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Integrated Photonics-Based Memristor Could Link AI, Quantum Computing

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By developing a photonic quantum memristor, researchers at the University of Vienna, the National Research Council (CNR), and the Polytechnic University of Milan may have found a way to link artificial intelligence (AI) and quantum computing. The researchers engineered a device that works the same as a memristor, while encoding and transmitting quantum information and acting on quantum states.

Memristive devices are electrical components that change their resistance depending on the memory of the previous electrical current flowing through them. They are used in neuromorphic architectures such as neural networks because their behavior is similar to that of a neural synapse.
Abstract representation of a neural network that is made of photons and has memory capability potentially related to artificial intelligence. Courtesy of Equinox Graphics, University of Vienna.
Abstract representation of a neural network that is made of photons and has memory capability potentially related to artificial intelligence. Courtesy of Equinox Graphics, University of Vienna.
Artificial intelligence applications are guided by neural networks that are mathematically trained to mimic human problem-solving. The quantum memristor will improve the speed and efficiency at which neural networks compute information, potentially providing the memory capabilities needed for computations at the quantum level.

The team’s approach exploited the ability of single photons to propagate simultaneously in a superposition of two or more paths. The researchers demonstrated the quantum memristor on an integrated photonic quantum processor operating on single photons. In the experiment, single photons propagated along waveguides that were laser-written on a glass substrate. The laser-written integrated photonic circuits were reconfigurable by means of integrated phase shifters.

The photonic circuit produced memristive dynamics on single-photon states through measurement and classical feedback. The single photons were guided on a superposition of several paths. One path measured the flow of photons traveling through the device. Through a feedback scheme, this measurement controlled the transmission of coherent quantum information, thus achieving memristive behavior.

After characterizing the memristive dynamics of the quantum memristor and tomographically reconstructing its quantum output state, the researchers demonstrated a potential application of the quantum memristor in the framework of quantum machine learning. They designed a memristor-based quantum reservoir computer and tested it numerically on both classical and quantum learning tasks, achieving strong performance with limited physical and computational resources and, most importantly, no architectural change when moving from one type of task to the other.


To the best of the researchers’ knowledge, this is the first experimental demonstration of a quantum memristor. Realizing such a device is especially challenging because the dynamics of a memristor differ from typical quantum behavior.
Artistic representation of a neural network containing optically-interconnected Mach-Zehnder interferometers. The interferometer is the main component of the quantum memristor. Courtesy of Equinox Graphics, University of Vienna.
Artistic representation of a neural network containing optically interconnected Mach-Zehnder interferometers. The interferometer is the main component of the quantum memristor. Courtesy of Equinox Graphics, University of Vienna.
The quantum memristor is scalable to larger architectures using integrated quantum photonics. The only limit to larger scalability, according to the researchers, is the single-photon rate.

The device could be enhanced by integrating optical and electronic components in the same chip; the researchers believe this could be done using current semiconductor technology.

The researchers also believe that the frequency at which the quantum memristor operates could be improved using existing technology. For laser-written circuits, high-frequency operations are readily available at the expense of higher-power consumption, and other photonic platforms routinely enable frequencies even in the gigahertz regime. To take advantage of higher frequencies, however, the photon detection rate would need to be improved. Faster detection rates could be achieved by using customized fast detectors and bright single-photon sources.

The quantum memristor could provide a missing nonlinear element for quantum optical neural networks, providing a link between artificial intelligence and quantum computing.
 
The research was published in Nature Photonics (www.doi.org/10.1038/s41566-022-00973-5).

Published: March 2022
Glossary
integrated photonics
Integrated photonics is a field of study and technology that involves the integration of optical components, such as lasers, modulators, detectors, and waveguides, on a single chip or substrate. The goal of integrated photonics is to miniaturize and consolidate optical elements in a manner similar to the integration of electronic components on a microchip in traditional integrated circuits. Key aspects of integrated photonics include: Miniaturization: Integrated photonics aims to reduce the...
optoelectronics
Optoelectronics is a branch of electronics that focuses on the study and application of devices and systems that use light and its interactions with different materials. The term "optoelectronics" is a combination of "optics" and "electronics," reflecting the interdisciplinary nature of this field. Optoelectronic devices convert electrical signals into optical signals or vice versa, making them crucial in various technologies. Some key components and applications of optoelectronics include: ...
quantum
The term quantum refers to the fundamental unit or discrete amount of a physical quantity involved in interactions at the atomic and subatomic scales. It originates from quantum theory, a branch of physics that emerged in the early 20th century to explain phenomena observed on very small scales, where classical physics fails to provide accurate explanations. In the context of quantum theory, several key concepts are associated with the term quantum: Quantum mechanics: This is the branch of...
artificial intelligence
The ability of a machine to perform certain complex functions normally associated with human intelligence, such as judgment, pattern recognition, understanding, learning, planning, and problem solving.
interferometry
The study and utilization of interference phenomena, based on the wave properties of light.
quantum optics
The area of optics in which quantum theory is used to describe light in discrete units or "quanta" of energy known as photons. First observed by Albert Einstein's photoelectric effect, this particle description of light is the foundation for describing the transfer of energy (i.e. absorption and emission) in light matter interaction.
Research & TechnologyUniversity of ViennaEuropeeducationintegrated photonicsOpticsoptoelectronicsquantumartificial intelligenceneural networksTest & Measurementinterferometryquantum opticssingle photons and quantum effectsmemristorsquantum memristorsTechnology News

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