The Dragonfly Nearby Galaxies Survey. III. The Luminosity Function of the M101 Group
Bibliographic record
Abstract
Abstract We obtained follow-up HST observations of the seven low surface brightness galaxies discovered with the Dragonfly Telephoto Array in the field of the massive spiral galaxy M101. Out of the seven galaxies, only three were resolved into stars and are potentially associated with the M101 group at D = 7 Mpc. Based on HST ACS photometry in the broad F606W and F814W filters, we use a maximum likelihood algorithm to locate the Tip of the Red Giant Branch in galaxy color–magnitude diagrams. Distances are and and we confirm that they are members of the M101 group. Combining the three confirmed low-luminosity satellites with previous results for brighter group members, we find the M101 galaxy group to be a sparsely populated galaxy group consisting of seven group members, down to M V = −9.2 mag. We compare the M101 cumulative luminosity function to that of the Milky Way and M31. We find that they are remarkably similar; in fact, the cumulative luminosity function of the M101 group gets even flatter for fainter magnitudes, and we show that the M101 group might exhibit the two known small-scale flaws in the ΛCDM model, namely “the missing satellite” problem and the “too big to fail” problem. Kinematic measurements of M101's satellite galaxies are required to determine whether the “too big to fail” problem does in fact exist in the M101 group.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".