Design of Mode-Locked Fibre Laser with Non-Linear Power and Spectrum Width Transfer Functions with a Power Threshold

Abstract

There is a growing demand for higher computational speed and energy efficiency of machine learning approaches and, in particular, neural networks. Optical implementation of neural networks can address this challenge. Compared to other neuromorphic platforms, fibre-based technologies can unlock a wide bandwidth window and offer flexibility in dimensionality and complexity. Moreover, fibre represents a well-studied, low-cost and low-loss material, widely used for signal processing and transmission. At the same time, mode-locked fibre lasers offer flexibility and control, while the mode-locking effect can be crucial for unlocking ultra-short timescales and providing ultra-fast processing. Here, we propose a mode-locked fibre laser with a non-linear power threshold in both power and spectrum. The advantage of the proposed system is a spectrum width two-branch function dependent on the input signal power. The effect is caused by a transition between two operating regimes and is governed by the input signal power. The proposed design enables receiving a non-linear transfer function in amplitude with a power threshold as an optical analogue of biological neurons with the additional advantage of a non-linear two-branch transfer function in spectrum width. The latter property is similar to the frequency-varied response dependent on stimulus properties in biological neurons. Thus, our work opens new avenues in research into novel types of artificial neurons with a frequency spectrum width variable response and, consequently, spiking neural networks and neural-rate-based coding with potential applications in optical communications and networks with flexible bandwidth, such as 5G and emerging 6G.

Publication DOI: https://doi.org/10.3390/app122010318
Divisions: College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT)
College of Engineering & Physical Sciences
Additional Information: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Funding: Royal Academy of Engineering (RF/201718/17154).
Uncontrolled Keywords: optical signal processing,optical neurons,mode-locked fibre lasers
Publication ISSN: 2076-3417
Last Modified: 14 Feb 2024 08:14
Date Deposited: 07 Nov 2022 13:08
Full Text Link:
Related URLs: https://www.mdp ... 417/12/20/10318 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2022-10
Published Online Date: 2022-10-13
Accepted Date: 2022-10-10
Submitted Date: 2022-04-10
Authors: Xie, Ziyi
Peng, Junsong
Sorokina, Mariia (ORCID Profile 0000-0001-6082-0316)
Zeng, Heping

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