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Earth Observation (EO) satellites generate a growing amount of data every year and highlight the need for scalable algorithms and adequate computational resources. However, the question about how to leverage quantum computing for enhancing the required computational steps is still largely unanswered. The QC4EO study proposes insightful answers and potential solutions to this question. The study has been conducted in the period March 2023 – October 2023 by a consortium led by Forschungszentrum Jülich, with Thales Alenia Space Italy/France, INFN and IQM, and supported by the European Space Agency. The scope of the study covers 12 use cases and a 15-year timeframe, evaluating a potential practical advantage of quantum computing in specific computational tasks and the availability of the required hardware in the near future.




UC1: Mission Planning for EO applicationsFinding an  optimal acquisition plan of a satellite constellation given user requestsAcquisition planning is a combinatorial optimization problem of exponential complexity, currently solved with deterministic or heuristic methodsTwo different approaches have been studied: quantum optimization and quantum machine learning
UC2: Multiple-view Geometry on Optical ImagesAnalyzing satellite images of a specific area captured from various perspectivesKeypoint extraction: combinatorial optimization problem of exponential
Quantum clustering:
quantum k-medoids,
quantum kernel density
UC3: Optical Satellite Data AnalysisAnalyzing the semantic content of satellite imagesKernel methods: quadratic algorithmic complexity and time overhead of kernel computation, expressivity of
the kernel
Quantum kernels
UC4: SAR Raw Data ProcessingImage generation of an area of interest from the raw signal received by the SAR systemFrequency-based methods (Range Doppler): polylogarithmic complexity of Fourier transformationQuantum Range Doppler Algorithm
This study culminated in the release of four technical deliverables and an executive summary, each encompassing a detailed analysis of four selected use cases, i.e., mission planning for EO acquisitions, multiple-view geometry on optical images, optical satellite data analysis, and SAR raw data processing. The use cases have been selected according to their impact for the space industry and their compatibility with the expected development of quantum computing devices in the considered timeframe. For each use case, a relevant quantum algorithm is selected, a realistic problem instance is defined, and a timeline is proposed, mapping the problem size with quantum hardware requirements. Superconducting qubits and ion-traps are considered the most promising quantum computing technologies. The QC4EO study concludes that executing experiments on real hardware is expected to be possible for a reasonable problem size in the near future, providing practical insights on the theoretical advantage of the designed quantum algorithms.
The QC4EO study provides an analysis of the exploitation of quantum algorithms and computing technologies for four selected use cases that hold high interest and impact in the domain of Earth Observation (EO). The main results regarding the expected predictions for effective usage of quantum computing are illustrated in the timeline. The tables show time predictions regarding the applicability of quantum computing to the use cases for different problem instance sizes. Some problems of small size, which are still distant from effective practical use, might be solved in a 3-5 year time frame. Full-size problems, on the other hand, are expected to be efficiently solved in at least 15 years, with improved, and possibly error-resilient, quantum computing hardware. It is important to point out, however, that these predictions were made considering the current knowledge of different quantum hardware platforms, and therefore, the actual possibility of efficiently solving the use-cases using quantum computing may change depending on future research findings.


To further explore the intersection of High-Performance Computing (HPC) and EO, the HPC and Innovative Computing workshop was organized. The workshop, held at ESRIN, the ESA center for Earth Observation in Frascati, Italy, on October 12th, 2023, brought together experts from the HPC and EO fields to discuss their interconnections, future prospects, and challenges.The event featured speakers from European HPC centers such as FZ Julich, Cineca, and CSC, as well as representatives from IQM computers, the University of Padova, and ESA. The workshop had 25 attendees in person and an additional 75 participants online. The presentations and the report on the workshop can be found below.

ESA High Performance and Innovative Computing (HPIC) Workshop
Report on the HPIC workshop
HPC and Quantum Computing: Impact and Future TrendsG. Cavallaro, FZ Julich
Quantum Computing in EuropeG. Bettonte, CINECA
Quantum Computing PlatformsJiri Guth Jarkovsky, IQM Computers
Climate Digital Twin + Quantum?Mikael Johansson, CSC
Tensor Network applications to quantum computingIlaria Siloi, University of Padova
Destination Earth – The potential of high-performance computingLuca Girardo, ESA


Additional contributions
Scientific ContributionsConference and WorkshopLink
A Single-Step Multiclass SVM Based on Quantum Annealing for Remote Sensing Data ClassificationIEEE JSTARSAccess
Kernel Approximation on a Quantum Annealer for Remote Sensing Regression TasksIEEE JSTARSAccess
Adiabatic Quantum Kitchen Sinks With Parallel Annealing For Remote Sensing Regression ProblemsIGARSS 2023, Pasadena, USAAccess
Quantum Computing for Earth Observation Study: A Space Sector Industry perspectiveESA Quantum Conference 2023, Matera, ItalyAccess
Challenges and Opportunities in the Adoption of High Performance Computing for Earth Observation Applications in the Exascale EraBiDS 2023, Vienna, AustriaAccess



Technical ContributionsLink
QC4EO Study Executive SummaryAccess
QC4EO Study Executive slide deckAccess
Use-Case 1 Mission Planning for Earth Observation Acquisitionsexecutive summary pdf
Use-Case 2 Multiple-view Geometry on Optical Imageexecutive summary pdf
Use-Case 3 Optical Satellite Data Analysisexecutive summary pdf
Use-Case 4 SAR Raw Data Processingexecutive summary pdf
QC4EO Study Final Reports:
QC4EO WP1 D1 Use case definition and design reportAccess
QC4EO WP2 D2 Machine Definition ReportAccess
QC4EO WP3 D3 Machines Roadmap Assessment ReportAccess
QC4EO WP4 D4 Use Cases Timeline ReportAccess



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