Mapping the dark matter halo of early-type galaxy NGC 2974 through orbit-based models with combined stellar and cold gas kinematics
Bibliographic record
Abstract
ABSTRACT We present an orbit-based method of combining stellar and cold gas kinematics to constrain the dark matter profile of early-type galaxies. We apply this method to early-type galaxy NGC 2974, using Pan-STARRS imaging and SAURON stellar kinematics to model the stellar orbits, and introducing H i kinematics from VLA observation as a tracer of the gravitational potential. The introduction of the cold gas kinematics shows a significant effect on the confidence limits of especially the dark halo properties: we exclude more than $95{{\ \rm per\ cent}}$ of models within the 1σ confidence level of Schwarzschild modelling with only stellar kinematics, and reduce the relative uncertainty of the dark matter fraction significantly to $10{{\ \rm per\ cent}}$ within 5Re. Adopting a generalized Navarro–Frenk–White (NFW) dark matter profile, we measure a shallow cuspy inner slope of $0.6^{+0.2}_{-0.3}$ when including the cold gas kinematics in our model. We cannot constrain the inner slope with the stellar kinematics alone.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".