The M101 Satellite Luminosity Function and the Halo–Halo Scatter among Local Volume Hosts
Bibliographic record
Abstract
Abstract We have obtained deep Hubble Space Telescope (HST) imaging of 19 dwarf galaxy candidates in the vicinity of M101. Advanced Camera for Surveys HST photometry for two of these objects showed resolved stellar populations and tip of the red giant branch derived distances (D ∼ 7 Mpc) consistent with M101 group membership. The remaining 17 were found to have no resolved stellar populations, meaning they are either part of the background NGC 5485 group or are distant low surface brightness (LSB) galaxies. It is noteworthy that many LSB objects that had previously been assumed to be M101 group members based on projection have been shown to be background objects, indicating the need for future diffuse dwarf surveys to be very careful in drawing conclusions about group membership without robust distance estimates. In this work we update the satellite luminosity function of M101 based on the presence of these new objects down to M V = −8.2. M101 is a sparsely populated system with only nine satellites down to M V ≈ −8, as compared with 26 for M31 and 24.5 ± 7.7 for the median host in the Local Volume. This makes M101 by far the sparsest group probed to this depth, although M94 is even sparser to the depth at which it has been examined (M V = −9.1). M101 and M94 share several properties that mark them as unusual compared with the other Local Volume galaxies examined: they have a very sparse satellite population but also have high star-forming fractions among these satellites; such properties are also found in the galaxies examined as part of the Satellites around Galactic Analogs survey. We suggest that these properties appear to be tied to the wider galactic environment, with more isolated galaxies showing sparse satellite populations that are more likely to have had recent star formation, while those in dense environments have more satellites that tend to have no ongoing star formation. Overall, our results show a level of halo-to-halo scatter between galaxies of similar mass that is larger than is predicted in the lambda cold dark matter model.
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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".