Structure of the Milky Way stellar halo out to its outer boundary with blue horizontal-branch stars
Bibliographic record
Abstract
Abstract We present the structure of the Milky Way stellar halo beyond Galactocentric distances of r = 50 kpc traced by blue horizontal-branch (BHB) stars, which are extracted from the survey data in the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). We select BHB candidates based on (g, r, i, z) photometry, where the z-band is on the Paschen series and the colors that involve the z-band are sensitive to surface gravity. About 450 BHB candidates are identified between r = 50 kpc and 300 kpc, most of which are beyond the reach of previous large surveys, including the Sloan Digital Sky Survey. We find that the global structure of the stellar halo in this range has substructures, which are especially remarkable in the GAMA15H and XMM-LSS fields in the HSC-SSP. We find that the stellar halo can be fitted to a single power-law density profile with an index of α ≃ 3.3 (3.5) with (without) these fields and its global axial ratio is q ≃ 2.2 (1.3). Thus, the stellar halo may be significantly disturbed and be made in a prolate form by halo substructures, perhaps associated with the Sagittarius stream in its extension beyond r ∼ 100 kpc. For a broken power-law model allowing different power-law indices inside/outside a break radius, we obtain a steep power-law slope of α ≃ 5 outside a break radius of ∼100 kpc (200 kpc) for the case with (without) GAMA15H and XMM-LSS. This radius of 200 kpc might be as close as a halo boundary if there is any, although a larger BHB sample is required from further HSC-SSP surveys to increase its statistical significance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".