The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: baryon acoustic oscillations in the Fourier space
Bibliographic record
Abstract
We analyse the baryon acoustic oscillation (BAO) signal of the final Baryon Oscillation Spectroscopic Survey (BOSS) data release (DR12). Our analysis is performed in the Fourier space, using the power spectrum monopole and quadrupole. The data set includes 1198 006 galaxies over the redshift range 0.2 < z < 0.75. We divide this data set into three (overlapping) redshift bins with the effective redshifts zeff = 0.38, 0.51 and 0.61. We demonstrate the reliability of our analysis pipeline using N-body simulations as well as ∼1000 MultiDark-Patchy mock catalogues that mimic the BOSS-DR12 target selection. We apply density field reconstruction to enhance the BAO signal-to-noise ratio. By including the power spectrum quadrupole we can separate the line of sight and angular modes, which allows us to constrain the angular diameter distance DA(z) and the Hubble parameter H(z) separately. We obtain two independent 1.6 and 1.5 per cent constraints on DA(z) and 2.9 and 2.3 per cent constraints on H(z) for the low (zeff = 0.38) and high (zeff = 0.61) redshift bin, respectively. We obtain two independent 1 and 0.9 per cent constraints on the angular averaged distance DV(z), when ignoring the Alcock–Paczynski effect. The detection significance of the BAO signal is of the order of 8σ (post-reconstruction) for each of the three redshift bins. Our results are in good agreement with the Planck prediction within Λ cold dark matter. This paper is part of a set that analyses the final galaxy clustering data set from BOSS. The measurements and likelihoods presented here are combined with others in Alam et al. to produce the final cosmological constraints from BOSS.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".