Simulating non-axisymmetric flows in disk galaxies
Bibliographic record
Abstract
Context. We present a two-step method to simulate and study non-circular motions in strongly barred galaxies. The first step is to constrain the initial parameters using a Bayesian analysis of each galaxy’s azimuthally averaged rotation curve, the 3.6 μm surface brightness, and the gas surface density. The second step is to generate equilibrium models using the GalactICS code and evolve them via GADGET-2. Aims. The bar strengths and mock velocity maps of the resulting snapshots are compared to observations in order to determine the best representation of the galaxy. Methods. We apply our method to the unbarred galaxy NGC 3621 and the barred galaxies NGC 1300 and NGC 1530. NGC 3621 provides a validation of our method of generating initial conditions. NGC 1530 has an intermediate bar orientation that allows for a comparison to DiskFit. Finally NGC 1300 has a bar oriented parallel to the galaxy’s major axis, where other algorithms tend to fail. Results. Our models for NGC 3621 and NGC 1530 are comparable to those obtained using commonly available algorithms. Moreover, we produce one of the first mass distribution models for NGC 1300.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".