Phase Space Structure of Disequilibrium in the Milky Way
Bibliographic record
Abstract
Following Gaia Data Release 2, observations of spiral structure in the vertical phase space of the Milky Way have been made. In this thesis we set out to explain these structures, using a combination of analytic modeling, simulations, and Dynamic Mode Decomposition to study explicitly their formation and evolution in the presence of self gravity. In doing so, we have demonstrated the first application of DMD to collisionless, self-gravitating systems. We show by comparison of self-gravitating and independent-particle simulations in a realistic Milky Way model, that the timescale of phase space spiral formation is drastically dependent on whether or not stars mutually interact. This is followed by the proposition that mutually interacting stars in a background potential conducive to oscillations can produce a persisting spiral in their phase space distribution, existing on much longer time scales than predicted by traditional kinematic phase mixing arguments. Our proposition is investigated with use of Dynamic Mode Decomposition, which facilitates determining eigenfunctions of the time evolution operator of a system from data snapshots. We apply this to two one-dimensional models for the vertical structure of the Milky Way: the homogeneous slab, and the isothermal plane. We found that the eigenfunctions, or modes, determined for a self-gravitating system undergoing phase mixing comprise a set of modes similar to what is expected from linear perturbation theory. Particularly, the disequilibrium distribution function can be modeled as the superposition of an equilibrium mode and a combination of perturbative modes, all computed directly from snapshots of the system. DMD solutions are determined for the isothermal plane model with a variable relative dominance of self-gravity and background potential. We find that there is a regime of relative dominance where modes of the distribution function containing pronounced spiral structure can persist on extremely long time scales. This implies that a single snapshot of a phase space spiral could belong to an evolution where the distribution function remains in a spiral for long times, driven by mutual interactions, as opposed to the spiral being a short lived transient response as in kinematic phase mixing.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".