Creating a galaxy lacking dark matter in a dark matter-dominated universe
Bibliographic record
Abstract
ABSTRACT We use hydrodynamical cosmological simulations to show that it is possible to create, via tidal interactions, galaxies lacking dark matter (DM) in a DM-dominated universe. We select dwarf galaxies from the NIHAO project, obtained in the standard cold dark matter model and use them as initial conditions for simulations of satellite–central interactions. After just one pericentric passage on an orbit with a strong radial component, NIHAO dwarf galaxies can lose up to 80 per cent of their DM content, but, most interestingly, their central (≈8 kpc) DM-to-stellar mass ratio changes from a value of ∼25, as expected from numerical simulations and abundance matching techniques, to roughly unity as reported for NGC 1052-DF2 and NGC 1054-DF4. The stellar velocity dispersion drops from ∼30 $\, \rm km\, s^{-1}$ before infall to values as low as 6 ± 2 $\, \rm km\, s^{-1}$. These, and the half-light radius around 3 kpc, are in good agreement with observations from van Dokkum and collaborators. Our study shows that it is possible to create a galaxy without DM starting from typical dwarf galaxies formed in a DM-dominated universe, provided they live in a dense environment.
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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 | 0.001 |
| 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".