Geodesics and scalar perturbations of Schwarzschild black holes embedded in a Dehnen-type dark matter halo with quintessence (2505.18611v1)
Abstract: We perform a thorough analysis into a Schwarzschild black hole embedded in a Dehnen-type dark matter halo with a quintessential field. We develop the composite spacetime metric and examine its geometric properties, including horizon structure and curvature invariants. Our findings reveal that increasing both the DM core density $\rho_{s}$ and quintessence parameter $c$ leads to an expansion of the event horizon and a reduction in the size of the cosmological horizon. We then investigate the dynamics of timelike and null geodesics, focusing on the determination of innermost stable circular orbits, photon sphere radii, and black hole shadow features. Thereafter, using the Gauss-Bonnet theorem, we calculate the weak deflection angles, demonstrating that lensing effects are enhanced with increasing halo density and radius. Scalar perturbations are examined using the sixth-order WKB method and Pad\'{e} approximants, highlighting suppressed quasinormal mode frequencies as DM density rises. Greybody factors and Hawking radiation sparsity are also explored, showing increased transmission coefficients for larger halos and deviations from standard blackbody behavior. These results underscore the significant influence of DM and quintessence on black hole observables, offering testable predictions for astrophysical probes such as Event Horizon Telescope imaging and gravitational wave spectroscopy. Scalar perturbations are analyzed using the 6th-order WKB method, demonstrating that quasinormal mode frequencies are suppressed as the DM density increases. We also explore greybody factors and the sparsity of Hawking radiation, showing increased transmission coefficients for larger halos and deviations from standard blackbody behavior.
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.