New superconducting diode could boost AI performance

A University of Minnesota Twin Cities-led team has developed a superconducting diode, a key component in electronic devices that could help scale up quantum computers for industry use and improve the performance of artificial intelligence systems. Compared to other superconducting diodes, the researchers’ device is more energy efficient, can process multiple electrical signals at a time and contains a series of gates to control the flow of energy. The research findings were published in Nature Communications.

A diode allows current to flow one way but not the other in an electrical circuit. It is essentially half of a transistor, the main element in computer chips. Diodes are typically made with semiconductors, but researchers are interested in making them with superconductors, which have the ability to transfer energy without losing any power along the way.

Vlad Pribiag, senior author of the paper, said the researchers want to make computers more powerful, but have faced some challenges with current materials and fabrication methods. “We need new ways to develop computers, and one of the biggest challenges for increasing computing power right now is that they dissipate so much energy. So, we’re thinking of ways that superconducting technologies might help with that,” Pribiag said.

The University of Minnesota researchers created the device using three Josephson junctions, which are made by sandwiching pieces of non-superconducting material between superconductors. In this case, the researchers connected the superconductors with layers of semiconductors. The device’s unique design allowed the researchers to use voltage to control the behaviour of the device. The device can also process multiple signal inputs, whereas typical diodes can only handle one input and one output. This feature could have applications in neuromorphic computing, a method of engineering electrical circuits to mimic the way neurons function in the brain to enhance the performance of artificial intelligence systems.

Mohit Gupta, first author of the paper, said the new device has an extremely high energy efficiency, with the researchers demonstrating that it is possible to add gates and apply electric fields to tune this effect. “Other researchers have made superconducting devices before, but the materials they’ve used have been very difficult to fabricate. Our design uses materials that are more industry-friendly and deliver new functionalities,” Gupta said.

The method the researchers used can, in principle, be used with any type of superconductor, making it more versatile and easier to use than other techniques in the field. Because of these qualities, their device is more compatible for industry applications and could help scale up the development of quantum computers for wider use.

“Right now, all the quantum computing machines out there are very basic relative to the needs of real-world applications. Scaling up is necessary in order to have a computer that’s powerful enough to tackle useful, complex problems. A lot of people are researching algorithms and usage cases for computers or AI machines that could potentially outperform classical computers. Here, we’re developing the hardware that could enable quantum computers to implement these algorithms. This shows the power of universities seeding these ideas that eventually make their way to industry and are integrated into practical machines,” Pribiag said.

Image credit: Olivia Hultgren