BUDDI-MaNGA II: the star-formation histories of bulges and discs of S0s
Bibliographic record
Abstract
ABSTRACT Many processes have been proposed to explain the quenching of star formation in spiral galaxies and their transformation into S0s. These processes affect the bulge and disc in different ways, and so by isolating the bulge and disc spectra, we can look for these characteristic signatures. In this work, we used buddi to cleanly extract the spectra of the bulges and discs of 78 S0 galaxies in the MaNGA Survey. We compared the luminosity and mass weighted stellar populations of the bulges and discs, finding that bulges are generally older and more metal rich than their discs. When considering the mass and environment of each galaxy, we found that the galaxy stellar mass plays a more significant role on the formation of the bulges. Bulges in galaxies with masses $\ge 10^{10}\, {\rm M}_\odot$ built up the majority of their mass rapidly early in their lifetimes, while those in lower mass galaxies formed over more extended time-scales and more recently. No clear difference was found in the formation or quenching processes of the discs as a function of galaxy environment. We conclude that more massive S0 galaxies formed through an inside-out scenario, where the bulge formed first and evolved passively while the disc underwent a more extended period of star formation. In lower mass S0s, the bulges and discs either formed together from the same material, or through an outside-in scenario. Our results therefore imply multiple formation mechanisms for S0 galaxies, the pathway of which is chiefly determined by a galaxy’s current stellar mass.
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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 | 0.001 |
| 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".