The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
The best inflationary models after Planck
Open accessAbstract
We compute the Bayesian evidence and complexity of 193 slow-roll single-field models of inflation using the Planck 2013 Cosmic Microwave Background data, with the aim of establishing which models are favoured from a Bayesian perspective. Our calculations employ a new numerical pipeline interfacing an inflationary effective likelihood with the slow-roll library ASPIC and the nested sampling algorithm MultiNest . The models considered represent a complete and systematic scan of the entire landscape of inflationary scenarios proposed so far. Our analysis singles out the most probable models (from an Occam's razor point of view) that are compatible with Planck data, while ruling out with very strong evidence 34% of the models considered. We identify 26% of the models that are favoured by the Bayesian evidence, corresponding to 15 different potential shapes. If the Bayesian complexity is included in the analysis, only 9% of the models are preferred, corresponding to only 9 different potential shapes. These shapes are all of the plateau type.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A new type of isotropic cosmological models without singularity
Starobinsky, A. A. (1980) · Physics Letters B · doi:10.1016/0370-2693(80)90670-x · Cited by 7,677
Lewis, A., Challinor, A., & Lasenby, A. (2000) · The Astrophysical Journal · doi:10.1086/309179 · Cited by 4,920
Cosmological parameters from CMB and other data: A Monte Carlo approach
Lewis, A., & Bridle, S. (2002) · Physical Review D · doi:10.1103/physrevd.66.103511 · Cited by 3,495 · cited 3×
“The MCMC exploration has been stopped once the total number of samples reached two millions, which corresponds to the R-statistics convergence of COSMOMC (the Gelman-Rubin criterion) to be less than 10−3 (see ref.”
BackgroundMethodBernardo, J. M., & Smith, A. F. M. (1994) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316870 · Cited by 2,178
Revised standards for statistical evidence
Johnson, V. E. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1313476110 · Cited by 808
Testing a Point Null Hypothesis: The Irreconcilability of P Values and Evidence
Berger, J. O., & Sellke, T. (1987) · Journal of the American Statistical Association · doi:10.2307/2289131 · Cited by 548
The interplay of Bayesian and frequentist analysis
Bayarri, M. J., & Berger, J. O. (2004) · Statistical Science · doi:10.1214/088342304000000116 · Cited by 525
Cited by
Planck 2018 results: X. Constraints on inflation
Planck Collaboration, Akrami, Y., Arroja, F., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A. J., Barreiro, R. B., Bartolo, N., et al. (2020) · Astronomy & Astrophysics · doi:10.1051/0004-6361/201833887 · Cited by 2,442
Abdalla, E., Abellán, G. F., Aboubrahim, A., Agnello, A., Akarsu, Ö., Akrami, Y., Alestas, G., Aloni, D., Amendola, L., Anchordoqui, L. A., et al. (2022) · Journal of High Energy Astrophysics · doi:10.1016/j.jheap.2022.04.002 · Cited by 37
Metadata
- Authors
- Martin, J., Ringeval, C., Trotta, R., & Vennin, V.
- Venue
- Journal of Cosmology and Astroparticle Physics
- Publisher
- IOP Publishing
- Published
- 2014-03-19
- Volume
- 2014
- Issue
- 03
- Pages
- 039-039
- ISSN
- 1475-7508 (ISSN-L)
- 1475-7516
- OpenAlex
- W2039344615
- Cited by
- 301
- References
- 7
- FWCI
- 18.01
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
