The power spectrum and bispectrum of SDSS DR11 BOSS galaxies – I. Bias and gravity
Bibliographic record
Abstract
We analyse the anisotropic clustering of the Baryon Oscillation Spectroscopic Survey CMASS Data Release 11 sample, which consists of 690 827 galaxies in the redshift range 0.43 < z < 0.70 and has a sky coverage of 8498 deg2 corresponding to an effective volume of ∼ 6 Gpc3. We fit the Fourier space statistics, the power spectrum and bispectrum monopoles to measure the linear and quadratic bias parameters, b1 and b2, for a non-linear non-local bias model, the growth of structure parameter f and the amplitude of dark matter density fluctuations parametrized by σ8. We obtain b1(zeff)1.40σ8(zeff) = 1.672 ± 0.060 and |$b_2^{0.30}(z_{\rm eff})\sigma _8(z_{\rm eff})=0.579\pm 0.082$| at the effective redshift of the survey, zeff = 0.57. The main cosmological result is the constraint on the combination f 0.43(zeff)σ8(zeff) = 0.582 ± 0.084, which is complementary to fσ8 constraints obtained from two-point redshift-space distortion analyses. A less conservative analysis yields f 0.43(zeff)σ8(zeff) = 0.584 ± 0.051. We ensure that our result is robust by performing detailed systematic tests using a large suite of survey galaxy mock catalogues and N-body simulations. The constraints on f 0.43σ8 are useful for setting additional constraints on neutrino mass, gravity, curvature as well as the number of neutrino species from galaxy surveys analyses (as presented in a companion paper).
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".