Radial Trends in IMF-Sensitive Absorption Features in Two Early-Type Galaxies: Evidence for Abundance-Driven Gradients
Bibliographic record
Abstract
Samples of early-type galaxies show a correlation between stellar velocity dispersion and the stellar initial mass function (IMF) as inferred from gravity-sensitive absorption lines in the galaxies' central regions. To search for spatial variations in the IMF, we have observed two early-type galaxies with Keck/LRIS and measured radial gradients in the strengths of absorption features from 4000-5500 Å$\,$ and 8000-10,000 Å. We present spatially resolved measurements of the dwarf-sensitive spectral indices NaI (8190 Å) and Wing-Ford FeH (9915 Å), as well as indices for species of H, C$_2$, CN, Mg, Ca, TiO, and Fe. Our measurements show a metallicity gradient in both objects, and Mg/Fe consistent with a shallow gradient in α-enhancement, matching widely observed trends for massive early-type galaxies. The NaI index and the CN$_1$ index at 4160 Å$\,$ exhibit significantly steeper gradients, with a break at $r \sim 0.1 r_{\rm eff}$ ($r \sim 300$ pc). Inside this radius NaI strength increases sharply toward the galaxy center, consistent with a rapid central rise in [Na/Fe]. In contrast, the ratio of FeH to Fe index strength decreases toward the galaxy center. This behavior cannot be reproduced by a steepening IMF inside $0.1 r_{\rm eff}$ if the IMF is a single power law. While gradients in the mass function above $\sim 0.4 M_\odot$ may occur, exceptional care is required to disentangle these IMF variations from the extreme variations in individual element abundances near the galaxies' centers.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".