Quantum Annealing for Aerospace Engineering Applications

This study explores the potential of quantum annealing for solving complex problems in aerospace engineering. Quantum annealing is a metaheuristic optimization technique that utilizes quantum mechanical principles to address combinatorial optimization challenges. Specifically, this paper presents three aerospace applications: (1) computational fluid dynamics, (2) aerodynamic shape optimization, and (3) super-resolution of particle image velocimetry (PIV) images. The proposed quantum annealing-based method obtains a converged flow solution without relying on conventional iterative methods. In aerodynamic shape optimization, the proposed method, based on quantum annealing black-box optimization, identifies an aerodynamic shape that outperforms all shapes in the initial data sets. Finally, it is demonstrated that a velocity field can be reconstructed in PIV using a super-resolved image generated by a quantum Boltzmann machine.