Toward neuro-inspired computing using a small network of micro-ring resonators on an integrated photonic chip
Loading...
Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
SPIE
Abstract
We present in this work numerical simulations of the performance of an on-chip photonic reservoir computer
using nonlinear microring resonator as neurons. We present dynamical properties of the nonlinear node and the
reservoir computer, and we analyse the performance of the reservoir on a typical nonlinear Boolean task : the
delayed XOR task. We study the performance for various designs (number of nodes, and length of the synapses
in the reservoir), and with respect to the properties of the optical injection of the data (optical detuning and
power). From this work, we nd that such a reservoir has state-of-the art level of performance on this particular
task - that is a bit error rate of 2.5 104 - at 20 Gb/s, with very good power e ciency (total injected power
lower than 1.0 mW).
Description
Keywords
Neuromorphic Computing, Reservoir Computing, Integrated Photonics, Microring Resonators
Citation
Florian Denis-le Coarer, Damien Rontani, Andrew Katumba, Matthias Freiberger, Joni Dambre, Peter Bienstman, Marc Sciamanna, "Toward neuroinspired computing using a small network of micro-ring resonators on an integrated photonic chip," Proc. SPIE 10689, Neuro-inspired Photonic Computing, 1068908 (21 May 2018); doi: 10.1117/12.2306780