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Quantum computing uses the physical principles of very small systems todevelop computing platforms which can solve problems that are intractable onconventional supercomputers. There are challenges not only in building therequired hardware, but also in identifying the most promising application areasand developing the corresponding quantum algorithms. The availability ofintermediate-scale noisy quantum computers is now propelling the developmentsof novel algorithms, with applications across a variety of domains, includingin aeroscience. Variational quantum algorithms are particularly promising sincethey are comparatively noise tolerant and aim to achieve a quantum advantagewith only a few hundred qubits. Furthermore, they are applicable to a widerange of optimization problems arising throughout the natural sciences andindustry. To demonstrate the possibilities for the aeroscience community, wegive a perspective on how variational quantum algorithms can be utilized incomputational fluid dynamics. We discuss how classical problems are translatedinto quantum algorithms and their logarithmic scaling with problem size. As anexplicit example we apply this method to Burgers' Equation in one spatialdimension. We argue that a quantum advantage over classical computing methodscould be achieved by the end of this decade if quantum hardware progresses ascurrently envisaged and emphasize the importance of joining up development ofquantum algorithms with application-specific expertise to achieve real-worldimpact.

Variational Quantum Algorithms for Computational Fluid Dynamics