Comparing the Quenching Times of Faint M31 and Milky Way Satellite Galaxies
Bibliographic record
Abstract
Abstract We present the star formation histories (SFHs) of 20 faint M31 satellites (−12 ≲ M V ≲ −6) that were measured by modeling sub-horizontal branch depth color–magnitude diagrams constructed from Hubble Space Telescope (HST) imaging. Reinforcing previous results, we find that virtually all galaxies quenched between 3 and 9 Gyr ago, independent of luminosity, with a notable concentration 3–6 Gyr ago. This is in contrast to the Milky Way (MW) satellites, which are generally either faint with ancient quenching times or luminous with recent (<3 Gyr) quenching times. We suggest that systematic differences in the quenching times of M31 and MW satellites may be a reflection of the varying accretion histories of M31 and the MW. This result implies that the formation histories of low-mass satellites may not be broadly representative of low-mass galaxies in general. Among the M31 satellite population we identify two distinct groups based on their SFHs: one with exponentially declining SFHs (τ ∼ 2 Gyr) and one with rising SFHs with abrupt quenching. We speculate how these two groups could be related to scenarios for a recent major merger involving M31. The Cycle 27 HST Treasury survey of M31 satellites will provide well-constrained ancient SFHs to go along with the quenching times we measure here. The discovery and characterization of M31 satellites with M V ≳ −6 would help quantify the relative contributions of reionization and environment to quenching of the lowest-mass satellites.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".