The use of quantum computers asks new scalable SW engineering techniques to be integrated with the “classical” High Performance Computing (HPC) at HW and SW levels. Quantum programming languages control physical specialized devices, coding and code verification is new field tightly connected to the data and application nature. The design of quantum circuits is supported by “classical” programming, simulators or Python. Results are obtained either using simulators that run on the user's own device, quantum software development kits. These tools need adaptations for applications from Remote Sensing (RS) and the particular quantum complexity classes.
Gabriele Cavallaro, Morris Riedel, Thomas Lippert and Kristel Michielsen, "Hybrid Quantum-classical Workflows In Modular Supercomputing Architectures With The Jülich Unified Infrastructure For Quantum Computing", get presentation
Manish K. Gupta, Martin Beseda and Piotr Gawron, "How Quantum Computing-friendly Multispectral Data Can Be?", get presentation
Lorenzo Giuliano Papale, Fabio Del Frate, Leila Guerriero and Giovanni Schiavon, "A Physics-based Ml Approach For Corn Plant Height Estimation With Simulated Sar Data", get presentation
Shanshan Mu and Xiaofeng Li, "Retrieval Of Rainfall Information By Spaceborne C-band Sar Based On Machine Learning"
Gabriele Cavallaro (Forschungszentrum Jülich)
Mihai Datcu (German Aerospace Center - DLR)