Integrated Photonic Reservoir Computing with All-Optical Readout

Integrated photonic reservoir computing has been demonstrated to be able to tackle different problems because of its neural network nature. A key advantage of photonic reservoir computing over other neuromorphic paradigms is its straightforward readout system, which facilitates both rapid training a...

Full description

Saved in:
Bibliographic Details
Published inarXiv.org
Main Authors Ma, Chonghuai, Joris Van Kerrebrouck, Deng, Hong, Sackesyn, Stijn, Gooskens, Emmanuel, Bai, Bing, Dambre, Joni, Bienstman, Peter
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 28.06.2023
Subjects
Hardware
Neural networks
Photonics
Read out systems
Real time
Training
Online AccessGet full text

Cover

More Information
Summary:Integrated photonic reservoir computing has been demonstrated to be able to tackle different problems because of its neural network nature. A key advantage of photonic reservoir computing over other neuromorphic paradigms is its straightforward readout system, which facilitates both rapid training and robust, fabrication variation-insensitive photonic integrated hardware implementation for real-time processing. We present our recent development of a fully-optical, coherent photonic reservoir chip integrated with an optical readout system, capitalizing on these benefits. Alongside the integrated system, we also demonstrate a weight update strategy that is suitable for the integrated optical readout hardware. Using this online training scheme, we successfully solved 3-bit header recognition and delayed XOR tasks at 20 Gbps in real-time, all within the optical domain without excess delays.
ISSN:2331-8422