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Record W2067696419 · doi:10.1093/mnras/stt513

The clustering of galaxies at z ≈ 0.5 in the SDSS-III Data Release 9 BOSS-CMASS sample: a test for the ΛCDM cosmology

2013· article· en· W2067696419 on OpenAlexfundno aff
Sebastián E. Nuza, Ariel G. Sánchez, Francisco Prada, Anatoly Klypin, David J. Schlegel, Stefan Gottlöber, Antonio D. Montero-Dorta, Marc Manera, Cameron K. McBride, Ashley J. Ross, Raúl E. Angulo, Michael R. Blanton, A. Bolton, Ginevra Favole, Lado Samushia, Francesco Montesano, Will J. Percival, Nikhil Padmanabhan, Matthias Steinmetz, Jeremy L. Tinker, Ramin Skibba, Donald P. Schneider, Hong Guo, Idit Zehavi, Zheng Zheng, Dmitry Bizyaev, O. Malanushenko, Viktor Malanushenko, Audrey E. Oravetz, Daniel Oravetz, Alaina Shelden

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 LaboratoryScience and Technology Facilities CouncilCollege of Engineering, Michigan State UniversityMinisterio de Ciencia e InnovaciónDeutsche ForschungsgemeinschaftYork UniversityAmes Research CenterJohns Hopkins UniversityOhio State UniversityNew Mexico State UniversityUniversity of PortsmouthYale UniversityVanderbilt UniversityNational Science FoundationUniversity of WashingtonAlfred P. Sloan FoundationNational Aeronautics and Space AdministrationUniversity of ArizonaLeibniz-GemeinschaftPrinceton UniversityBrookhaven National LaboratoryU.S. Department of Energy
KeywordsPhysicsAstrophysicsGalaxyRedshiftBaryonHaloCosmologyCorrelation function (quantum field theory)SkyGalaxy formation and evolutionAstronomy

Abstract

fetched live from OpenAlex

We present results on the clustering of 282 068 galaxies in the Baryon Oscillation Spectroscopic Survey (BOSS) sample of massive galaxies with redshifts 0.4 < z < 0.7 which is part of the Sloan Digital Sky Survey III project. Our results cover a large range of scales from ∼500 to ∼90 h−1 Mpc. We compare these estimates with the expectations of the flat Λ cold dark matter (ΛCDM) standard cosmological model with parameters compatible with Wilkinson Microwave Anisotropy Probe 7 data. We use the MultiDark cosmological simulation, one of the largest N-body runs presently available, together with a simple halo abundance matching technique, to estimate galaxy correlation functions, power spectra, abundance of subhaloes and galaxy biases. We find that the ΛCDM model gives a reasonable description to the observed correlation functions at z ≈ 0.5, which is remarkably good agreement considering that the model, once matched to the observed abundance of BOSS galaxies, does not have any free parameters. However, we find a ≳10 per cent deviation in the correlation functions for scales ≲ 1 and ∼10–40 h−1 Mpc. A more realistic abundance matching model and better statistics from upcoming observations are needed to clarify the situation. We also estimate that about 12 per cent of the ‘galaxies’ in the abundance-matched sample are satellites inhabiting central haloes with mass M ≳ 1014 h−1 M⊙. Using the MultiDark simulation, we also study the real-space halo bias b of the matched catalogue finding that b = 2.00 ± 0.07 at large scales, consistent with the one obtained using the measured BOSS-projected correlation function. Furthermore, the linear large-scale bias, defined using the extrapolated linear matter power spectrum, depends on the number density n of the abundance-matched sample as b = −0.048 − (0.594 ± 0.02)log10(n/ h3 Mpc−3). Extrapolating these results to baryon acoustic oscillation scales, we measure a scale-dependent damping of the acoustic signal produced by non-linear evolution that leads to ∼2–4 per cent dips at ≳ 3σ level for wavenumbers k ≳ 0.1 h Mpc−1 in the linear large-scale bias.

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)0.002
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.224
Teacher spread0.210 · 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

Citations119
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueMonthly Notices of the Royal Astronomical SocietySame topicGalaxies: Formation, Evolution, PhenomenaFrench-language works237,207