GTGIB couples graph structure learning with a temporal information bottleneck and is claimed to beat existing link prediction methods on four real-world networks.
Fermionic greybody factors and strong gravitational lensing by Lorentz-violating global monopole
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abstract
In this work, we study the greybody factors (GFs) of spin 1/2 and spin 3/2 fermions for a black hole with global monopole in self-interacting Kalb-Ramond gravity with Lorentz symmetry violation. For our purpose, we consider the Dirac and Rarita-Schwinger equations in curved spacetime by proceeding with separating these equations into sets of radial and angular equations. Using the analytical solution of the angular equation, the Schr\"{o}dinger-like wave equations with potentials are derived by decoupling the radial wave equations using the tortoise coordinate. Moreover, we calculate the angular deflection of light in the strong field limit. With the expression for angular deflection in the strong field limit, we compute the positions as well as magnification of the respective relativistic images. We compute the shadows cast by the Lorentz-violating (LV) black hole with a global monopole and analyze how the LV parameter and the monopole charge affect the shadows.
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cs.LG 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
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Graph Structure Learning with Temporal Graph Information Bottleneck for Inductive Representation Learning
GTGIB couples graph structure learning with a temporal information bottleneck and is claimed to beat existing link prediction methods on four real-world networks.