On the H i Content of MaNGA Major Merger Pairs
Bibliographic record
Abstract
Abstract The role of H i content in galaxy interactions is still under debate. To study the H i content of galaxy pairs at different merging stages, we compile a sample of 66 major-merger galaxy pairs and 433 control galaxies from the Sloan Digital Sky Survey IV (SDSS-IV) MaNGA IFU survey. In this study, we adopt kinematic asymmetry as a new effective indicator to describe the merging stage of galaxy pairs. With archival data from the HI-MaNGA survey and new observations from the Five-hundred-meter Aperture Spherical radio Telescope (FAST), we investigate the differences in H i gas fraction ( f H I ), star formation rate (SFR), and H i star formation efficiency (SFE H I ) between the pair and control samples. Our results suggest that the H i gas fraction of major-merger pairs on average is marginally decreased by ∼15% relative to isolated galaxies, implying mild H i depletion during galaxy interactions. Compared to isolated galaxies, pre-passage paired galaxies have similar f H I , SFR, and SFE H I , while pairs during the pericentric passage have weakly decreased f H I (−0.10 ± 0.05 dex), significantly enhanced SFR (0.42 ± 0.11 dex), and SFE H I (0.48 ± 0.12 dex). When approaching the apocenter, paired galaxies show marginally decreased f H I (−0.05 ± 0.04 dex), comparable SFR (0.04 ± 0.06 dex), and SFE H I (0.08 ± 0.08 dex). We propose that the marginally detected H i depletion may originate from the gas consumption in fueling the enhanced H 2 reservoir of galaxy pairs. In addition, new FAST observations also reveal a H i absorber ( N H I ∼ 4.7 × 10 21 cm −2 ), which may suggest gas infalling and the triggering of active galactic nuclei activity.
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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 | 0.000 | 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".