BOSS DR12 full-shape cosmology: <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi mathvariant="normal">Λ</mml:mi><mml:mi>CDM</mml:mi></mml:mrow></mml:math> constraints from the large-scale galaxy power spectrum and bispectrum monopole
Bibliographic record
Abstract
We present a full $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ analysis of the BOSS DR12 dataset, including information from the power spectrum multipoles, the real-space power spectrum, the reconstructed power spectrum and the bispectrum monopole. This is the first analysis to feature a complete treatment of the galaxy bispectrum, including a consistent theoretical model and without large-scale cuts. Unlike previous works, the statistics are measured using window-free estimators: this greatly reduces computational costs by removing the need to window-convolve the theory model. Our pipeline is tested using a suite of high-resolution mocks and shown to be robust and precise, with systematic errors far below the statistical thresholds. Inclusion of the bispectrum yields consistent parameter constraints and shrinks the ${\ensuremath{\sigma}}_{8}$ posterior by 13% to reach $<5%$ precision; less conservative analysis choices would reduce the error bars further. Our constraints are broadly consistent with Planck: in particular, we find ${H}_{0}={69.6}_{\ensuremath{-}1.3}^{+1.1}\text{ }\text{ }\mathrm{km}{\mathrm{s}}^{\ensuremath{-}1}\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$, ${\ensuremath{\sigma}}_{8}=0.69{2}_{\ensuremath{-}0.041}^{+0.035}$ and ${n}_{s}=0.87{0}_{\ensuremath{-}0.064}^{+0.067}$, including a BBN prior on the baryon density. When ${n}_{s}$ is set by Planck, we find ${H}_{0}=68.3{1}_{\ensuremath{-}0.86}^{+0.83}\text{ }\text{ }\mathrm{km}{\mathrm{s}}^{\ensuremath{-}1}\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$ and ${\ensuremath{\sigma}}_{8}=0.72{2}_{\ensuremath{-}0.036}^{+0.032}$. Our ${S}_{8}$ posterior, $0.751\ifmmode\pm\else\textpm\fi{}0.039$, is consistent with weak lensing studies, but lower than Planck. Constraints on the higher-order bias parameters are significantly strengthened from the inclusion of the bispectrum, and we find no evidence for deviation from the dark matter halo bias relations. These results represent the most complete full-shape analysis of BOSS DR12 to-date, and the corresponding spectra will enable a variety of beyond-$\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ analyses, probing phenomena such as the neutrino mass and primordial non-Gaussianity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 0.053 |
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".