The Weak Lensing Signal and the Clustering of BOSS Galaxies II: Astrophysical and Cosmological Constraints
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We perform a joint analysis of the abundance, the clustering, and the galaxy–galaxy lensing signal of galaxies measured from Data Release 11 of the Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey in our companion paper, Miyatake et al. The lensing signal was obtained by using the shape catalog of background galaxies from the Canada France Hawaii Telescope Legacy Survey, which was made publicly available by the CFHTLenS collaboration, with an area overlap of about 105 deg2. We analyze the data in the framework of the halo model in order to fit halo occupation parameters and cosmological parameters (Ω and ) to these observables simultaneously, and thus break the degeneracy between galaxy bias and cosmology. Adopting a flat ΛCDM cosmology with priors on Ω, , and <em>h</em> from the analysis of<em>WMAP</em> 9 yr data, we obtain constraints on the stellar mass–halo mass relation of galaxies in our sample. Marginalizing over the halo occupation distribution parameters and a number of other nuisance parameters in our model, we obtain Ω and (68% confidence). We demonstrate the robustness of our results with respect to sample selection and a variety of systematics such as the halo off-centering effect and possible incompleteness in our sample. Our constraints are consistent, complementary, and competitive with those obtained using other independent probes of these cosmological parameters. The cosmological analysis is the first of its kind to be performed at a redshift as high as 0.53.
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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 | 0.001 | 0.003 |
| 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 it