DWARF GALAXY CLUSTERING AND MISSING SATELLITES
Bibliographic record
Abstract
At redshifts around 0.1 the Canada–France–Hawaii Telescope Legacy Survey Deep fields contain some 6 × 104 galaxies spanning the mass range from 105 to 1012 M☉. We measure the stellar mass dependence of the two-point correlation using angular measurements to largely bypass the errors, approximately 0.02 in the median, of the photometric redshifts. Inverting the power-law fits with Limber's equation we find that the autocorrelation length increases from a very low 0.4 h−1 Mpc at 105.5 M☉ to the conventional 4.5 h−1 Mpc at 1010.5 M☉. The power-law fit to the correlation function has a slope which increases from γ ≃ 1.6 at high mass to γ ≃ 2.3 at low mass. The spatial cross-correlation of dwarf galaxies with more massive galaxies shows fairly similar trends, with a steeper radial dependence at low mass than predicted in numerical simulations of subhalos within galaxy halos. To examine the issue of "missing satellites" we combine the cross-correlation measurements with our estimates of the low-mass galaxy number density. We find on the average there are 60 ± 20 dwarfs in subhalos with M(total)>107 M☉ for a typical Local Group M(total)/M(stars) = 30, corresponding to M/LV ≃ 100 for a galaxy with no recent star formation. The number of dwarfs per galaxy is about a factor of 2 larger than currently found for the Milky Way. Nevertheless, the average dwarf counts are about a factor of 30 below lambda cold dark matter (LCDM) simulation results. The divergence from LCDM predictions is one of the slope of the relation, approximately dN/dln M ≃ −0.5 rather than the predicted −0.9, not sudden onset at some characteristic scale. The dwarf galaxy star formation rates span the range from passive to bursting, which suggests that there are few completely dark halos.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".