The Cold Dark Matter Halos of Local Group Dwarf Spheroidals
Bibliographic record
Abstract
We use N -body simulations to study the evolution of dwarf spheroidal galaxies (dSphs) driven by galactic tides. We adopt a cosmologically motivated model in which dSphs are approximated by a King model embedded in an NFW halo. We find that these NFW-embedded King models are extraordinarily resilient to tides; the stellar density profile still resembles a King model even after losing more than 99% of the stars. As tides strip the galaxy, the stellar luminosity, velocity dispersion, central surface brightness, and core radius decrease monotonically. Remarkably, we find that the evolution of these parameters is solely controlled by the total amount of mass lost from within the luminous radius. Of all parameters, the core radius is the least affected: after losing 99% of the stars, R c decreases by just a factor of ~2. Interestingly, tides tend to make dSphs more dark matter dominated because the tightly bound central dark matter "cusp" is more resilient to disruption than the "cored" King profile. We examine whether the extremely large mass-to-light ratios of the newly discovered ultrafaint dSphs might have been caused by tidal stripping of once brighter systems. Although dSph tidal evolutionary tracks parallel the observed scaling relations in the luminosity-radius plane, they predict too steep a change in velocity dispersion compared with the observational estimates hitherto reported in the literature. The ultrafaint dwarfs are thus unlikely to be the tidal remnants of systems like Fornax, Draco, or Sagittarius. Despite spanning four decades in luminosity, dSphs appear to inhabit halos of comparable peak circular velocity, lending support to scenarios that envision dwarf spheroidals as able to form only in halos above a certain mass threshold.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".