First galaxy–galaxy lensing measurement of satellite halo mass in the CFHT Stripe-82 Survey
Bibliographic record
Abstract
We select satellite galaxies from the galaxy group catalogue constructed with the Sloan Digital Sky Survey spectroscopic galaxies and measure the tangential shear around these galaxies with the source catalogue extracted from the Canada–France–Hawaii Telescope Stripe-82 Survey. Using the tangential shear, we constrain the mass of subhaloes associated with these satellites. The lensing signal is measured around satellites in groups with masses in the range 1013−5 × 1014h−1 M⊙, and is found to agree well with theoretical expectations. Fitting the data with a truncated NFW profile, we obtain an average subhalo mass of log (Msub/h−1 M⊙) = 11.68 ± 0.67 for satellites whose projected distances to central galaxies are in the range 0.1−0.3 h−1 and log (Msub/h−1 M⊙) = 11.68 ± 0.76 for satellites with projected halo-centric distance in [0.3, 0.5] h−1 Mpc. The best-fitting subhalo masses are comparable to the truncated subhalo masses assigned to satellite galaxies using abundance matching and are about 5–10 times higher than the average stellar mass of the lensing satellite galaxies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".