Measurements of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>E</mml:mi></mml:math>-mode polarization and temperature-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>E</mml:mi></mml:math>-mode correlation of the CMB from SPT-3G 2018 data
Bibliographic record
Abstract
We present measurements of the $E$-mode ($EE$) polarization power spectrum and temperature-$E$-mode ($TE$) cross-power spectrum of the cosmic microwave background using data collected by SPT-3G, the latest instrument installed on the South Pole Telescope. This analysis uses observations of a $1500\text{ }\text{ }{\mathrm{deg}}^{2}$ region at 95, 150, and 220 GHz taken over a four-month period in 2018. We report binned values of the $EE$ and $TE$ power spectra over the angular multipole range $300\ensuremath{\le}\ensuremath{\ell}<3000$, using the multifrequency data to construct six semi-independent estimates of each power spectrum and their minimum-variance combination. These measurements improve upon the previous results of SPTpol across the multipole ranges $300\ensuremath{\le}\ensuremath{\ell}\ensuremath{\le}1400$ for $EE$ and $300\ensuremath{\le}\ensuremath{\ell}\ensuremath{\le}1700$ for $TE$, resulting in constraints on cosmological parameters comparable to those from other current leading ground-based experiments. We find that the SPT-3G data set is well fit by a $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ cosmological model with parameter constraints consistent with those from Planck and SPTpol data. From SPT-3G data alone, we find ${H}_{0}=68.8\ifmmode\pm\else\textpm\fi{}1.5\text{ }\text{ }\mathrm{km}\text{ }{\mathrm{s}}^{\ensuremath{-}1}\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$ and ${\ensuremath{\sigma}}_{8}=0.789\ifmmode\pm\else\textpm\fi{}0.016$, with a gravitational lensing amplitude consistent with the $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ prediction (${A}_{L}=0.98\ifmmode\pm\else\textpm\fi{}0.12$). We combine the SPT-3G and the Planck data sets and obtain joint constraints on the $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ model. The volume of the 68% confidence region in six-dimensional $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ parameter space is reduced by a factor of 1.5 compared to Planck-only constraints, with no significant shifts in central values. We note that the results presented here are obtained from data collected during just half of a typical observing season with only part of the focal plane operable, and that the active detector count has since nearly doubled for observations made with SPT-3G after 2018.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".