The clustering of galaxies in the SDSS-III DR10 Baryon Oscillation Spectroscopic Survey: no detectable colour dependence of distance scale or growth rate measurements
Bibliographic record
Abstract
We study the clustering of galaxies, as a function of their colour, from Data Release Ten (DR10) of the Sloan Digital Sky Survey III (SDSS-III) Baryon Oscillation Spectroscopic Survey. DR10 contains 540 505 galaxies with 0.43 < z < 0.7; from these we select 122 967 for a ‘Blue’ sample and 131 969 for a ‘Red’ sample based on k + e corrected (to z = 0.55) r − i colours and i-band magnitudes. The samples are chosen such that both contain more than 100 000 galaxies, have similar redshift distributions and maximize the difference in clustering amplitude. The Red sample has a 40 per cent larger bias than the Blue (bRed/bBlue = 1.39 ± 0.04), implying that the Red galaxies occupy dark matter haloes with an average mass that is 0.5 log10 M⊙ greater. Spherically averaged measurements of the correlation function, ξ0, and the power spectrum are used to locate the position of the baryon acoustic oscillation (BAO) feature of both samples. Using ξ0, we obtain distance scales, relative to the distance of our reference Λ cold dark matter cosmology, of 1.010 ± 0.027 for the Red sample and 1.005 ± 0.031 for the Blue. After applying reconstruction, these measurements improve to 1.013 ± 0.020 for the Red sample and 1.008 ± 0.026 for the Blue. For each sample, measurements of ξ0 and the second multipole moment, ξ2, of the anisotropic correlation function are used to determine the rate of structure growth, parametrized by fσ8. We find fσ8, Red = 0.511 ± 0.083, fσ8, Blue = 0.509 ± 0.085 and fσ8, Cross = 0.423 ± 0.061 (from the cross-correlation between the Red and Blue samples). We use the covariance between the bias and growth measurements obtained from each sample and their cross-correlation to produce an optimally combined measurement of fσ8, comb = 0.443 ± 0.055. This result compares favourably to that of the full 0.43 < z < 0.7 sample (fσ8, full = 0.422 ± 0.051) despite the fact that, in total, we use less than half of the number of galaxies analysed in the full sample measurement. In no instance do we detect significant differences in distance scale or structure growth measurements obtained from the Blue and Red samples. Our results are consistent with theoretical predictions and our tests on mock samples, which predict that any colour-dependent systematic uncertainty on the measured BAO position is less than 0.5 per cent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 |
| 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 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".