The one-dimensional Ly<i>α</i>forest power spectrum from BOSS
Bibliographic record
Abstract
We have developed two independent methods for measuring the one-dimensional power spectrum of the transmitted flux in the Lyman-α forest. The first method is based on a Fourier transform and the second on a maximum-likelihood estimator. The two methods are independent and have different systematic uncertainties. Determination of the noise level in the data spectra was subject to a new treatment, because of its significant impact on the derived power spectrum. We applied the two methods to 13 821 quasar spectra from SDSS-III/BOSS DR9 selected from a larger sample of over 60 000 spectra on the basis of their high quality, high signal-to-noise ratio (S/N), and good spectral resolution. The power spectra measured using either approach are in good agreement over all twelve redshift bins from ⟨z⟩ = 2.2 to ⟨z⟩ = 4.4, and scales from 0.001 km s-1 to 0.02 km s-1. We determined the methodological andinstrumental systematic uncertainties of our measurements. We provide a preliminary cosmological interpretation of our measurements using available hydrodynamical simulations. The improvement in precision over previously published results from SDSS is a factor 2–3 for constraints on relevant cosmological parameters. For a ΛCDM model and using a constraint on H0 that encompasses measurements based on the local distance ladder and on CMB anisotropies, we infer σ8 = 0.83 ± 0.03 and ns = 0.97 ± 0.02 based on H i absorption in the range 2.1 < z < 3.7.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".