Quantum Computing for Aerospace Research

Tobias Stollenwerk

Eric Donkor, Michael J. Hayduk, Andrew R. Pirich +1 more

Y. K. An

Quantum computing has been a relatively new research area in the physics and computer engineering combined fields since Feynman proposed an abstract model of quantum computer in 1980s. After Shor presented the algorithm for practical implementation of quantum computing in 1994, the research of quantum computing has grown quickly. However, there is a gap between the academic research and the application to industry. This survey paper attempts to fill the gap by presenting the application to the industrial needs specifically to the needs of the aerospace industry.

Tobias Stollenwerk

Tobias Stollenwerk

We report on the mapping of hard optimization problems from aerospace research to the D-Wave quantum annealer.

Fred C. Briggs

Quantum computing is rapidly becoming an invaluable component of aerospace analysis. Selecting a programing language that enables efficient quantum algorithm development and integrates seamlessly with classical simulation tools is essential for translating these capabilities into practice. This paper is a general literature survey of recent research and publications that will attempt to answer the question: What may be appropriate quantum computing software programming language(s) for aerospace applications? What quantum programming language(s) would be suitable for scientific and engineering calculations as FORTRAN was for classical computing? Quantum computing has the potential to make complex aerospace simulations like Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), material, and boundary layer analysis much faster and more efficient. Successful quantum enhancement work has already been completed towards secure quantum space networks, space weather detection and early warning alerts, satellite image processing, and flight path optimization. There is a plethora (thirty-six plus) of quantum computing languages and toolkits today. How do they deal effectively with the unique characteristics of quantum computing like entanglement and the no cloning theory? The differences between Artificial Intelligence (AI) and quantum computing will be discussed and a survey of the current quantum computing software and tools will be presented. A framework for choosing an appropriate quantum programming language for aerospace applications is also provided. Findings from the literature show Python used with the Qiskit platform could be the most useful for aerospace applications.