Quantum-Based Optimization of Reconfigurable Intelligent Surfaces: Barren Plateaus Analysis

Reconfigurable intelligent surface (RIS) optimization is a high-dimensional combinatorial problem, where classical methods face significant scalability challenges. The quantum approximate optimization algorithm (QAOA) offers a promising alternative by encoding the optimization problem into a quantum Hamiltonian and finding its ground state through a parameterized quantum circuit, known as the ansatz [1]. In the quantum framework, the RIS optimization problem is mapped onto the Sherrington-Kirkpatrick (SK) Hamiltonian, which models the transfer function between the transmitting antenna (TX) and the receiver (RX) [2], [3] as follows: