A MegaCam Survey of Outer Halo Satellites. III. Photometric and Structural Parameters*<sup>†</sup>
Bibliographic record
Abstract
Abstract We present structural parameters from a wide-field homogeneous imaging survey of Milky Way satellites carried out with the MegaCam imagers on the 3.6 m Canada–France–Hawaii Telescope and 6.5 m Magellan-Clay telescope. Our survey targets an unbiased sample of “outer halo” satellites (i.e., substructures having galactocentric distances greater than 25 kpc) and includes classical dSph galaxies, ultra-faint dwarfs, and remote globular clusters. We combine deep, panoramic gr imaging for 44 satellites and archival gr imaging for 14 additional objects (primarily obtained with the DECam instrument as part of the Dark Energy Survey) to measure photometric and structural parameters for 58 outer halo satellites. This is the largest and most uniform analysis of Milky Way satellites undertaken to date and represents roughly three-quarters (58/81 ≃ 72%) of all known outer halo satellites. We use a maximum-likelihood method to fit four density laws to each object in our survey: exponential, Plummer, King, and Sérsic models. We systematically examine the isodensity contour maps and color–magnitude diagrams for each of our program objects, present a comparison with previous results, and tabulate our best-fit photometric and structural parameters, including ellipticities, position angles, effective radii, Sérsic indices, absolute magnitudes, and surface brightness measurements. We investigate the distribution of outer halo satellites in the size–magnitude diagram and show that the current sample of outer halo substructures spans a wide range in effective radius, luminosity, and surface brightness, with little evidence for a clean separation into star cluster and galaxy populations at the faintest luminosities and surface brightnesses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".