Cosmic discordance: are Planck CMB and CFHTLenS weak lensing measurements out of tune?
Bibliographic record
Abstract
We examine the level of agreement between low-redshift weak lensing data and the cosmic microwave background using measurements from the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) and Planck+Wilkinson Microwave Anisotropy Probe (WMAP) polarization. We perform an independent analysis of the CFHTLenS six bin tomography results of Heymans et al. We extend their systematics treatment and find the cosmological constraints to be relatively robust to the choice of non-linear modelling, extension to the intrinsic alignment model and inclusion of baryons. We find that when marginalized in the Ωm–σ8 plane, the 95 per cent confidence contours of CFHTLenS and Planck+WMAP only just touch, but the discrepancy is less significant in the full six-dimensional parameter space of Λ cold dark matter (ΛCDM). Allowing a massive active neutrino or tensor modes does not significantly resolve the tension in the full n-dimensional parameter space. Our results differ from some in the literature because we use the full tomographic information in the weak lensing data and marginalize over systematics. We note that adding a sterile neutrino to ΛCDM brings the 2D marginalized contours into greater overlap, mainly due to the extra effective number of neutrino species, which we find to be 0.88 ± 0.43 (68 per cent) greater than standard on combining the data sets. We discuss why this is not a completely satisfactory resolution, leaving open the possibility of other new physics or observational systematics as contributing factors. We provide updated cosmology fitting functions for the CFHTLenS constraints and discuss the differences from ones used in the literature.
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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 | 0.010 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".