JOURNAL ARTICLE

Higher-dimensional compact objects with radiative viscous flow.

  • Published In: International Journal of Geometric Methods in Modern Physics, 2026, v. 23, n. 2. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Zahra, A.; Mardan, S. A.; Saleem, Sana; Malik, Adnan; Riaz, Muhammad Bilal 3 of 3

Abstract

In this paper, we develop a set of equations and associated matching conditions that are essential for the dissipation process in spherical symmetry. This process is characterized by both viscosity and free-streaming radiation, which are approximated using both free-streaming and diffusion methods. Our study focuses on a spherical distribution of matter that contains a fluid that dissipates. By using non-comoving coordinates with the post-quasi-static (PQS) approximation, we are able to analyze viscous fluid spheres as they depart from equilibrium in the streaming-out limit. In this work, we study a technique for obtaining a PQS approximation of the algorithm in non-comoving coordinates, which are used to discuss the phenomenon of gravitational collapse (GC). The PQS approximation is a step-by-step algorithm for evolving self-gravitating matter spheres. The system of surface equations is developed by matching the inner spacetime with the Vaidya outer spacetime. These surface equations play a crucial role in the study of various physical phenomena, including luminosity, redshift, and Doppler shift at gravitational source boundary surfaces (BS). [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Geometric Methods in Modern Physics. 2026/02, Vol. 23, Issue 2, p1
  • Document Type:Article
  • Subject Area:Physics
  • Publication Date:2026
  • ISSN:0219-8878
  • DOI:10.1142/S021988782530003X
  • Accession Number:190513285
  • 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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