Exploring the Sgr–Milky Way–disk Interaction Using High-resolution N-body Simulations
Bibliographic record
Abstract
Abstract The ongoing merger of the Sagittarius (Sgr) dwarf galaxy with the Milky Way is believed to strongly affect the dynamics of the Milky Way’s disk. We present a suite of 13 N -body simulations, with 500 million–1 billion particles, modeling the interaction between the Sgr dwarf galaxy and the Galactic disk. To quantify the perturbation to the disk’s structure and dynamics in the simulation, we compute the number count asymmetry and the mean vertical velocity in a solar-neighborhood-like volume. We find that, overall, the trends in the simulations match those seen in a simple one-dimensional model of the interaction. We explore the effects of changing the mass model of Sgr, the orbital kinematics of Sgr, and the mass of the Milky Way halo. We find that none of the simulations match the observations of the vertical perturbation using Gaia Data Release 2. In the simulation that is the most similar, we find that the final mass of Sgr far exceeds the observed mass of the Sgr remnant, the asymmetry wavelength is too large, and the shape of the asymmetry does not match past z ≈ 0.7 kpc. We therefore conclude that our simulations support the conclusion that Sgr alone could not have caused the observed perturbation to the solar neighborhood.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".