Erwin Schrödinger Center for Quantum Science & Technology (ESQ)

The researchers/ authors propose a possible application of their device in the framework of quantum machine learning through a scheme of quantum reservoir computing, which they apply to classical and quantum learning tasks. Their simulations show promising results, and may break new ground towards the use of quantum memristors in quantum neuromorphic architectures.

"Unlocking the full potential of quantum resources within artificial intelligence is one of the greatest challenges of the current research in quantum physics and computer science", says Michele Spagnolo, who is first author of the publication in the journal "Nature Photonics". The group of Philip Walther of the University of Vienna has also recently demonstrated that robots can learn faster when using quantum resources and borrowing schemes from quantum computation. This new achievement represents one more step towards a future where quantum artificial intelligence become reality.

For more information see:

https://walther.univie.ac.at/detailview-news/news/artificial-neurons-go-quantum-with-photonic-circuits/?tx_news_pi1%5Bcontroller%5D=News&tx_news_pi1%5Baction%5D=detail&cHash=c0c3cb9a31a54d346d647707ada6c0ea

https://science.apa.at/power-search/287226329491057321

https://www.nature.com/articles/s41566-022-00973-5