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We have recently seen the emergence of quantum processors with more than 50 qubits. This has initiated a huge world-wide effort to utilize this new computational power. However so far it has not been that easy to extract the computational power promised in those quantum processors. Quantum neural networks has been seen as an approach, through which we might be able to facilitate these new quantum systems for computational tasks. In this seminar, I introduce several ideas with quantum neural networks and present a new quantum computational model which utilizes scale-free networks in the Hilbert space generated by the quantum processors. This quantum computational model is based on both reservoir computation and extreme machine learning and inherits their advantages. We discuss its potential and the advantages it provides.

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Kae Nemoto, National Institute of Informatics, Japan
Zoom (https://uni-koeln.zoom.us/j/91902676314?pwd=SFAyR1kxRUYwV3hDRjhVWDdoTDNEdz09 )
Contact: Anne Matthies