The stellar IMF in early-type galaxies from a non-degenerate set of optical line indices
Bibliographic record
Abstract
We investigate the optical spectral region of spectra of ∼1000 stars searching for initial mass function (IMF)-sensitive features to constrain the low-mass end of the IMF slope in elliptical galaxies. The use of indicators bluer than near-infrared features (NaI, CaT, Wing-Ford FeH) is crucial if we want to compare our observations to optical simple stellar population (SSP) models. We use the MILES stellar library (Sánchez-Blázquez et al.) in the wavelength range 3500–7500 Å to select indices that are sensitive to cool dwarf stars and that do not or only weakly depend on age and metallicity. We find several promising indices of molecular TiO and CaH lines. In this wavelength range, the response of a change in the effective temperature of the cool red giant (RGB) population is similar to the response of a change in the number of dwarf stars in the galaxy. We therefore investigate the degeneracy between IMF variation and ΔTeff, RGB, and show that it is possible to break this degeneracy with the new IMF indicators defined here. In particular, we define a CaH1 index around λ6380 Å that arises purely from cool dwarfs, does not strongly depend on age and is anticorrelated with [α/Fe]. This index allows the determination of the low-mass end of the IMF slope from integrated-light measurements when combined with different TiO lines and age- and metallicity-dependent features such as Hβ, Mgb, Fe5270 and Fe5335. The use of several indicators is crucial to break degeneracies between IMF variations, age, abundance pattern and effective temperature of the cool red giant (RGB) population. We measure line-index strengths of our new optical IMF indicators in the Conroy & van Dokkum SSP models and compare these with index strengths of the same spectral features in a sample of stacked Sloan Digital Sky Survey early-type galaxy spectra with varying velocity dispersions. Using different indicators, we find a clear trend of a steepening IMF with increasing velocity dispersion from 150 to 310 km s−1 described by the linear equation x = (2.3 ± 0.1) log σ200 + (2.13 ± 0.15), where x is the IMF slope and σ200 is the central stellar velocity dispersion measured in units of 200 km s−1. We test the robustness of this relation by repeating the analysis with 10 different sets of indicators. We found that the NaD feature has the largest impact on the IMF slope, if we assume solar [Na/Fe] abundance. By including NaD, the slope of the linear relation increases by 0.3 (2.6 ± 0.2). We compute the ‘IMF mismatch’ parameter as the ratio of stellar mass-to-light ratio predicted from the x-σ200 relation to that inferred from SSP models assuming a Salpeter IMF and find good agreement with independent published results.
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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 | 0.000 |
| 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".