Discovery of Diffuse Dwarf Galaxy Candidates around M101
Bibliographic record
Abstract
Abstract We have conducted a search of a 9 deg 2 region of the Canada–France–Hawaii-Telescope Legacy Survey around the Milky Way analog M101 ( D ∼ 7 Mpc), in order to look for previously unknown low-surface-brightness galaxies. This search has uncovered 38 new low-surface-brightness dwarf candidates, and confirmed 11 previously reported galaxies, all with central surface brightness μ ( g , 0) > 23 mag arcsec −2 , potentially extending the satellite luminosity function for the M101 group by ∼1.2 mag. The search was conducted using an algorithm that nearly automates the detection of diffuse dwarf galaxies. The candidates’ small sizes and low surface brightnesses mean that the faintest of these objects would likely be missed by traditional visual or computer detection techniques. The dwarf galaxy candidates span a range of −7.1 ≥ M g ≥ −10.2 and half-light radii of 118–540 pc at the distance of M101, and they are well fit by simple Sérsic surface brightness profiles. These properties are consistent with dwarfs in the Local Group, and to match the Local Group luminosity function, ∼10–20 of these candidates should be satellites of M101. Association with a massive host is supported by the lack of detected star formation and the overdensity of candidates around M101 compared to the field. The spatial distribution of the dwarf candidates is highly asymmetric, and concentrated to the northeast of M101, therefore distance measurements will be required to determine if these are genuine members of 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".