GUP corrected black holes with cloud of string
Ahmad Al-Badawi, Sanjar Shaymatov, Sohan Kumar Jha, Anisur Rahaman

TL;DR
This paper studies the effects of quantum corrections via GUP on black holes with a string cloud, analyzing shadows, light deflection, quasinormal modes, and Hawking radiation to understand their astrophysical implications.
Contribution
It introduces a comprehensive analysis of GUP corrections on Schwarzschild string cloud black holes across multiple phenomena, including shadows, deflection, QNMs, and radiation, using various GUP frameworks.
Findings
String cloud increases greybody factor; linear GUP decreases it.
GUP parameters significantly affect quasinormal modes.
Linear GUP and string parameters have contrasting effects on observables.
Abstract
We investigate shadows, deflection angle, quasinormal modes (QNMs), and sparsity of Hawking radiation of the Schwarzschild string cloud black hole's solution after applying quantum corrections required by the Generalised Uncertainty Principle (GUP). First, we explore the shadow's behaviour in the presence of a string cloud using three alternative GUP frameworks: linear quadratic GUP (LQGUP), quadratic GUP (QGUP), and linear GUP. We then used the weak field limit approach to determine the effect of the string cloud and GUP parameters on the light deflection angle, with computation based on the Gauss-Bonnet theorem. Next, to compute the quasinormal modes of Schwarzschild string clouds incorporating quantum correction with GUP, we determine the effective potentials generated by perturbing scalar, electromagnetic and fermionic fields, using the sixth-order WKB approach in conjunction with…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsParticle Accelerators and Free-Electron Lasers · Distributed and Parallel Computing Systems · Particle Detector Development and Performance
