China quantum research team uses AI to crack processing time in supercomputer race

AI is set to transform quantum research with a huge boost in processing speed that could ultimately pave the way for a supercomputer a billion – or even a trillion – times faster than existing technology.

Photo credit: Gavin Tracy

According to a new study by scientists in China – which has established some of the world’s largest quantum research facilities – machine learning technology can slash the time-consuming task of calculating the nature of the quirky ties between particles that exist in the subatomic quantum realm.

The power of quantum technology arises from particles that are linked by the mysterious forces of quantum mechanics.

Quantum entanglement, for example, refers to the correlation between particles that allows changes in one to instantly affect another, regardless of the distance between them. The behavior of these correlated particles forms the basis of quantum information processing.

Now, a Chinese research team has established that machine learning technology can assess the nature of the ties between particles with unprecedented speed and accuracy, according to a paper published this month in the scientific journal Physical Review Letters.

This is important, according to the researchers, because different ties between particles make them suitable for different tasks. As well as quantum entanglement, particles may be related through EPR steering – the paradoxical phenomenon best known for Schrodinger’s Cat – or Bell nonlocality, which states that in some situations the property of a particle can be altered by the act of measuring it.

Most quantum devices – from key distribution networks for ultra safe communication and superfast quantum computers to quantum radar systems for stealth aircraft detection – remain tantalisingly beyond practical application because of the huge amount of traditional processing time required now to establish the nature of the ties between particles.

“It works like the separation of minerals,” said professor Li Chuanfeng, a lead scientist of the study with the University of Science and Technology of China (USTC) in Hefei, Anhui province.

“The AI tells us whether an ore contains gold, iron, or copper, so we can make use of them for different purposes. This was not possible before,” Li said.

Until now, quantum researchers have had to measure a complete set of physical properties to determine the type of link between particles. It is a difficult, time-consuming job and, when the number of particles increases, the workload grows exponentially.

“At the end of the day, we might be able to tell this is not a piece of gold, and that would be it. There is no way to know more,” Li said.

This method will increase the supply of resources for quantum information processing significantly.

USTC researchers have been conducting quantum experiments for decades and amassed a large amount of data. Li’s team built up a data set containing more than 400 pairs of particles carefully picked with different types of links, such as quantum entanglement, EPR steering, and Bell nonlocality.