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cs.CE2026
Robust Matrix-Free Newton-Krylov Solvers via Automatic Differentiation
Marco Pasquale, Stefano Markidis
Jacobian-Free Newton-Krylov (JFNK) methods avoid forming the full Jacobian, but still require Jacobian-vector products, i.e., Gateaux derivatives of the nonlinear residual along Kr…
cs.CE2026
Quantum Optimization for Electromagnetics: Physics-Informed QAOA for Reconfigurable Intelligent Surfaces
Marco Pasquale, Erik M. Åsgrim, Stefano Markidis +1
Optimizing Reconfigurable Intelligent Surfaces (RIS) is a high-dimensional combinatorial challenge. Current quantum algorithms often simplify this problem by ignoring physical cons…
cs.CE2026
BVH-Accelerated Ray Tracing for High-Frequency Electromagnetic Backscattering
Marco Pasquale, Andong Hu, Luca Pennati +2
As computational complexity in electromagnetics increases with frequency, full-wave solvers become computationally infeasible for electrically large problems. To address this limit…