NIHAO – IV: core creation and destruction in dark matter density profiles across cosmic time
Bibliographic record
Abstract
We use the NIHAO (Numerical Investigation of Hundred Astrophysical Objects) cosmological simulations to investigate the effects of baryonic physics on the time evolution of dark matter central density profiles. The sample is made of &ap;70 independent high-resolution hydrodynamical simulations of galaxy formation and covers a wide mass range: 1010 &lsim; <it>M</it><inf>halo</inf>/M<inf>&odot;</inf> &lsim; 1012, i.e. from dwarfs to <it>L</it>&sstarf;. We confirm previous results on the dependence of the inner dark matter density slope, α, on the ratio between stellar-to-halo mass, <it>M</it><inf>star</inf>/<it>M</it><inf>halo</inf>. We show that this relation holds approximately at all redshifts (with an intrinsic scatter of ∼0.18 in α measured between 1 and 2 per cent of the virial radius). This implies that in practically all haloes the shape of their inner density profile changes quite substantially over cosmic time, as they grow in stellar and total mass. Thus, depending on their final <it>M</it><inf>star</inf>/<it>M</it><inf>halo</inf> ratio, haloes can either form and keep a substantial density core (<it>R</it><inf>core</inf> ∼ 1 kpc), or form and then destroy the core and recontract the halo, going back to a cuspy profile, which is even steeper than cold-dark-matter predictions for massive galaxies (1012 M<inf>&odot;</inf>). We show that results from the NIHAO suite are in good agreement with recent observational measurements of α in dwarf galaxies. Overall our results suggest that the notion of a universal density profile for dark matter haloes is no longer valid in the presence of galaxy formation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".