JOURNAL ARTICLE
Energy density inhomogeneities with self-gravitating charged fluid in modified teleparallel gravity.
Published In: International Journal of Geometric Methods in Modern Physics, 2024, v. 21, n. 9. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Bhatti, M. Z.; Turki, Nasser Bin; Hanif, S.; Malik, A. 3 of 3
Abstract
In this paper, we analyze energy density inhomogeneities for charged fluid configuration in the background of f (T) theory and recognize its prime features as computed in GR. The dynamical equations are composed employing Bianchi identities for the standard, f (T) extra terms, and energy-momentum tensor for the electromagnetic field. We evaluate various mathematical models of dissipative and anisotropic fluid distributions in-plane symmetry under f (T) gravity. To proceed with the investigation, we design the f (T) field equations, kinematical quantities, and mass function. We analyzed dynamical variables and Ellis equations in terms of our considered theory. To examine the associated inhomogeneity factors, specific scenarios are illustrated alongside and without dissipation. Within a non-radiating situation, we analyze dust and isotropic and anisotropic matter in the state of electric charge. We examine the inhomogeneity factor of a dissipative fluid via a charged dust haze. We derive that the electromagnetic field fosters matter inhomogeneity, but additional curvature factors make the entire structure more homogenous as time passes. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Geometric Methods in Modern Physics. 2024/08, Vol. 21, Issue 9, p1
- Document Type:Article
- Subject Area:Physics
- Publication Date:2024
- ISSN:0219-8878
- DOI:10.1142/S0219887824501718
- Accession Number:178097695
- Copyright Statement:Copyright of International Journal of Geometric Methods in Modern Physics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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