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Record W3100951766 · doi:10.1051/0004-6361/201629504

<i>Planck </i>intermediate results

2017· article· en· W3100951766 on OpenAlexafffund
N. Aghanim, Y. Akrami, M. Ashdown, J. Aumont, C. Baccigalupi, M. Ballardini, A. J. Banday, R. B. Barreiro, N. Bartolo, S. Basak, K. Benabed, M. Bersanelli, P. Bielewicz, A. Bonaldi, L. Bonavera, J. R. Bond, J. Borrill, F. R. Bouchet, C. Burigana, E. Calabrese, J.-F. Cardoso, A. Challinor, H. C. Chiang, L. P. L. Colombo, C. Combet, B. P. Crill, A. Curto, F. Cuttaia, P. de Bernardis, A. de Rosa, G. de Zotti, J. Delabrouille, Eleonora Di Valentino, C. Dickinson, J. M. Diego, O. Doré, A. Ducout, X. Dupac, S. Dusini, G. Efstathiou, F. Elsner, T. A. Enßlin, H. K. Eriksen, Y. Fantaye, F. Finelli⋆, F. Forastieri, M. Frailis, E. Franceschi, A. Frolov, S. Galeotta, S. Galli, K. Ganga, R. T. Génova-Santos, M. Gerbino, J. González-Nuevo, K. M. Górski, S. Gratton, A. Gruppuso, J. E. Gudmundsson, D. Herranz, E. Hivon, Zhiqi Huang, A. H. Jaffe, W. C. Jones, E. Keihänen, R. Keskitalo, K. Kiiveri, J. Kim, T. S. Kisner, L. Knox, N. Krachmalnicoff, M. Kunz, H. Kurki‐Suonio, G. Lagache, J.-M. Lamarre, A. Lasenby, M. Lattanzi, C. R. Lawrence, M. Le Jeune, F. Levrier, Antony Lewis, M. Liguori, P. B. Lilje, M. Lilley, V. Lindholm, M. López-Caniego, P. M. Lubin, Yin-Zhe Ma, J. F. Macías–Pérez, F. Mannucci, D Maino, N. Mandolesi, A. Mangilli, M. Maris, P. G. Martin, E. Martínez-González, S. Matarrese, N. Mauri, J. D. McEwen, P. R. Meinhold, A. Mennella, M. Migliaccio, M. Millea, M.-A. Miville-Deschênes, D. Molinari, A. Moneti, L. Montier, G. Morgante, A. Moss, A. Narimani, P. Natoli, C. A. Oxborrow, L. Pagano, D. Paoletti, B. Partridge, G. Patanchon, L. Patrizii, V. Pettorino, F. Piacentini, L. Polastri, G. Polenta, J.-L. Puget, J. P. Rachen, B. Racine, M. Reinecke, M. Remazeilles, A. Renzi, G. Rocha, M. Rossetti, G. Roudier, J. A. Rubiño-Martín, B. Ruiz-Granados, L. Salvati, M. Sandri, M. Savelainen, D. Scott, C. Sirignano, G. Sirri, L. Stančo, A.-S. Suur-Uski, J. A. Tauber, D. Tavagnacco, M. Tenti, L. Toffolatti, M. Tomasi, M. Tristram, T. Trombetti, J. Väliviita, F. Van Tent, P. Vielva, F. Villa, N. Vittorio, B. D. Wandelt, I. K. Wehus, Martin White, A. Zacchei, A. Zonca

Bibliographic record

VenueAstronomy and Astrophysics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityUniversity of Toronto
FundersFundação para a Ciência e a TecnologiaInstitut National de Physique Nucléaire et de Physique des ParticulesMinistério da Ciência, Tecnologia e Ensino SuperiorCentre National de la Recherche ScientifiqueSecretário de Ciência, Tecnologia e Ensino Superior, Governo do Estado de ParanaScience and Technology Facilities CouncilTekesCentre National d’Etudes SpatialesScience Foundation IrelandWestern Canada Research GridAgence Nationale de la RechercheChina Scholarship CouncilNational Aeronautics and Space AdministrationCompute CanadaEuropean Space AgencyPartnership for Advanced Computing in Europe AISBLMax-Planck-GesellschaftUK Space Agency
KeywordsPhysicsAstrophysicsPlanckAstronomy

