The Completed SDSS-IV Extended Baryon Oscillation Spectroscopic Survey: Baryon Acoustic Oscillations with Lyα Forests
Bibliographic record
Abstract
Abstract We present a measurement of baryonic acoustic oscillations (BAOs) from Lyα absorption and quasars at an effective redshift using the complete extended Baryonic Oscillation Spectroscopic Survey (eBOSS). The 16th and final eBOSS data release (SDSS DR16) contains all data from eBOSS and its predecessor, the Baryonic Oscillation Spectroscopic Survey (BOSS), providing 210,005 quasars with z q > 2.10 that are used to measure Lyα absorption. We measure the BAO scale both in the autocorrelation of Lyα absorption and in its cross-correlation with 341,468 quasars with redshift z q > 1.77. Apart from the statistical gain from new quasars and deeper observations, the main improvements over previous work come from more accurate modeling of physical and instrumental correlations and the use of new sets of mock data. Combining the BAO measurement from the auto- and cross-correlation yields the constraints of the two ratios and , where the error bars are statistical. These results are within 1.5σ of the prediction of the flat-ΛCDM cosmology of Planck (2016). The analysis code, picca, the catalog of the flux transmission field measurements, and the Δχ 2 surfaces are publicly available.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".