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This research demonstrates a significant breakthrough in applying quantum optimization to Reconfigurable Intelligent Surfaces (RIS), achieving near-optimal power aggregation with up to 16 elements using a novel $2^{m}$-phase dictionary. By overcoming the computational barriers of discrete-phase problems, this work establishes a viable pathway for scalable wireless communication enhancements on future fault-tolerant quantum computers.

Source coveringQuantum Zeitgeist

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Gulbahar and Colleagues Introduce $2^{m}$-Phase Dictionary for RIS Power Optimization

Quantum ZeitgeistJuly 21, 20266 min read

Achieving comparable performance to established classical algorithms using quantum optimisation was previously limited to small reconfigurable intelligent surface systems. Now, a thirty-two phase dictionary delivers near-optimal power aggregation for RIS with up to sixteen elements, a result unattainable with higher-order quantum models. This approach signals a pathway towards scalable quantum-enhanced wireless communication using future fault-tolerant computers.

Researchers Burhan Gulbahar, from the Yasar University, and colleagues, have developed a new method for optimising power in reconfigurable intelligent surface (RIS) systems. Their design utilises a 2M-phase dictionary for offline QAOA angle optimisation, bounding spin-Hamiltonian interaction order and demonstrating performance approaching a near-optimal classical reference for RIS channels with up to 16 elements. The method suggests a pathway towards achieving near-optimal performance with large-scale RIS deployments on future quantum computers. The team tackles the computational challenge of discrete-phase optimisation, typically NP-hard, and the limitations of applying the quantum approximate optimisation algorithm (QAOA) to RIS, such as barren plateaus and the need…

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