CASE STUDY
Quantum Utility Unlocked for the Aerospace Industry
Access world-class algorithms, build, tune and run hybrid quantum models and unlock business value today
The Problem: Satellite Mission Planning
Earth imaging satellites are a crucial part of our everyday lives, impacting services such as connectivity, navigation, and media. Therefore, it is critical that satellites are employed efficiently and reliably. As they receive dynamic instructions on how to execute their mission in orbit, optimally planning the exact sequence of tasks is a complex endeavour, known as the satellite mission planning problem, which may be computationally prohibitive to solve at scale.
The Objective
The satellite mission planning problem consists of maximizing the number of images captured by satellites based on a list of task requests and available time. The goal is to optimize the order of task requests, maximizing the number of completed requests, given numerous constraints, including fuel, opportunity cost, and second-order consequences.
Our Solution
Collaborating with a global leader in new technology solutions for aerospace, a hybridized quantum-enhanced approach to satellite mission planning optimization was delivered, using hybrid quantum algorithms in the areas of machine learning and optimization, demonstrating their superior performance and potential for unlocking significant additional revenue.
Performance Metrics
- Maximize the completion rate of the imaging requests
- Minimize computation time
- Optimize the order of requests tackled in order to maximize the ratio of high-value requests and unlock new revenue
98.5%
Imaging capture task completion rate, using hybridized quantum-enhanced methods
1.5%
Improvement in solution optimality versus the existing greedy algorithms, leveraging the Hybrid AlphaZero method
2x
Improvement in run time (faster calculation) using hybrid quantum optimization methods