Comment on "All-optical machine learning using diffractive deep neural networks"
This is an incremental comment clarifying theoretical limitations in optical computing for researchers in photonics and machine learning.
The authors critique a prior study for mischaracterizing a linear optical setup as an all-optical deep learning framework, arguing it overlooks the system's linearity and passivity.
Lin et al. (Reports, 7 September 2018, p. 1004) reported a remarkable proposal that employs a passive, strictly linear optical setup to perform pattern classifications. But interpreting the multilayer diffractive setup as a deep neural network and advocating it as an all-optical deep learning framework are not well justified and represent a mischaracterization of the system by overlooking its defining characteristics of perfect linearity and strict passivity.