Abstract

fetched live from OpenAlex

The six parameters of the standard ΛCDM model have best-fit values derived from the Planck temperature power spectrum that are shifted somewhat from the best-fit values derived from WMAP data. These shifts are driven by features in the Planck temperature power spectrum at angular scales that had never before been measured to cosmic-variance level precision. We have investigated these shifts to determine whether they are within the range of expectation and to understand their origin in the data. Taking our parameter set to be the optical depth of the reionized intergalactic medium τ , the baryon density ω b , the matter density ω m , the angular size of the sound horizon θ ∗ , the spectral index of the primordial power spectrum, n s , and A s e − 2 τ (where A s is the amplitude of the primordial power spectrum), we have examined the change in best-fit values between a WMAP-like large angular-scale data set (with multipole moment ℓ &lt; 800 in the Planck temperature power spectrum) and an all angular-scale data set ( ℓ &lt; 2500 Planck temperature power spectrum), each with a prior on τ of 0.07 ± 0.02. We find that the shifts, in units of the 1 σ expected dispersion for each parameter, are { Δ τ, Δ A s e − 2 τ ,Δ n s ,Δ ω m ,Δ ω b ,Δ θ ∗ } = { −1.7,−2.2,1.2,−2.0,1.1,0.9 }, with a χ 2 value of 8.0. We find that this χ 2 value is exceeded in 15% of our simulated data sets, and that a parameter deviates by more than 2.2 σ in 9% of simulated data sets, meaning that the shifts are not unusually large. Comparing ℓ &lt; 800 instead to ℓ &gt; 800, or splitting at a different multipole, yields similar results. We examined the ℓ &lt; 800 model residuals in the ℓ &gt; 800 power spectrum data and find that the features there that drive these shifts are a set of oscillations across a broad range of angular scales. Although they partly appear similar to the effects of enhanced gravitational lensing, the shifts in ΛCDM parameters that arise in response to these features correspond to model spectrum changes that are predominantly due to non-lensing effects; the only exception is τ , which, at fixed A s e − 2 τ , affects the ℓ &gt; 800 temperature power spectrum solely through the associated change in A s and the impact of that on the lensing potential power spectrum. We also ask, “what is it about the power spectrum at ℓ &lt; 800 that leads to somewhat different best-fit parameters than come from the full ℓ range?” We find that if we discard the data at ℓ &lt; 30, where there is a roughly 2 σ downward fluctuation in power relative to the model that best fits the full ℓ range, the ℓ &lt; 800 best-fit parameters shift significantly towards the ℓ &lt; 2500 best-fit parameters. In contrast, including ℓ &lt; 30, this previously noted “low- ℓ deficit” drives n s up and impacts parameters correlated with n s , such as ω m and H 0 . As expected, the ℓ &lt; 30 data have a much greater impact on the ℓ &lt; 800 best fit than on the ℓ &lt; 2500 best fit. So although the shifts are not very significant, we find that they can be understood through the combined effects of an oscillatory-like set of high- ℓ residuals and the deficit in low- ℓ power, excursions consistent with sample variance that happen to map onto changes in cosmological parameters. Finally, we examine agreement between Planck TT data and two other CMB data sets, namely the Planck lensing reconstruction and the TT power spectrum measured by the South Pole Telescope, again finding a lack of convincing evidence of any significant deviations in parameters, suggesting that current CMB data sets give an internally consistent picture of the ΛCDM model.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.627
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.237
Teacher spread0.229 · 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 teacher head, 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".

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Citations178
Published2017
Admission routes2
Has abstractyes

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