Quantifying the Impact of the Large Magellanic Cloud on the Structure of the Milky Way’s Dark Matter Halo Using Basis Function Expansions
Bibliographic record
Abstract
Abstract Indications of disequilibrium throughout the Milky Way (MW) highlight the need for compact, flexible, non-parametric descriptions of phase–space distributions of galaxies. We present a new representation of the current dark matter (DM) distribution and potential derived from N -body simulations of the MW and Large Magellanic Cloud (LMC) system using basis function expansions (BFEs). We incorporate methods to maximize the physical signal in the representation. As a result, the simulations of 10 8 DM particles representing the distorted MW(MW+LMC) system can be described by ∼236(2067) coefficients. We find that the LMC induces asymmetric perturbations (odd l, m ) to the MW’s halo, which are inconsistent with oblate, prolate, or triaxial halos. Furthermore, the energy in high order even modes ( l , m > 2) is similar to average triaxial halos found in cosmological simulations. As such, the response of the MW’s halo to the LMC must be accounted for in order to recover the imprints of its assembly history. The LMC causes the outer halo (>30 kpc) to shift from the disk center of mass (COM) by ∼15–25 kpc at present day, manifesting as a dipole in the BFE and in the radial velocities of halo stars. The shift depends on the LMC’s infall mass, the distortion of the LMC’s halo and the MW halo response.Within 30 kpc, halo tracers are expected to orbit the COM of the MW’s disk, regardless of LMC infall mass. The LMC’s halo is also distorted by MW tides; we discuss the implications for its mass loss and the subsequent effects on current Magellanic satellites.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".