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Quantum computing for space applications: a selective review and perspectives
by
Casati, Rebecca
, Torta, Pietro
, Bruni, Stefano
, Mandarino, Antonio
, Prati, Enrico
in
Algorithms
/ Cognitive tasks
/ Image classification
/ Machine learning
/ Nanotechnology and Microengineering
/ Optimization
/ Physics
/ Physics and Astronomy
/ Prospects for Space Quantum Research
/ Quantum computing
/ Quantum Information Technology
/ Quantum Physics
/ Review
/ Satellite constellations
/ Software
/ Spintronics
2025
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Quantum computing for space applications: a selective review and perspectives
by
Casati, Rebecca
, Torta, Pietro
, Bruni, Stefano
, Mandarino, Antonio
, Prati, Enrico
in
Algorithms
/ Cognitive tasks
/ Image classification
/ Machine learning
/ Nanotechnology and Microengineering
/ Optimization
/ Physics
/ Physics and Astronomy
/ Prospects for Space Quantum Research
/ Quantum computing
/ Quantum Information Technology
/ Quantum Physics
/ Review
/ Satellite constellations
/ Software
/ Spintronics
2025
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Do you wish to request the book?
Quantum computing for space applications: a selective review and perspectives
by
Casati, Rebecca
, Torta, Pietro
, Bruni, Stefano
, Mandarino, Antonio
, Prati, Enrico
in
Algorithms
/ Cognitive tasks
/ Image classification
/ Machine learning
/ Nanotechnology and Microengineering
/ Optimization
/ Physics
/ Physics and Astronomy
/ Prospects for Space Quantum Research
/ Quantum computing
/ Quantum Information Technology
/ Quantum Physics
/ Review
/ Satellite constellations
/ Software
/ Spintronics
2025
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Quantum computing for space applications: a selective review and perspectives
Journal Article
Quantum computing for space applications: a selective review and perspectives
2025
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Overview
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.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
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