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gr-qc2026
Learning Parameters of dRGT Black Holes in Nonlinear Electrodynamics with Neural Network Scenarios
Adil Belhaj, Salah Eddine Ennadifi, Maryem Jemri
Using machine learning methods, we present constraining parameter scenarios of AdS black holes in dRGT-like massive gravity coupled to nonlinear electrodynamics. We first approach…
gr-qc2025
Constraining Black Hole Shadows in Dunkl Spacetime using CUDA Numerical Computations
Saad Eddine Baddis, Adil Belhaj, Hajar Belmahi +1
With the help of CUDA high-performance numerical codes exploited in machine learning, we investigate the shadow aspect of new rotating and charged black holes using the Dunkl deriv…