Bibliographic record
Abstract
We present an axisymmetric, equilibrium model for late-type galaxies which consists of an exponential disk, a Sersic bulge, and a cuspy dark halo. The model is specified by a phase space distribution function which, in turn, depends on the integrals of motion. Bayesian statistics and the Markov Chain Monte Carlo method are used to tailor the model to satisfy observational data and theoretical constraints. By way of example, we construct a chain of 10^5 models for the Milky Way designed to fit a wide range of photometric and kinematic observations. From this chain, we calculate the probability distribution function of important Galactic parameters such as the Sersic index of the bulge, the disk scale length, and the disk, bulge, and halo masses. We also calculate the probability distribution function of the local dark matter velocity dispersion and density, two quantities of paramount significance for terrestrial dark matter detection experiments. Though the Milky Way models in our chain all satisfy the prescribed observational constraints, they vary considerably in key structural parameters and therefore respond differently to non-axisymmetric perturbations. We simulate the evolution of twenty-five models which have different Toomre Q and Goldreich-Tremaine X parameters. Virtually all of these models form a bar, though some, more quickly than others. The bar pattern speeds are ~ 40 - 50 km/s/kpc at the time when they form and then decrease, presumably due to coupling of the bar with the halo. Since the Galactic bar has a pattern speed ~50 km/s/kpc we conclude that it must have formed recently.
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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 | 0.001 | 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".