Angular momentum transport and disc morphology in smoothed particle hydrodynamics simulations of galaxy formation
Bibliographic record
Abstract
We perform controlled N-body/smoothed particle hydrodynamics simulations of disc galaxy formation by cooling a rotating gaseous mass distribution inside equilibrium cuspy spherical and triaxial dark matter haloes. We systematically study the angular momentum transport and the disc morphology as we increase the number of dark matter and gas particles from 104 to 106, and decrease the gravitational softening from 2 kpc to 50 pc. The angular momentum transport, disc morphology and radial profiles depend sensitively on force and mass resolution. At low resolution, similar to that used in most current cosmological simulations, the cold gas component has lost half of its initial angular momentum via different mechanisms. The angular momentum is transferred primarily to the hot halo component, by resolution-dependent hydrodynamical and gravitational torques; the latter arising from asymmetries in the mass distribution. In addition, disc particles can lose angular momentum while they are still in the hot phase by artificial viscosity. In the central disc, particles can transfer away over 99 per cent of their initial angular momentum due to spiral structure and/or the presence of a central bar. The strength of this transport also depends on force and mass resolution – large softening will suppress the bar instability, and low mass resolution enhances the spiral structure. This complex interplay between resolution and angular momentum transfer highlights the complexity of simulations of galaxy formation even in isolated haloes. With 106 gas and dark matter particles, disc particles lose only 10–20 per cent of their original angular momentum, yet we are unable to produce pure exponential profiles due to the steep density peak of baryons within the central kpc. We speculate that the central luminosity excess observed in many Sc–Sd galaxies may be due to star formation in gas that has been transported to the central regions by spiral patterns.
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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".