Properties of Dark Matter Halos in Disk Galaxies
Bibliographic record
Abstract
We present a simple technique to estimate mass-to-light ( M/L ) ratios of stellar populations based on two broadband photometry measurements, i.e. a colour- M/L relation. We apply the colour- M/L relation to galaxy rotation curves, using a large set of galaxies that span a great range in Hubble type, luminosity and scale size and that have accurately measured HI and/or H α rotation curves. Using the colour- M/L relation, we construct stellar mass models of the galaxies and derive the dark matter contribution to the rotation curves. We compare our dark matter rotation curves with adiabatically contracted Navarro, Frenk, & White (1997, NFW hereafter) dark matter halos. We find that before adiabatic contraction most high surface brightness galaxies and some low surface brightness galaxies are well fit by a NFW dark matter profile. However, after adiabatic contraction, most galaxies are poorly fit in the central few kpc. the observed angular momentum distribution in the baryonic component is poorly matched by ACDM model predictions, indicating that the angular momentum distribution is not conserved during the galaxy assembly process. We find that in most galaxies the dark matter distribution can be derived by scaling up the HI gas contribution. However, we find no consistent value for the scaling factor among all the galaxies.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".