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Researchers at North Carolina State University have introduced a non-Abelian mixer for the Quantum Approximate Optimisation Algorithm that consistently outperforms existing methods in simulations for hybrid quantum processors. This advancement addresses a critical gap in algorithmic development for systems combining qubits and oscillators, offering a more efficient pathway to solving complex optimisation problems like Max-Cut. The technique provides a tangible step forward for leveraging emerging hybrid hardware in practical applications such as network optimisation.
Quantum Algorithm Design Advances with New Hybrid Processor Control
Across all simulated graph sizes, a new quantum mixer consistently delivered better optimisation solutions and a higher chance of finding the best possible answer than existing methods. This non-Abelian mixer, designed for hybrid quantum processors combining qubits and oscillators, represents a tangible step forward in algorithmic development for these emerging systems. Simulations demonstrate improved performance on the Max-Cut problem, suggesting a promising route for tackling complex optimisation challenges.
Algorithms for hybrid continuous-variable and discrete-variable quantum processors have lagged behind hardware advancements. Thinh Le, Hansika Weerasena, and Jianqing Liu of North Carolina State University have created a non-Abelian mixer for the Quantum Approximate Optimisation Algorithm, applied to the Max-Cut problem. Simulations consistently demonstrate this new mixer improves both the quality of solutions and the likelihood of finding the best possible solution, when compared to existing methods. A new computational technique for quantum processors integrating both continuous and discrete quantum bits addresses a current limitation in the field. This innovation centres on a specifically designed ‘mixer’ within the Quantum Approximate Optimisation Algorithm, used to tackle the complex Max-Cut problem, consistently yielding improved solutions in simulations. The development offers…
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