Classification of cylindrically symmetric static Lorentzian manifolds according to their Petrov types and metrics

Muhammad Ziad*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The cylindrically symmetric static manifolds are classified for their Petrov types and metrics. This classification besides verifying the earlier result that such manifolds cannot be of petrov type II, III and N, gives a complete list of all static cylindrically symmetric metrics of Petrov type O. In the case of Petrov type D metrics, the results appear as three independent classes metrics.

Original languageEnglish
Title of host publication14th Marcel Grossman Meeting On Recent Developments in Theoretical and Experimental General Relativity, Astrophysics and Relativistic Field Theories, Proceedings
EditorsMassimo Bianchi, Robert T Jantzen, Remo Ruffini, Remo Ruffini
PublisherWorld Scientific Publishing Co. Pte Ltd
Pages2582-2587
Number of pages6
ISBN (Electronic)9789813226593
DOIs
Publication statusPublished - 2018
Event14th Marcel Grossman Meeting On Recent Developments in Theoretical and Experimental General Relativity, Astrophysics and Relativistic Field Theories - Rome, Italy
Duration: Jul 12 2015Jul 18 2015

Publication series

Name14th Marcel Grossman Meeting On Recent Developments in Theoretical and Experimental General Relativity, Astrophysics and Relativistic Field Theories, Proceedings

Other

Other14th Marcel Grossman Meeting On Recent Developments in Theoretical and Experimental General Relativity, Astrophysics and Relativistic Field Theories
Country/TerritoryItaly
CityRome
Period7/12/157/18/15

Keywords

  • Metrics
  • Petrov classification
  • Static cylindrical symmetry

ASJC Scopus subject areas

  • Nuclear and High Energy Physics
  • Astronomy and Astrophysics

Fingerprint

Dive into the research topics of 'Classification of cylindrically symmetric static Lorentzian manifolds according to their Petrov types and metrics'. Together they form a unique fingerprint.

Cite this