Constraints on $Λ$CDM Extensions from the SPT-3G 2018 $EE$ and $TE$ Power Spectra
Bibliographic record
Abstract
We present constraints on extensions to the $Λ$CDM cosmological model from measurements of the $E$-mode polarization auto-power spectrum and the temperature-$E$-mode cross-power spectrum of the cosmic microwave background (CMB) made using 2018 SPT-3G data. The extensions considered vary the primordial helium abundance, the effective number of relativistic degrees of freedom, the sum of neutrino masses, the relativistic energy density and mass of a sterile neutrino, and the mean spatial curvature. We do not find clear evidence for any of these extensions, from either the SPT-3G 2018 dataset alone or in combination with baryon acoustic oscillation and \textit{Planck} data. None of these model extensions significantly relax the tension between Hubble-constant, $H_0$, constraints from the CMB and from distance-ladder measurements using Cepheids and supernovae. The addition of the SPT-3G 2018 data to \textit{Planck} reduces the square-root of the determinants of the parameter covariance matrices by factors of $1.3 - 2.0$ across these models, signaling a substantial reduction in the allowed parameter volume. We also explore CMB-based constraints on $H_0$ from combined SPT, \textit{Planck}, and ACT DR4 datasets. While individual experiments see some indications of different $H_0$ values between the $TT$, $TE$, and $EE$ spectra, the combined $H_0$ constraints are consistent between the three spectra. For the full combined datasets, we report $H_0 = 67.49 \pm 0.53\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$, which is the tightest constraint on $H_0$ from CMB power spectra to date and in $4.1\,σ$ tension with the most precise distance-ladder-based measurement of $H_0$. The SPT-3G survey is planned to continue through at least 2023, with existing maps of combined 2019 and 2020 data already having $\sim3.5\times$ lower noise than the maps used in this analysis.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".