The SDSS-III Baryonic Oscillation Spectroscopic Survey: constraints on the integrated Sachs–Wolfe effect
Bibliographic record
Abstract
In the context of the study of the integrated Sachs–Wolfe (ISW) effect, we construct a template of the projected density distribution up to redshift z ≃ 0.7 by using the luminous galaxies (LGs) from the Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8). We use a photometric redshift catalogue trained with more than a hundred thousand galaxies from the Baryon Oscillation Spectroscopic Survey (BOSS) in the SDSS DR8 imaging area covering nearly one-quarter of the sky. We consider two different LG samples whose selection matches that of SDSS-III/BOSS: the low-redshift sample (LOWZ, z ∈ [0.15, 0.5]) and the constant mass sample (CMASS, z ∈ [0.4, 0.7]). When building the galaxy angular density templates we use the information from star density, survey footprint, seeing conditions, sky emission, dust extinction and airmass to explore the impact of these artefacts on each of the two LG samples. In agreement with previous studies, we find that the CMASS sample is particularly sensitive to Galactic stars, which dominate the contribution to the auto-angular power spectrum below ℓ = 7. Other potential systematics affect mostly the very low multipole range (ℓ ∈ [2, 7]), but leave fluctuations on smaller scales practically unchanged. The resulting angular power spectra in the multipole range ℓ ∈ [2, 100] for the LOWZ, CMASS and LOWZ+CMASS samples are compatible with linear Λ cold dark matter (ΛCDM) expectations and constant bias values of b = 1.98 ± 0.11, 2.08 ± 0.14 and 1.88 ± 0.11, respectively, with no traces of non-Gaussianity signatures, i.e. |$f_{\rm NL}^{\rm local}=59\pm 75$| at 95 per cent confidence level for the full LOWZ+CMASS sample in the multipole range ℓ ∈ [4, 100]. After cross-correlating Wilkinson Microwave Anisotropy Probe 9-year data with the LOWZ+CMASS LG projected density field, the ISW signal is detected at the level of 1.62–1.69σ. While this result is in close agreement with theoretical expectations and predictions from realistic Monte Carlo simulations in the concordance ΛCDM model, it cannot rule out by itself an Einstein–de Sitter scenario, and has a moderately low signal compared to previous studies conducted on subsets of this LG sample. We discuss possible reasons for this apparent discrepancy, and point to uncertainties in the galaxy survey systematics as most likely sources of confusion.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".