ANATOMY OF THE BAR INSTABILITY IN CUSPY DARK MATTER HALOS
Bibliographic record
Abstract
We examine the bar instability in galactic models with an exponential disk and a cuspy dark matter (DM) halo with a Navarro–Frenk–White cosmological density profile. The equilibrium models are constructed from a three-integral composite distribution function but subject to the bar instability. We generate a sequence of models with a range of mass resolution from 1.8 K to 18 M particles in the disk and 10 K to 100 M particles in the halo along with a multimass model with an effective resolution of ∼10 10 particles. We describe how mass resolution affects the bar instability, including its linear growth phase, the buckling instability, pattern speed decay through the resonant transfer of angular momentum to the DM halo, and the possible destruction of the halo cusp. Our higher resolution simulations show a converging spectrum of discrete resonance interactions between the bar and DM halo orbits. As the pattern speed decays, orbital resonances sweep through most of the DM halo phase space and widely distribute angular momentum among the halo particles. The halo does not develop a flat density core and preserves the cusp, except in the region dominated by gravitational softening. The formation of the bar increases the central stellar density and the DM is compressed adiabatically increasing the halo central density by 1.7 times. Overall, the evolution of the bar displays a convergent behavior for halo particle numbers between 1 M and 10 M particles, when comparing bar growth, pattern speed evolution, the DM halo density profile and a nonlinear analysis of the orbital resonances. Higher resolution simulations clearly illustrate the importance of discrete resonances in transporting the angular momentum from the bar to the halo.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".