Enhanced atomic gas fractions in recently merged galaxies: quenching is not a result of post-merger gas exhaustion
Bibliographic record
Abstract
We present a detailed assessment of the global atomic hydrogen gas fraction (f gas = log[M H I /M ]) in a sample of post-merger galaxies identified in the Sloan Digital Sky Survey (SDSS).Archival H I measurements of 47 targets are combined with new Arecibo observations of a further 51 galaxies.The stellar mass range of the post-merger sample, our observing strategy, detection thresholds and data analysis procedures replicate those of the extended GALEX Arecibo SDSS Survey (xGASS) which can therefore be used as a control sample.Our principal results are (1) the post-merger sample shows a ∼50 per cent higher HI detection fraction compared with xGASS; (2) accounting for non-detections, the median atomic gas fraction of the post-merger sample is larger than the control sample by 0.3-0.6 dex; and (3) the median atomic gas fraction enhancement ( f gas ), computed on a galaxy-by-galaxy basis at fixed stellar mass, is 0.51 dex.Our results demonstrate that recently merged galaxies are typically a factor of ∼3 more H I rich than control galaxies of the same M .If the control sample is additionally matched in star formation rate, the median H I excess is reduced to f gas = 0.2 dex, showing that the enhanced atomic gas fractions in post-mergers are not purely a reflection of changes in star formation activity.We conclude that merger-induced starbursts and outflows do not lead to prompt quenching via exhaustion/expulsion of the galactic gas reservoirs.Instead, we propose that if star formation ceases after a merger, it is more likely due to an enhanced turbulence which renders the galaxy unable to effectively form new stars.
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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) | 0.001 | 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".