Formation of dwarf galaxies in major gas-rich disc–disc mergers
Bibliographic record
Abstract
ABSTRACT Galaxies usually follow a mass–metallicity relation, where higher mass galaxies are typically more metal-rich than lower mass galaxies. Yet, tidal dwarf galaxies are outliers to this relation. These kinds of dwarfs are formed in galactic mergers. Since their material comes from the parent galaxies, they are typically more metal-rich than regular dwarfs. However, galaxies were far less enriched when the Universe was younger. One can ask if tidal dwarfs that formed at high redshift could be chemically distinguished from regular dwarfs. To answer this question, we performed a series of numerical simulations of gas-rich galaxy mergers at high redshift. We then identified the dwarf galaxies that formed in these mergers, and studied the evolution of their metal content. While the initial abundance of metals in the progenitors was low, the merger allows rapid enrichment and all tidal dwarf galaxies end up with high abundances. Their mass–metallicity relation is well fitted by the relation $12+\log ({\rm O/H})=5.47+0.415\log (M_*/\,{\rm {M}_\odot})$, putting them well above the observed relation for local dwarfs galaxies. We conclude that tidal dwarfs should be outliers to the mass–metallicity relation, no matter the epoch of formation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".