CMB delensing beyond the<i>B</i>modes
Bibliographic record
Abstract
Gravitational lensing by large-scale structure significantly impacts observations of the cosmic microwave background (CMB): it smooths the acoustic peaks in temperature and E -mode polarization power spectra, correlating previously uncorrelated modes; and it converts E -mode polarization into B -mode polarization. The act of measuring and removing the effect of lensing from CMB maps, or delensing, has been well studied in the context of B modes, but little attention has been given to the delensing of the temperature and E modes. In this paper, we model the expected delensed T and E power spectra to all orders in the lensing potential, demonstrating the sharpening of the acoustic peaks and a significant reduction in lens-induced power spectrum covariances. We then perform cosmological forecasts, demonstrating that delensing will yield improved sensitivity to parameters with upcoming surveys. We highlight the breaking of the degeneracy between the effective number of neutrino species and primordial helium fraction as a concrete application. We also show that delensing increases cosmological information as long as the measured lensing reconstruction is included in the analysis. We conclude that with future data, delensing will be crucial not only for primordial B -mode science but for a range of other observables as well.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".