NEW NEUTRINO MASS BOUNDS FROM SDSS-III DATA RELEASE 8 PHOTOMETRIC LUMINOUS GALAXIES
Bibliographic record
Abstract
We present neutrino mass bounds using 900,000 luminous galaxies with photometric redshifts measured from Sloan Digital Sky Survey III Data Release 8. The galaxies have photometric redshifts between z = 0.45 and z = 0.65 and cover 10,000 deg(2), thus probing a volume of 3 h(-3) Gpc(3) and enabling tight constraints to be derived on the amount of dark matter in the form of massive neutrinos. A new bound on the sum of neutrino masses Sigma m nu < 0.27 eV, at the 95% confidence level (CL), is obtained after combining our sample of galaxies, which we call CMASS with Wilkinson Microwave Anisotropy Probe (WMAP) seven-year cosmic microwave background data and the most recent measurement of the Hubble parameter from the Hubble Space Telescope (HST). This constraint is obtained with a conservative multipole range of 30 < l < 200 in order to minimize nonlinearities, and a free bias parameter in each of the four redshift bins. We study the impact of assuming this linear galaxy bias model using mock catalogs and find that this model causes a small (similar to 1 sigma-1.5 sigma) bias in Omega(DM)h(2). For this reason, we also quote neutrino bounds based on a conservative galaxy bias model containing additional, shot-noise-like free parameters. In this conservative case, the bounds are significantly weakened, e. g., Sigma m(nu) < 0.38 eV (95% CL) for WMAP+HST+CMASS (l(max) = 200). We also study the dependence of the neutrino bound on the multipole range (l(max) = 150 versus l(max) = 200) and on which combination of data sets is included as a prior. The addition of supernova and/or baryon acoustic oscillation data does not significantly improve the neutrino mass bound once the HST prior is included. A companion paper describes the construction of the angular power spectra in detail and derives constraints on a general cosmological model, including the dark energy equation of state w and the spatial curvature Omega(K), while a second companion paper presents a measurement of the scale of baryon acoustic oscillations from the same data set. All three works are based on the catalog by Ross et al.
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 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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".