FIRST RESULTS FROM THE DRAGONFLY TELEPHOTO ARRAY: THE APPARENT LACK OF A STELLAR HALO IN THE MASSIVE SPIRAL GALAXY M101
Bibliographic record
Abstract
We use a new telescope concept, the Dragonfly Telephoto Array, to study the low surface brightness outskirts of the spiral galaxy M101. The radial surface brightness profile is measured down to μ g ∼ 32 mag arcsec −2 , a depth that approaches the sensitivity of star count studies in the Local Group. We convert surface brightness to surface mass density using the radial g − r color profile. The mass density profile shows no significant upturn at large radius and is well-approximated by a simple bulge + disk model out to R = 70 kpc, corresponding to 18 disk scale lengths. Fitting a bulge + disk + halo model we find that the best-fitting halo mass M ☉ . The total stellar mass of M101 is M ☉ , and we infer that the halo mass fraction . This mass fraction is lower than that of the Milky Way ( f halo ∼ 0.02) and M31 ( f halo ∼ 0.04). All three galaxies fall below the f halo – M tot, * relation predicted by recent cosmological simulations that trace the light of disrupted satellites, with M101's halo mass a factor of ∼10 below the median expectation. However, the predicted scatter in this relation is large, and more galaxies are needed to better quantify this possible tension with galaxy formation models. Dragonfly is well suited for this project: as integrated-light surface brightness is independent of distance, large numbers of galaxies can be studied in a uniform way.
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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 | 0.000 |
| 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) | 0.001 | 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".