Already, artificial intelligence and machine learning are being applied to fields such as predictive maintenance and supply chain management, but Airbus believes that “traditional computers [are] approaching their limits.”
In response, it has launched a global challenge asking quantum computing experts to propose and develop solutions for complex optimization and modelization across the full aircraft lifecycle.
Quantum computers work very differently to classical computers in that they utilize the ability of quantum particles to exist in many states simultaneously. Therefore a given number of quantum bits (qubits) can hold exponentially more information than the same number of classical computer bits.
However, they are mainly useful for specific tasks and despite a long-held understanding of quantum computers’ theoretical superiority for certain functions, it was only in late 2018 that an advantage over classical computers was definitively demonstrated.
Accordingly, it may be several years before we see a practical application for aviation.
That said, the industry’s increasing use of data, and the ballooning volume of information coming off aircraft and engine sensors, could be an ideal fit for quantum computing, one use of which is to speed up machine learning.
For starters, Airbus has identified five distinct challenges in the flight physics domain that have an impact on all aspects of its business, from design and operations, to airline revenue streams. With varying degrees of complexity, the statements range from the simple optimization of aircraft climb to the more complex optimization of wing-box design.
The Airbus Quantum Computing Challenge will run through 2019.