A rogues gallery of Andromeda’s dwarf galaxies – II. Precise distances to 17 faint satellites
Bibliographic record
Abstract
ABSTRACT We present new horizontal branch (HB) distance measurements to 17 of the faintest known M31 satellites (−6 ≲ MV ≲ −13) based on deep Hubble Space Telescope (HST) imaging. The colour–magnitude diagrams extend ∼1–2 mag below the HB, which provides for well-defined HBs, even for faint galaxies in which the tip of the red giant branch (TRGB) is sparsely populated. We determine distances across the sample to an average precision of 4 per cent (∼30 kpc at 800 kpc). We find that the majority of these galaxies are in good agreement, though slightly farther (0.1–0.2 mag) when compared to recent ground-based TRGB distances. Two galaxies (And IX and And XVII) have discrepant HST and ground-based distances by ∼0.3 mag (∼150 kpc), which may be due to contamination from Milky Way foreground stars and/or M31 halo stars in sparsely populated TRGB regions. We use the new distances to update the luminosities and structural parameters for these 17 M31 satellites. The new distances do not substantially change the spatial configuration of the M31 satellite system. We comment on future prospects for precise and accurate HB distances for faint galaxies in the Local Group and beyond.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".