The PAndAS View of the Andromeda Satellite System. IV. Global Properties
Bibliographic record
Abstract
Abstract We build a statistical framework to infer the global properties of the satellite system of the Andromeda galaxy (M31) from the properties of individual dwarf galaxies located in the Pan-Andromeda Archaelogical Survey (PAndAS) and the previously determined completeness of the survey. Using forward modeling, we infer the slope of the luminosity function of the satellite system, the slope of its spatial density distribution, and the size–luminosity relation followed by the dwarf galaxies. We find that the slope of the luminosity function is β = −1.5 ± 0.1. Combined with the spatial density profile, it implies that, when accounting for survey incompleteness, M31 hosts 92 − 26 + 19 dwarf galaxies with M V < −5.5 and a sky-projected distance from M31 between 30 and 300 kpc. We conclude that many faint or distant dwarf galaxies remain to be discovered around Andromeda, especially outside the PAndAS footprint. Finally, we use our model to test if the higher number of satellites situated in the hemisphere facing the Milky Way could be explained simply by the detection limits of dwarf galaxy searches. We rule this out at >99.9% confidence and conclude that this anisotropy is an intrinsic feature of the M31 satellite system. The statistical framework we present here is a powerful tool to robustly constrain the properties of a satellite system and compare those across hosts, especially considering the upcoming start of the Euclid or Rubin large photometric surveys that are expected to uncover a large number of dwarf galaxies in the Local Volume.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.007 |
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".