The Masses and Shapes of Dark Matter Halos from Galaxy‐Galaxy Lensing in the CFHT Legacy Survey
Bibliographic record
Abstract
We present the first galaxy-galaxy weak-lensing results using early data from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS). These results are based on ~22 deg 2 of i ' data. From these data, we estimate the average velocity dispersion for an L * galaxy at a redshift of 0.3 to be 137 ± 11 km s -1 , with a virial mass, M 200 , of (1.1 ± 0.2) × 10 12 h -1 M ☉ and a rest-frame mass-to-light ratio of 173 ± 34 h M ☉ / L . We also investigate various possible sources of systematic error in detail. In addition, we separate our lens sample into two subsamples, divided by apparent magnitude and thus average redshift. From these early data we do not detect significant evolution in galaxy dark matter halo mass-to-light ratios at redshifts from 0.45 to 0.27. Finally, we test for nonspherical galaxy dark matter halos. Our results favor a dark matter halo with an ellipticity of ~0.3 at the 2 σ level when averaged over all galaxies. If the sample of foreground lens galaxies is selected to favor elliptical galaxies, the mean halo ellipticity and significance of this result increase.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".