Artificial intelligence has become ubiquitous, with applications such as speech interpretation, image recognition, medical diagnosis, and many more. At the same time, quantum technology has been proven capable of computational power well beyond the reach of even the world's largest supercomputer.

Figure 1: Quantum Memristor in photonic circuit.

Figure I state that the Physicists at the University of Vienna have now demonstrated a new device, called quantum memristor.

The experiment, carried out in collaboration with the National Research Council (CNR) and the Politecnico di Milano in Italy.

It has been realized on an integrated quantum processor operating on single photons. The work is published in the current issue of the journal Nature Photonics. [1]

The heart of all artificial intelligence applications are mathematical models called neural networks. These models are inspired by the biological structure of the human brain, made of interconnected nodes.

Just like our brain learns by constantly rearranging the connections between neurons, neural networks can be mathematically trained by tuning their internal structure.

Having integrated devices capable of performing the computations involved in neural networks quickly and efficiently has thus become a major research focus, both academic and industrial.[2]

“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.[3]

References:

1. https://www.sciencedaily.com/releases/2022/03/220324122549.htm
2. https://phys.org/news/2022-03-artificial-neurons-quantum-photonic-circuits.html
3. https://www.thinkingport.com/2022/03/25/news-79131/

Cite this article:

Sri Vasagi K (2022), AI and Quantum Computing in Photonic Circuits, Anatechmaz, pp. 53