The Stellar Halo of the Galaxy is Tilted and Doubly Broken
Bibliographic record
Abstract
Abstract Modern Galactic surveys have revealed an ancient merger that dominates the stellar halo of our galaxy (Gaia–Sausage–Enceladus, GSE). Using chemical abundances and kinematics from the H3 Survey, we identify 5559 halo stars from this merger in the radial range r Gal = 6–60kpc. We forward model the full selection function of H3 to infer the density profile of this accreted component of the stellar halo. We consider a general ellipsoid with principal axes allowed to rotate with respect to the galactocentric axes, coupled with a multiply broken power law. The best-fit model is a triaxial ellipsoid (axes ratios 10:8:7) tilted 25° above the Galactic plane toward the Sun and a doubly broken power law with breaking radii at 12 kpc and 28 kpc. The doubly broken power law resolves a long-standing dichotomy in literature values of the halo breaking radius, being at either ∼15 kpc or ∼30 kpc assuming a singly broken power law. N -body simulations suggest that the breaking radii are connected to apocenter pile-ups of stellar orbits, and so the observed double-break provides new insight into the initial conditions and evolution of the GSE merger. Furthermore, the tilt and triaxiality of the stellar halo could imply that a fraction of the underlying dark matter halo is also tilted and triaxial. This has important implications for dynamical mass modeling of the galaxy as well as direct dark matter detection experiments.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".