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Record W1819346083 · doi:10.1103/physrevd.92.123516

Cosmological implications of baryon acoustic oscillation measurements

2015· article· en· W1819346083 on OpenAlexfundno aff
É. Aubourg, S. Bailey, Julian Bautista, Florian Beutler, Vaishali Bhardwaj, Dmitry Bizyaev, Michael R. Blanton, Michael Blomqvist, A. Bolton, Jo Bovy, H. Brewington, J. Brinkmann, Joel R. Brownstein, A. Burden, Nicolás G. Busca, W. Carithers, Chia-Hsun Chuang, Johan Comparat, Rupert A. C. Croft, Antonio J. Cuesta, Kyle Dawson, Timothée Delubac, Daniel J. Eisenstein, Andreu Font-Ribera, Jian Ge, J.M. Le Goff, Satya Gontcho A Gontcho, J. Richard Gott, James E. Gunn, Hong Guo, Julien Guy, J.–Ch. Hamilton, Shirley Ho, Klaus Honscheid, Cullan Howlett, D. Kirkby, Francisco-Shu Kitaura, Jean‐Paul Kneib, Khee‐Gan Lee, Dan Long, Robert H. Lupton, M. Vargas-Magaña, Viktor Malanushenko, Elena Malanushenko, Marc Manera, Claudia Maraston, Daniel Margala, Cameron K. McBride, Jordi Miralda‐Escudé, Adam D. Myers, Robert C. Nichol, P. Noterdaeme, Sebastián E. Nuza, Matthew D. Olmstead, Daniel Oravetz, Isabelle Pâris, Nikhil Padmanabhan, N. Palanque‐Delabrouille, Kaike Pan, Marcos Pellejero-Ibáñez, Will J. Percival, Patrick Petitjean, Matthew M. Pieri, Francisco Prada, Beth Reid, Natalie A. Roe, Ashley J. Ross, Nicholas P. Ross, Graziano Rossi, J. A. Rubiño-Martín, Ariel G. Sánchez, Lado Samushia, R. Génova-Santos, Claudia G. Scóccola, David J. Schlegel, Donald P. Schneider, Hee‐Jong Seo, Erin Sheldon, Audrey Simmons, Ramin Skibba, Anže Slosar, Michael A. Strauss, D. Thomas, Jeremy L. Tinker, Rita Tojeiro, J. Alberto Vázquez, Matteo Viel, David A. Wake, Benjamin A. Weaver, David H. Weinberg, W. M. Wood‐Vasey, Christophe Yèche, Idit Zehavi, Gong‐Bo Zhao

Bibliographic record

VenuePhysical review. D. Particles, fields, gravitation, and cosmology/Physical review. D, Particles, fields, gravitation, and cosmology · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryYork UniversityOffice of ScienceJohns Hopkins UniversityScience and Technology Facilities CouncilCarnegie Mellon UniversityCollege of Engineering, Michigan State UniversityHarvard UniversityOhio State UniversityNational Science FoundationUniversity of WashingtonAlfred P. Sloan FoundationNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityYale UniversityPrinceton UniversityBrookhaven National LaboratoryU.S. Department of Energy
KeywordsBaryonOscillation (cell signaling)Baryon acoustic oscillationsPhysicsAstrophysicsAstronomyCosmologyDark energyBiology

Abstract

fetched live from OpenAlex

We derive constraints on cosmological parameters and tests of dark energy models from the combination of baryon acoustic oscillation (BAO) measurements with cosmic microwave background (CMB) data and a recent reanalysis of Type Ia supernova (SN) data. In particular, we take advantage of high-precision BAO measurements from galaxy clustering and the Lyman-$\ensuremath{\alpha}$ forest (LyaF) in the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). Treating the BAO scale as an uncalibrated standard ruler, BAO data alone yield a high confidence detection of dark energy; in combination with the CMB angular acoustic scale they further imply a nearly flat universe. Adding the CMB-calibrated physical scale of the sound horizon, the combination of BAO and SN data into an ``inverse distance ladder'' yields a measurement of ${H}_{0}=67.3\ifmmode\pm\else\textpm\fi{}1.1\text{ }\text{ }\mathrm{km}\text{ }{\mathrm{s}}^{\ensuremath{-}1}\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$, with 1.7% precision. This measurement assumes standard prerecombination physics but is insensitive to assumptions about dark energy or space curvature, so agreement with CMB-based estimates that assume a flat $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ cosmology is an important corroboration of this minimal cosmological model. For constant dark energy ($\mathrm{\ensuremath{\Lambda}}$), our $\mathrm{BAO}+\mathrm{SN}+\mathrm{CMB}$ combination yields matter density ${\mathrm{\ensuremath{\Omega}}}_{m}=0.301\ifmmode\pm\else\textpm\fi{}0.008$ and curvature ${\mathrm{\ensuremath{\Omega}}}_{k}=\ensuremath{-}0.003\ifmmode\pm\else\textpm\fi{}0.003$. When we allow more general forms of evolving dark energy, the $\mathrm{BAO}+\mathrm{SN}+\mathrm{CMB}$ parameter constraints are always consistent with flat $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ values at $\ensuremath{\approx}1\ensuremath{\sigma}$. While the overall ${\ensuremath{\chi}}^{2}$ of model fits is satisfactory, the LyaF BAO measurements are in moderate ($2--2.5\ensuremath{\sigma}$) tension with model predictions. Models with early dark energy that tracks the dominant energy component at high redshift remain consistent with our expansion history constraints, and they yield a higher ${H}_{0}$ and lower matter clustering amplitude, improving agreement with some low redshift observations. Expansion history alone yields an upper limit on the summed mass of neutrino species, $\ensuremath{\sum}{m}_{\ensuremath{\nu}}<0.56\text{ }\text{ }\mathrm{eV}$ (95% confidence), improving to $\ensuremath{\sum}{m}_{\ensuremath{\nu}}<0.25\text{ }\text{ }\mathrm{eV}$ if we include the lensing signal in the Planck CMB power spectrum. In a flat $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ model that allows extra relativistic species, our data combination yields ${N}_{\mathrm{eff}}=3.43\ifmmode\pm\else\textpm\fi{}0.26$; while the LyaF BAO data prefer higher ${N}_{\mathrm{eff}}$ when excluding galaxy BAO, the galaxy BAO alone favor ${N}_{\mathrm{eff}}\ensuremath{\approx}3$. When structure growth is extrapolated forward from the CMB to low redshift, standard dark energy models constrained by our data predict a level of matter clustering that is high compared to most, but not all, observational estimates.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.039
GPT teacher head0.344
Teacher spread0.305 · 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 designTheoretical or conceptual
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

Citations742
Published2015
Admission routes1
Has abstractyes

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