New light-powered chip could accelerate AI and quantum computing

The advance marks a significant milestone for a growing area of research known as "valleytronics," which could help drive future breakthroughs in faster computing, lower energy consumption, and quantum technologies.

Developed by researchers from the Monash School of Physics and Astronomy, the new device combines advanced nanotechnology with cutting-edge materials to solve a challenge that has limited the field for years.

For the first time, the team has built a fully integrated chip capable of producing specialized light signals, steering them along specific paths, and converting them into electrical signals within the same compact system.

These signals store information using a quantum property called the "valley degree of freedom." Scientists believe this unique characteristic could provide entirely new ways to encode, transmit, and process data.

Integrated Valleytronics Chip Solves Long-Standing Challenge

Lead author Dr. Chi Li, whose team's findings were published in Nature Photonics, said the achievement addresses a major obstacle in valleytronics research.

"Until now, we could generate or detect these signals, but not do everything in one integrated device," Dr. Li said.

"What we've built is a complete on-chip system that can create, route and read this information with very high precision."

The device relies on ultra-thin materials that are only a few atoms thick. These materials are paired with specially engineered nanostructures designed to precisely control light at extremely small scales.

Dr. Kaijian Xing, co-first author of the study and a Research Fellow at Monash University, explained that the team developed a practical way to combine these components.

"We employ a straightforward stacking approach to integrate ultra-thin materials with metasurfaces, overcoming the technical challenges of direct material growth on photonic structures, and enabling further advances in valleytronics," Dr. Xing said.

Room-Temperature Photonic Technology

One of the technology's most important advantages is that it operates at room temperature. Many quantum systems require extremely cold environments, making them more difficult and expensive to use in real-world applications.

Senior author Dr. Haoran Ren, ARC Future Fellow and leader of the Monash NanoMeta Group, said the work could pave the way for a new generation of compact photonic devices that are both programmable and highly efficient.

According to Dr. Ren, the technology could support faster computing systems, reduce energy consumption, and enable new methods for secure communications and advanced data processing.

"This is a significant step toward scalable, chip-based technologies that use light instead of electricity to process information," Dr. Ren said.

"Photonic devices use light to achieve massive bandwidths, ultra-fast data transmission speeds, and lower energy consumption, so what we have achieved has strong potential for applications in quantum computing, advanced imaging, and next-generation optical communication systems."

Processing Multiple Streams of Information

To demonstrate the chip's capabilities, the researchers successfully encoded and processed two separate images at the same time. The experiment showed that the device can manage multiple streams of information simultaneously, an important feature for future computing technologies.

Professor Stefan A. Maier, Head of the School of Physics and Astronomy and Nanophotonics Laboratory at Monash University, said the development helps bridge the divide between fundamental scientific discoveries and practical technologies.

"This is an important step toward fully integrated valleytronic systems," said Professor Maier. "By combining light and quantum materials on a chip, we can access new ways of encoding and processing information."

The international project brought together researchers from Australia, China, Singapore, Germany, and Japan, combining expertise in nanophotonics, two-dimensional materials, and optoelectronics.

The Monash University team included Dr. Chi Li, Dr. Kaijian Xing, Professor Michael S. Fuhrer, Professor Stefan A. Maier, and Dr. Haoran Ren. Additional contributions came from the Singapore University of Technology and Design, LMU Munich, and the University of Technology Sydney.