The impact of dark matter cusps and cores on the satellite galaxy population around spiral galaxies
Bibliographic record
Abstract
We use N-body simulations to study the effects that a divergent (i.e. ‘cuspy’) dark matter profile introduces on the tidal evolution of dwarf spheroidal galaxies (dSphs). Our models assume cosmologically motivated initial conditions where dSphs are dark-matter-dominated systems on eccentric orbits about a host galaxy composed of a dark halo and a baryonic disc. We find that the resilience of dSphs to tidal stripping is extremely sensitive to the cuspiness of the inner halo profile; whereas dwarfs with a cored profile can be easily destroyed by the disc component, those with cusps always retain a bound remnant, even after losing more than 99.99 per cent of the original mass. For a given halo profile, the evolution of the structural parameters as driven by tides is controlled solely by the total amount of mass lost. This information is used to construct a semi-analytic code that follows the tidal evolution of individual satellites as they fall into a more massive host, which allows us to simulate the hierarchical build-up of spiral galaxies assuming different halo profiles and disc masses. We find that tidal encounters with discs tend to decrease the average mass of satellite galaxies at all galactocentric radii. Of all satellites, those accreted before re-ionization (z≳ 6), which may be singled out by anomalous metallicity patterns, provide the strongest constraints on the inner profile of dark haloes. These galaxies move on orbits that penetrate the disc repeatedly and survive to the present day only if haloes have an inner density cusp. We show that the size–mass relationship established from Milky Way (MW) dwarfs strongly supports the presence of cusps in the majority of these systems, as cored models systematically underestimate the masses of the known ultra-faint dSphs. Our models also indicate that a massive M31 disc may explain why many of its dSphs with suitable kinematic data fall below the size–mass relationship derived from MW dSphs. We also examine whether our modelling can constrain the mass threshold below which star formation is suppressed in dark matter haloes. We find that luminous satellites must be accreted with masses above 108–109 M⊙ in order to explain the size–mass relation observed in MW dwarfs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".