What are the potential, challenges, and path forward in quantum optimization?
In this comprehensive study on quantum optimization, we are proud to be part of a team of 46 authors discussing the current potential in quantum optimization. The paper explores the potential for quantum advantage in optimization, using computational complexity theory to identify scenarios where quantum methods could surpass classical techniques. It discusses various paradigms in quantum optimization algorithm design, including Grover Search and Quantum Adiabatic Algorithm, and outlines prominent problem classes in optimization. Additionally, it assesses the execution of these algorithms on noisy quantum hardware and emphasizes the importance of benchmarking and fair comparison with classical optimization methods. It concludes with illustrative applications in finance and sustainability, highlighting real-world impact potentials of quantum optimization.
Check out the paper here.
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