Novel optical neural network architecture with the temporal synthetic dimension [article]

Bo Peng, Shuo Yan, Dali Cheng, Danying Yu, Zhanwei Liu, Vladislav V. Yakovlev, Luqi Yuan, Xianfeng Chen
2021 arXiv   pre-print
Optical neural networks, employing optical fields and photonic tools to perform artificial neural network computations, are rapidly advancing and are generating a broad interest and sparking new applications. We propose a nascent approach for realizing the optical neural network utilizing a single resonator network, where the arrival times of optical pulses are interconnected to construct a synthetic temporal dimension. The set of pulses in each roundtrip therefore provides the sites in each
more » ... er in the optical neural network, and can be linearly transformed with splitters and delay lines, including the phase modulators, when pulses circulate inside the network. Such linear transformation can be arbitrarily controlled by applied modulation phases, which serve as the building block of the neural network together with a nonlinear component for pulses. We validate the functionality of the proposed optical neural network using an example of a complicated wine classification problem. This proof of principle demonstration opens up an opportunity to develop a photonics-based machine learning in a single ring network utilizing the concept of synthetic dimensions. Our approach holds flexibility and easiness of reconfiguration with potentially complex functionality in achieving desired optical tasks, pointing towards promisingly perform on-chip optical computations with further miniaturization.
arXiv:2101.08439v1 fatcat:g6gm5ny4eng4tjhhk7l3jlrdiu