Multidimensional fiber echo state network analogue

Mariia Sorokina

doi:10.1088/2515-7647/abb584

Abstract

Optical neuoromorphic technologies enable neural network-based signal processing through a specifically designed hardware and may confer advantages in speed and energy. However, the advances of such technologies in bandwidth and/or dimensionality are often limited by the constraints of the underlying material. Optical fiber presents a well-studied low-cost solution with unique advantages for low-loss high-speed signal processing. The fiber echo state network analogue (FESNA), fiber-based neuromorphic processor, has been the first technology suitable for multichannel high bandwidth (including THz) and dual-quadrature signal processing. Here we propose the multidimensional FESNA (MD-FESNA) processing by utilizing multi-mode fiber non-linearity. Thus, the developed MD-FESNA is the first neuromorphic technology which augments all aforementioned advantages of FESNA with multidimensional spatio-temporal processing. We demonstrate the performance and flexibility of the technology on the example of prediction tasks for hyperchaotic systems. These results will pave the way for a high-speed neuromorphic processing of multidimensional tasks, hardware for spatio-temporal neural networks and open new application venues for fiber-based spatio-temporal multiplexing.

Highlights

Optical neuromorphic computing has attracted increasing attention over the past decades [1, 2]
While recently we introduced a fiber-based neuromorphic technology - fiber echo state network (ESN) analogue (FESNA) [11], which realizes signal mixing and neural response by utilizing inherent fiber properties: dispersion and the Kerr non-linearity - this enabled to achieve a dual-quadrature [11], high bandwidth [12, 13] and multi-channel [14] neuromorphic signal processing for the first time
We show that by incorporating multi-mode fiber (MMF), we can achieve multidimensional neuromorphic processing - multidimensional FESNA (MD-FESNA)

Summary

Introduction

Optical neuromorphic computing has attracted increasing attention over the past decades [1, 2]. At the same time there is a surge in developments aimed at increasing operational bandwidth of the neuromorphic systems. An optical ESN utilizing semiconductor laser [9] and silicon photonics for reservoir technology [10] have been developed for processing 20 GHz and 40 GHz bandwidth signals correspondingly. While recently we introduced a fiber-based neuromorphic technology - fiber ESN analogue (FESNA) [11], which realizes signal mixing and neural response by utilizing inherent fiber properties: dispersion and the Kerr non-linearity - this enabled to achieve a dual-quadrature [11], high bandwidth (including THz) [12, 13] and multi-channel [14] neuromorphic signal processing for the first time

Methods

Findings

Discussion

Conclusion