CFHTLenS: combined probe cosmological model comparison using 2D weak gravitational lensing
Bibliographic record
Abstract
We present cosmological constraints from 2D weak gravitational lensing by the large-scale structure in the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) which spans 154 deg2 in five optical bands. Using accurate photometric redshifts and measured shapes for 4.2 million galaxies between redshifts of 0.2 and 1.3, we compute the 2D cosmic shear correlation function over angular scales ranging between 0.8 and 350 arcmin. Using non-linear models of the dark-matter power spectrum, we constrain cosmological parameters by exploring the parameter space with Population Monte Carlo sampling. The best constraints from lensing alone are obtained for the small-scale density-fluctuations amplitude σ8 scaled with the total matter density Ωm. For a flat Λcold dark matter (ΛCDM) model we obtain σ8(Ωm/0.27)0.6 = 0.79 ± 0.03. We combine the CFHTLenS data with 7-year Wilkinson Microwave Anisotropy Probe (WMAP7), baryonic acoustic oscillations (BAO): SDSS-III (BOSS) and a Hubble Space Telescope distance-ladder prior on the Hubble constant to get joint constraints. For a flat ΛCDM model, we find Ωm = 0.283 ± 0.010 and σ8 = 0.813 ± 0.014. In the case of a curved wCDM universe, we obtain Ωm = 0.27 ± 0.03, σ8 = 0.83 ± 0.04, w0 = −1.10 ± 0.15 and ΩK = 0.006+ 0.006− 0.004. We calculate the Bayesian evidence to compare flat and curved ΛCDM and dark-energy CDM models. From the combination of all four probes, we find models with curvature to be at moderately disfavoured with respect to the flat case. A simple dark-energy model is indistinguishable from ΛCDM. Our results therefore do not necessitate any deviations from the standard cosmological model.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".