The core–cusp problem: a matter of perspective
Bibliographic record
Abstract
The existence of two kinematically and chemically distinct stellar subpopulations in the Sculptor and Fornax dwarf galaxies offers the opportunity to constrain the density profile of their matter haloes by measuring the mass contained within the well-separated half-light radii of the two metallicity subpopulations. Walker and Peñarrubia have used this approach to argue that data for these galaxies are consistent with constant-density ‘cores’ in their inner regions and rule out ‘cuspy’ Navarro–Frenk–White (NFW) profiles with high statistical significance, particularly in the case of Sculptor. We test the validity of these claims using dwarf galaxies in the APOSTLE (A Project Of Simulating The Local Environment) Λ cold dark matter cosmological hydrodynamic simulations of analogues of the Local Group. These galaxies all have NFW dark matter density profiles and a subset of them develop two distinct metallicity subpopulations reminiscent of Sculptor and Fornax. We apply a method analogous to that of Walker and Peñarrubia to a sample of 50 simulated dwarfs and find that this procedure often leads to a statistically significant detection of a core in the profile when in reality there is a cusp. Although multiple factors contribute to these failures, the main cause is a violation of the assumption of spherical symmetry upon which the mass estimators are based. The stellar populations of the simulated dwarfs tend to be significantly elongated and, in several cases, the two metallicity populations have different asphericity and are misaligned. As a result, a wide range of slopes of the density profile are inferred depending on the angle from which the galaxy is viewed.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.006 | 0.019 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".