<i>Planck</i>2013 results. XVII. Gravitational lensing by large-scale structure
Bibliographic record
Abstract
On the arcminute angular scales probed by Planck, the cosmic microwave background (CMB) anisotropies are gently perturbed by gravitational lensing. Here we present a detailed study of this effect, detecting lensing independently in the 100, 143, and 217 GHz frequency bands with an overall significance of greater than 25σ. We use thetemperature-gradient correlations induced by lensing to reconstruct a (noisy) map of the CMB lensing potential, which provides an integrated measure of the mass distribution back to the CMB last-scattering surface. Our lensing potential map is significantly correlated with other tracers of mass, a fact which we demonstrate using several representative tracers of large-scale structure. We estimate the power spectrum of the lensing potential, finding generally good agreement with expectations from the best-fitting ΛCDM model for the Planck temperature power spectrum, showing that this measurement at z = 1100 correctly predicts the properties of the lower-redshift, later-time structures which source the lensing potential. When combined with the temperature power spectrum, our measurement provides degeneracy-breaking power for parameter constraints; it improves CMB-alone constraints on curvature by a factor of two and also partly breaks the degeneracy between the amplitude of the primordial perturbation power spectrum and the optical depth to reionization, allowing a measurement of the optical depth to reionization which is independent of large-scale polarization data. Discarding scale information, our measurement corresponds to a 4% constraint on the amplitude of the lensing potential power spectrum, or a 2% constraint on the root-mean-squared amplitude of matter fluctuations at z ~ 2.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.088 | 0.049 |
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".