Quantum memristor is a device that could allow combining artificial intelligence and quantum computing. The study, published in Nature Photonics, could spark research and innovations never seen before. It was a team of physicists from the Physics Department of the Milan Polytechnic, the Institute of Photonics and Nanotechnologies of the Italian National Research Council (CNR-IFN) and the University of Vienna to develop the device.
It all starts with neurons
Neural networks are a type of algorithm for performing Artificial Intelligence. These are “neuromorphic” structures, inspired by the biological structure of the human brain which is made up of interconnected nodes, the neurons. Just as in brain the learning process is based on the reorganization of the connections between neurons, artificial neural networks can be “trained” on a set of data that modify its internal structure, making it capable of carrying out tasks “human”.
In this case memory-resistor, or memristor is a component that changes its electrical resistance based on a memory of the current that has passed through it. As would neural synapses. The memristor, therefore, can become a fundamental component for building neuromorphic architectures.
AI with quantum possibilities.
The Italian-Austrian group of experimental physicists has shown that it is possible to engineer an optical device with the same functional characteristics of the memristor, capable of operating on quantum states of light and thus encoding and transmitting quantum information: a quantum memristor precisely.
Making such a device is not trivial, since the dynamics of the memristor would tend to compromise some advantageous aspects of quantum devices. Our researchers have overcome this challenge by employing single photons and exploiting their quantum ability to propagate simultaneously in two or more paths. These photons are conducted in so-called optical circuits, fabricated by laser pulses in a glass chip, dynamically reconfigurable, which can support superposition quantum states on different paths. By measuring the flow of photons propagating on one of these paths, it is possible, through a complex electronic feedback scheme, to reconfigure the transmission of the device on the other output, and this allows to obtain a functionality equivalent to that of the memristor”
Roberto Osellame, research director at CNR-IFN
This result seems to indicate that the quantum memristor can therefore combine AI and quantum computing.
“We also simulated an entire optical network made up of quantum memristors, showing that it could be used to learn both classical and quantum tasks”
Andrea Crespi, associate professor at the Milan Polytechnic
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