The inner structure of ÎCDM haloes - II. Halo mass profiles and low surface brightness galaxy rotation curves
Bibliographic record
Abstract
We use a set of high-resolution cosmological N-body simulations to investigate the inner mass profile of galaxy-sized cold dark matter (CDM) haloes. These simulations extend the numerical convergence study presented in Paper I of this series, and demonstrate that the mass profile of CDM galaxy haloes can be robustly estimated beyond a minimum converged radius of order rconv∼ 1 h−1 kpc in our highest-resolution runs. The density profiles of simulated haloes become progressively shallower from the virial radius inwards, and show no sign of approaching a well-defined power law near the centre. At rconv, the density profile is steeper than expected from the formula proposed by Navarro, Frenk & White, which has a ρ∝r−1 cusp, but significantly shallower than the steeply divergent ρ∝r−1.5 cusp proposed by Moore et al. We perform a direct comparison of the spherically averaged dark matter circular velocity profiles with Hα rotation curves of a sample of low surface brightness (LSB) galaxies. We find that most galaxies in the sample (about 70 per cent) have rotation curves that are consistent with the structure of CDM haloes. Of the remainder, 20 per cent have rotation curves which cannot be fit by any smooth fitting function with few free parameters, and 10 per cent are inconsistent with CDM haloes. However, the latter consist mostly of rotation curves that do not extend to large enough radii to accurately determine their shapes and maximum velocities. We conclude that the inner structure of CDM haloes is not manifestly inconsistent with the rotation curves of LSB galaxies
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".