https://doi.org/10.1140/epjqt/s40507-025-00369-8
Review
Quantum computing for space applications: a selective review and perspectives
Department of Physics Aldo Pontremoli, Università degli Studi di Milano, Via Celoria 16, 20133, Milan, Italy
a
pietro.torta@unimi.it
b
enrico.prati@unimi.it
Received:
21
February
2025
Accepted:
21
May
2025
Published online:
5
June
2025
Space science and technology are among the most challenging and strategic fields in which quantum computing promises to have a pervasive and long-lasting impact. We provide an overview of selected published works reporting the application of quantum computing to space science and technology. Our systematic analysis identifies three major classes of problems that have been approached with quantum computing. The first category includes optimization tasks, often cast into Quadratic Unconstrained Binary Optimization and solved using quantum annealing, with scheduling problems serving as a notable example. A second class comprises learning tasks, such as image classification in Earth Observation, often tackled with gate-based hybrid quantum-classical computation, namely with Quantum Machine Learning concepts and tools. Finally, integrating quantum computing with other quantum technologies may lead to new disruptive technologies, for instance, the creation of a quantum satellite internet constellation and distributed quantum computing. We organize our exposition by providing a critical analysis of the main challenges and methods at the core of different quantum computing paradigms and algorithms, which are often fundamentally similar across different domains of application in the space sector and beyond.
Key words: Quantum Computing / Quantum Annealing / Quantum Machine Learning / Space Science and Technology / Scheduling problems / Earth Observation / Quantum Technologies
© The Author(s) 2025
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