The Large-scale Structure of the Halo of the Andromeda Galaxy. II. Hierarchical Structure in the Pan-Andromeda Archaeological Survey
Bibliographic record
Abstract
Abstract The Pan-Andromeda Archaeological Survey is a survey of >400 square degrees centered on the Andromeda (M31) and Triangulum (M33) galaxies that has provided the most extensive panorama of an L ⋆ galaxy group to large projected galactocentric radii. Here, we collate and summarize the current status of our knowledge of the substructures in the stellar halo of M31, and discuss connections between these features. We estimate that the 13 most distinctive substructures were produced by at least 5 different accretion events, all in the last 3 or 4 Gyr. We suggest that a few of the substructures farthest from M31 may be shells from a single accretion event. We calculate the luminosities of some prominent substructures for which previous estimates were not available, and we estimate the stellar mass budget of the outer halo of M31. We revisit the problem of quantifying the properties of a highly structured data set; specifically, we use the OPTICS clustering algorithm to quantify the hierarchical structure of M31's stellar halo and identify three new faint structures. M31's halo, in projection, appears to be dominated by two “mega-structures,” which can be considered as the two most significant branches of a merger tree produced by breaking M31's stellar halo into increasingly smaller structures based on the stellar spatial clustering. We conclude that OPTICS is a powerful algorithm that could be used in any astronomical application involving the hierarchical clustering of points. The publication of this article coincides with the public release of all PAndAS data products.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".