Sparse distance-penalized Ising models are required for feasible QAOA execution on NISQ devices when optimizing RIS with mutual coupling, at the cost of reduced beamforming precision compared to dense models.
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Quantum Optimization for Electromagnetics: Physics-Informed QAOA for Reconfigurable Intelligent Surfaces
Sparse distance-penalized Ising models are required for feasible QAOA execution on NISQ devices when optimizing RIS with mutual coupling, at the cost of reduced beamforming precision compared to dense models.