The luminosity function of diverse satellite galaxy systems
Bibliographic record
Abstract
The high-resolution, smoothed particle hydrodynamics galaxies of the McMaster Unbiased Galaxy Survey are used to examine the satellite systems of 16 model host galaxies. Each galaxy has a different mass, angular momentum and merger history that yield a rich set of satellite luminosity functions. With new observations of distant satellite systems, we can compare these luminosity functions to satellite systems beyond the Local Group. We find that the luminosity functions of our simulations compare well to observations when the luminosity functions are scaled according to host mass. We use the recently found relationship between dwarf satellites and host mass in distant satellite systems to normalize a theoretical, complete luminosity function for the Milky Way. The luminosity function of satellites, expressed as a function of the host mass, is given by |$\mathrm{d}N/\mathrm{d}M_V=3.5M_{\rm host}^{0.91}\times 10^{0.1M_V-10.2}$|, where mass is given in M⊙. The mass of a host galaxy can be used to predict the number of dwarf satellites and even when considering spiral and elliptical hosts separately this relation holds.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".