The stellar mass function and efficiency of galaxy formation with a varying initial mass function
Bibliographic record
Abstract
Several recent observational studies have concluded that the initial mass function (IMF) of stars varies systematically with galaxy properties such as velocity dispersion. In this paper, we investigate the effect of linking the circular velocity of galaxies, as determined from the Fundamental Plane and Tully–Fisher relations, to the slope of the IMF with parametrizations guided by several of these studies. For each empirical relation, we generate stellar masses of ∼600 000 Sloan Digital Sky Survey galaxies at z ∼ 0.1, by fitting the optical photometry to large suites of synthetic stellar populations that sample the full range of galaxy parameters. We generate stellar mass functions and examine the stellar-to-halo mass relations using sub-halo abundance matching. At the massive end, the stellar mass functions become a power law, instead of the familiar exponential decline. As a result, it is a generic feature of these models that the central galaxy stellar-to-halo mass relation is significantly flatter at high masses (slope ∼−0.3 to −0.4) than in the case of a universal IMF (slope ∼−0.6). We find that regardless of whether the IMF varies systematically in all galaxies or just early types, there is still a well-defined peak in the central stellar-to-halo mass ratio at halo masses of ∼1012 M⊙. In general, the IMF variations explored here lead to significantly higher integrated stellar densities if the assumed dependence on circular velocity applies to all galaxies, including late-types; in fact the more extreme cases can be ruled out, as they imply an unphysical situation in which the stellar fraction exceeds the universal baryon fraction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".