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An Introduction to General Relativity and Cosmology
Abstract
General relativity is a cornerstone of modern physics, and is of major importance in its applications to cosmology. Plebanski and Krasinski are experts in the field and in this 2006 book they provide a thorough introduction to general relativity, guiding the reader through complete derivations of the most important results. Providing coverage from a unique viewpoint, geometrical, physical and astrophysical properties of inhomogeneous cosmological models are all systematically and clearly presented, allowing the reader to follow and verify all derivations. For advanced undergraduates and graduates in physics and astronomy, this textbook will enable students to develop expertise in the mathematical techniques necessary to study general relativity.
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Citations
Cited by
Two-component spinor techniques and Feynman rules for quantum field theory and supersymmetry
Dreiner, H. K., Haber, H. E., & Martin, S. P. (2010) · Physics Reports · doi:10.1016/j.physrep.2010.05.002 · Cited by 531
On the Weyl curvature hypothesis
Stoica, O. C. (2013) · Annals of Physics · doi:10.1016/j.aop.2013.08.002 · Cited by 22
Spherical domain wall collapse in a dust universe
Tanahashi, N., & Yoo, C.-M. (2015) · Classical and Quantum Gravity · doi:10.1088/0264-9381/32/15/155003 · Cited by 18
Metadata
- Authors
- Plebanski, J., & Krasinski, A.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2006-08-14
- OpenAlex
- W1571309011
- Cited by
- 400
- References
- 0
- FWCI
- 10.77
- Type
- book
- Language
- en
- Open access
- closed
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- Plebanski, J., & Krasinski, A. (2006). An Introduction to General Relativity and Cosmology. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511617676
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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.
