Photonics Breakthroughs 2024: Nonlinear Photonic Computing at Scale - Hao Wang; Jianqi Hu; Andrea Morandi; Alfonso Nardi; Fei Xia; Xuanchen Li; Romolo Savo; Qiang Liu; Rachel Grange; Sylvain Gigan (IEEE Photonics Journal)
A photonic neural network utilizes photons instead of electrons to process information, with the prospect of higher computing efficiency, lower power consumption, and reduced latency. This paper reviews several recent breakthroughs in large-scale photonic neural networks incorporating nonlinear operations. Specifically, we highlight our recent work, which leverages multiple light scattering and second harmonic generation in a slab of disordered lithium niobate nanocrystals for high-performance nonlinear photonic computing. The interplay of these optical effects not only enhances the computational capabilities of photonic neural networks but also increases the number of photonic computing operations. In addition, we discuss current challenges and outline future directions of nonlinear photonic computing. These advancements pave the way for exploring new frontiers in optical computing, unlocking opportunities for innovative experimental implementations, broad applications, and theoretical foundations of photonic neural networks.