Abstract
The simultaneous advances in artificial neural networks and photonic
integration technologies have spurred extensive research in optical
computing and optical neural networks (ONNs). The potential to
simultaneously exploit multiple physical dimensions of time, wavelength
and space give ONNs the ability to achieve computing operations with
high parallelism and large-data throughput. Different photonic
multiplexing techniques based on these multiple degrees of freedom have
enabled ONNs with large-scale interconnectivity and linear computing
functions. Here, we review the recent advances of ONNs based on
different approaches to photonic multiplexing, and present our outlook
on key technologies needed to further advance these photonic
multiplexing/hybrid-multiplexing techniques of ONNs.