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Record W2115280500 · doi:10.1093/mnras/stt1895

The clustering of galaxies in the SDSS-III DR10 Baryon Oscillation Spectroscopic Survey: no detectable colour dependence of distance scale or growth rate measurements

2013· article· en· W2115280500 on OpenAlexfundno aff
Ashley J. Ross, Lado Samushia, A. Burden, Will J. Percival, Rita Tojeiro, Marc Manera, Florian Beutler, J. Brinkmann, Joel R. Brownstein, L. A. N. da Costa, Daniel J. Eisenstein, Hong Guo, Shirley Ho, M. A. G. Maia, Francesco Montesano, Demitri Muna, Robert C. Nichol, Sebastián E. Nuza, Ariel G. Sánchez, Donald P. Schneider, Ramin Skibba, F. Sobreira, A. Streblyanska, Molly E. C. Swanson, D. Thomas, Jeremy L. Tinker, David A. Wake, Idit Zehavi, Gong‐Bo Zhao

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryBrookhaven National LaboratoryScience and Technology Facilities CouncilSmithsonian Astrophysical ObservatoryUniversity of California, Santa CruzUniversity of California, IrvineUniversity of PittsburghUniversity of CambridgeYork UniversityCarnegie Mellon UniversityHarvard UniversityTexas Christian UniversityUniversity of ArizonaOffice of ScienceSouth East Physics NetworkAlfred P. Sloan FoundationUniversity of WashingtonPrinceton UniversityJohns Hopkins UniversityCollege of Engineering, Michigan State UniversityOhio State UniversityNew Mexico State UniversityUniversity of PortsmouthYale UniversityVanderbilt UniversityU.S. Department of EnergyFermilabNational Science Foundation
KeywordsPhysicsAstrophysicsGalaxyBaryonOscillation (cell signaling)Cluster analysisScale (ratio)AstronomyStatisticsQuantum mechanics

Abstract

fetched live from OpenAlex

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.011
GPT teacher head0.205
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations63
Published2013
Admission routes1
Has abstractyes

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