Relaxed blue ellipticals: accretion-driven stellar growth is a key evolutionary channel for low mass elliptical galaxies
Bibliographic record
Abstract
ABSTRACT How elliptical galaxies form is a key question in observational cosmology. While the formation of massive ellipticals is strongly linked to mergers, the low mass (M⋆/M⊙ < 109.5) regime remains less well explored. In particular, studying elliptical populations when they are blue, and therefore rapidly building stellar mass, offers strong constraints on their formation. Here, we study 108 blue low-mass ellipticals (which have a median stellar mass of 108.7 M⊙) at z < 0.3 in the COSMOS field. Visual inspection of extremely deep optical HSC images indicates that less than 3 per cent of these systems have visible tidal features, a factor of 2 less than the incidence of tidal features in a control sample of galaxies with the same distribution of stellar mass and redshift. This suggests that the star formation activity in these objects is not driven by mergers or interactions but by secular gas accretion. We combine accurate physical parameters from the COSMOS2020 catalogue, with measurements of local density and the locations of galaxies in the cosmic web, to show that our blue ellipticals reside in low-density environments, further away from nodes and large-scale filaments than other galaxies. At similar stellar masses and environments, blue ellipticals outnumber their normal (red) counterparts by a factor of 2. Thus, these systems are likely progenitors of not only normal ellipticals at similar stellar mass but, given their high star formation rates, also of ellipticals at higher stellar masses. Secular gas accretion therefore likely plays a significant (and possibly dominant) role in the stellar assembly of elliptical galaxies in the low-mass regime.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".