Two interacting galaxies hiding as one, revealed by MaNGA
Bibliographic record
Abstract
Given their prominent role in galaxy evolution, it is of paramount importance to unveil galaxy interactions and merger events and to investigate the underlying mechanisms. The use of high-resolution data makes it easier to identify merging systems, but it can still be challenging when the morphology does not show any clear galaxy pair or gas bridge. Characterising the origin of puzzling kinematic features can help reveal complicated systems. Here, we present a merging galaxy, MaNGA 1-114955, in which we highlighted the superimposition of two distinct rotating discs along the line of sight. These counter-rotating objects both lie on the star-forming main sequence but display perturbed stellar velocity dispersions. The main galaxy presents off-centred star formation as well as off-centred high-metallicity regions, supporting the scenario of recent starbursts, while the secondary galaxy hosts a central starburst that coincides with an extended radio emission, in excess with respect to star formation expectations. Stellar mass as well as dynamical mass estimates agree towards a mass ratio within the visible radius of 9:1 for these interacting galaxies. We suggest that we are observing a pre-coalescence stage of a merger. The primary galaxy accreted gas through a past first pericentre passage about 1 Gyr ago and more recently from the secondary gas-rich galaxy, which exhibits an underlying active galactic nucleus. Our results demonstrate how a galaxy can hide another one and the relevance of a multi-component approach for studying ambiguous systems. We anticipate that our method will be efficient at unveiling the mechanisms taking place in a sub-sample of galaxies observed by the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, all of which exhibit kinematic features of a puzzling origin in their gas emission lines.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".