Baryon acoustic oscillations in the Ly
Bibliographic record
Abstract
We report a detection of the baryon acousticoscillation (BAO) feature in the flux-correlation function of the Lyα forest of high-redshift quasars with a statistical significance of five standard deviations. The study uses 137 562 quasars in the redshift range 2.1 ≤ z ≤ 3.5 from the data release 11 (DR11) of the Baryon Oscillation Spectroscopic Survey (BOSS) of SDSS-III. This sample contains three times the number of quasars used in previous studies. The measured position of the BAO peak determines the angular distance, DA(z = 2.34) and expansion rate, H(z = 2.34), both on a scale set by the sound horizon at the drag epoch, rd. We find DA/rd = 11.28 ± 0.65(1σ)+2.8-1.2 (2σ) and DH/rd = 9.18 ± 0.28(1σ) ± 0.6(2σ) where DH = c/H. The optimal combination, ~DH0.7DA0.3/rd is determined with a precision of ~2%. For the value rd = 147.4 Mpc, consistent with the cosmic microwave background power spectrum measured by Planck, we find DA(z = 2.34) = 1662 ± 96(1σ) Mpc and H(z = 2.34) = 222 ± 7(1σ) km s-1 Mpc-1. Tests with mock catalogs and variations of our analysis procedure have revealed no systematic uncertainties comparable to our statistical errors. Our results agree with the previously reported BAO measurement at the same redshift using the quasar-Lyα forest cross-correlation. The autocorrelation and cross-correlation approaches are complementary because of the quite different impact of redshift-space distortion on the two measurements. The combined constraints from the two correlation functions imply values of DA/rd that are 7% lower and 7% higher for DH/rd than the predictions of a flat ΛCDM cosmological model with the best-fit Planck parameters. With our estimated statistical errors, the significance of this discrepancy is ≈2.5σ.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".