SDSS-IV MaNGA: the spatially resolved stellar initial mass function in ∼400 early-type galaxies
Bibliographic record
Abstract
Mapping Nearby Galaxies at Apache Point Observatory provides the opportunity to make precise spatially resolved measurements of the IMF slope in galaxies owing to its unique combination of spatial resolution, wavelength coverage, and sample size. We derive radial gradients in age, element abundances, and IMF slope analysing optical and near-infrared absorption features from stacked spectra out to the half-light radius of 366 early-type galaxies with masses 9.9–10.8 log M/M⊙. We find flat gradients in age and [α/Fe] ratio, as well as negative gradients in metallicity, consistent with the literature. We further derive significant negative gradients in the [Na/Fe] ratio with galaxy centres being well enhanced in Na abundance by up to 0.5 dex. Finally, we find a gradient in IMF slope with a bottom-heavy IMF in the centre (typical mass excess factor of 1.5) and a Milky Way-type IMF at the half-light radius. This pattern is mass dependent with the lowest mass galaxies in our sample featuring only a shallow gradient around a Milky Way IMF. Our results imply the local IMF–σ relation within galaxies to be even steeper than the global relation and hint towards the local metallicity being the dominating factor behind the IMF variations. We also employ different stellar population models in our analysis and show that a radial IMF gradient is found independently of the stellar population model used. A similar analysis of the Wing-Ford band provides inconsistent results and further evidence of the difficulty in measuring and modelling this particular feature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".