Simulating the Milky Way bar and bulge with an initially Sérsic disc
Bibliographic record
Abstract
Abstract We model the formation of a bar plus box/peanut bulge (BP bulge) component in a Milky Way-like disc galaxy using simulations of isolated multi-component systems that evolve from equilibrium initial conditions. The simulations are designed to test the hypothesis that the bar forms early on and thickens to create the bulge. To this end, our initial conditions include a stellar disc with a Sérsic surface density profile and do not include any classical bulge component. We also include a gas disc, which is important in regulating the growth of the bar. Our best-fit model has an initial stellar disc with a Sersic index of n = 1.75 and a gas disc with mass equal to 7% of the mass of the stellar disc. The model reproduces the bar size, pattern speed, and box/peanut shape of the Milky Way’s bulge+bar.
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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 | 0.000 | 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 | 0.001 |
| 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".