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Efficient Computation of Cosmic Microwave Background Anisotropies in Closed Friedmann‐Robertson‐Walker Models
Open accessAbstract
We implement the efficient line-of-sight method to calculate the anisotropy and polarization of the cosmic microwave background for scalar and tensor modes in almost Friedmann-Robertson-Walker models with positive spatial curvature. We present new results for the polarization power spectra in such models.
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Metadata
- Authors
- Lewis, A., Challinor, A., & Lasenby, A.
- Affiliations
- University of Cambridge (GB)
- Venue
- The Astrophysical Journal
- Publisher
- American Astronomical Society
- Published
- 2000-08
- Volume
- 538
- Issue
- 2
- Pages
- 473-476
- ISSN
- 0004-637X (ISSN-L)
- 1538-4357
- OpenAlex
- W1944901286
- Cited by
- 4,920
- References
- 22
- Citations by year
- 2026: 226 · 2025: 298 · 2024: 272 · 2023: 263 · 2022: 265 · 2021: 291 · 2020: 327 · 2019: 278 · 2018: 281 · 2017: 259 · 2016: 325 · 2015: 252 · 2014: 270 · 2013: 250 · 2012: 234
- FWCI
- 17.05
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Astrophysical Journal (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Cosmology and Gravitation Theories
- Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Galaxies: Formation, Evolution, Phenomena
- Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › Dark Matter and Cosmic Phenomena
- Keywords
- cosmic microwave background anisotropies, CMB polarization, line-of-sight integration, positive spatial curvature, scalar perturbations, tensor perturbations, cosmological perturbation theory
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.
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