Planck 2018 results
Bibliographic record
Abstract
We present measurements of the cosmic microwave background (CMB) lensing potential using the final $\textit{Planck}$ 2018 temperature and polarization data. We increase the significance of the detection of lensing in the polarization maps from $5\,σ$ to $9\,σ$. Combined with temperature, lensing is detected at $40\,σ$. We present an extensive set of tests of the robustness of the lensing-potential power spectrum, and construct a minimum-variance estimator likelihood over lensing multipoles $8 \le L \le 400$. We find good consistency between lensing constraints and the results from the $\textit{Planck}$ CMB power spectra within the $\rm{ΛCDM}$ model. Combined with baryon density and other weak priors, the lensing analysis alone constrains $σ_8 Ω_{\rm m}^{0.25}=0.589\pm 0.020$ ($1\,σ$ errors). Also combining with baryon acoustic oscillation (BAO) data, we find tight individual parameter constraints, $σ_8=0.811\pm0.019$, $H_0=67.9_{-1.3}^{+1.2}\,\text{km}\,\text{s}^{-1}\,\rm{Mpc}^{-1}$, and $Ω_{\rm m}=0.303^{+0.016}_{-0.018}$. Combining with $\textit{Planck}$ CMB power spectrum data, we measure $σ_8$ to better than $1\,\%$ precision, finding $σ_8=0.811\pm 0.006$. We find consistency with the lensing results from the Dark Energy Survey, and give combined lensing-only parameter constraints that are tighter than joint results using galaxy clustering. Using $\textit{Planck}$ cosmic infrared background (CIB) maps we make a combined estimate of the lensing potential over $60\,\%$ of the sky with considerably more small-scale signal. We demonstrate delensing of the $\textit{Planck}$ power spectra, detecting a maximum removal of $40\,\%$ of the lensing-induced power in all spectra. The improvement in the sharpening of the acoustic peaks by including both CIB and the quadratic lensing reconstruction is detected at high significance (abridged).
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.001 |
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 teacher head, 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".