Cosmological constraints from the power spectrum of eBOSS quasars
Bibliographic record
Abstract
We present the effective-field theory (EFT-)based cosmological full-shape analysis of the anisotropic power spectrum of eBOSS quasars at the effective redshift ${z}_{\mathrm{eff}}=1.48$. We perform extensive tests of our pipeline on simulations, paying particular attention to the modeling of observational systematics, such as redshift smearing, fiber collisions, and the radial integral constraint. Assuming the minimal $\mathrm{\ensuremath{\Lambda}}$ cold dark matter model, and fixing the primordial power spectrum tilt and the physical baryon density, we find the Hubble constant ${H}_{0}=(66.7\ifmmode\pm\else\textpm\fi{}3.2)\text{ }\text{ }\mathrm{km}\text{ }{\mathrm{s}}^{\ensuremath{-}1}\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$, the matter density fraction ${\mathrm{\ensuremath{\Omega}}}_{m}=0.32\ifmmode\pm\else\textpm\fi{}0.03$, and the late-time mass fluctuation amplitude ${\ensuremath{\sigma}}_{8}=0.95\ifmmode\pm\else\textpm\fi{}0.08$. These measurements are fully consistent with the Planck cosmic microwave background results. Our eBOSS quasar ${S}_{8}$ posterior, $0.98\ifmmode\pm\else\textpm\fi{}0.11$, does not exhibit the so-called ${S}_{8}$ tension. Our work paves the way for systematic full-shape analyses of quasar samples from future surveys like DESI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".