Hypermultiplexed integrated photonics–based optical tensor processor
- Shaoyuan Ou
- Kaiwen Xue
- Lian Zhou
- Chun-ho Lee
- Alexander Sludds
- Ryan Hamerly
- Ke Zhang
- Hanke Feng
- Yue Yu
- Reshma Kopparapu
- Eric Zhong
- Cheng Wang
- Dirk Englund
- Mengjie Yu
- Zaijun Chen
2025-06-11
The escalating data volume and complexity resulting from the rapid expansion of artificial intelligence (AI), Internet of Things (IoT), and 5G/6G mobile networks is creating an urgent need for energy-efficient, scalable computing hardware. Here, we demonstrate a hypermultiplexed tensor optical processor that can perform trillions of operations per second using space-time-wavelength three-dimensional optical parallelism, enabling O(N 2 ) operations per clock cycle with O(N) modulator devices. The system is built with wafer-fabricated III/V micrometer-scale lasers and high-speed thin-film lithium niobate electro-optics for encoding at tens of femtojoules per symbol. Lasing threshold incorporates analog inline rectifier (ReLU) nonlinearity for low-latency activation. The system scalability is verified with machine learning models of 405,000 parameters. A combination of high clock rates, energy-efficient processing, and programmability unlocks the potential of light for low-energy AI accelerators for applications ranging from training of large AI models to real-time decision-making in edge deployment.