in the associated tidal dwarf galaxies (NGC7252E, SFR = 0.02 M⊙ yr−1 and NGC7252NW, SFR = 0.03 M⊙ yr−1) are typical of dwarf galaxies in the local Universe. The spatial resolution of the UV images reveals a gradient in star formation within the tidal dwarf galaxy. The star formation rates show a dependence on the distance from the centre of the galaxy. This can be due to the different initial conditions responsible for the triggering of star formation in the gas reservoir that was expelled during the recent merger in NGC7252.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".