Minimum complexity integrated photonic architecture for delay-based reservoir computing - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Optics Express Année : 2023

Minimum complexity integrated photonic architecture for delay-based reservoir computing

Résumé

Reservoir computing is an analog bio-inspired computation scheme for efficiently processing time-dependent signals, the photonic implementations of which promise a combination of massive parallel information processing, low power consumption, and high-speed operation. However, most of these implementations, especially for the case of time-delay reservoir computing, require extensive multi-dimensional parameter optimization to find the optimal combination of parameters for a given task. We propose a novel, largely passive integrated photonic TDRC scheme based on an asymmetric Mach-Zehnder interferometer in a self-feedback configuration, where the nonlinearity is provided by the photodetector, and with only one tunable parameter in the form of a phase shifting element that, as a result of our configuration, allows also to tune the feedback strength, consequently tuning the memory capacity in a lossless manner. Through numerical simulations, we show that the proposed scheme achieves good performance-when compared to other integrated photonic architectures-on the temporal bitwise XOR task and various time series prediction tasks, while greatly reducing hardware and operational complexity.
Fichier principal
Vignette du fichier
Abdalla2023_oe-31-7-11610.pdf (2.51 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-04047354 , version 1 (27-03-2023)

Identifiants

Citer

Mohab Abdalla, Clément Zrounba, Raphael Cardoso, Paul Jimenez, Guanghui Ren, et al.. Minimum complexity integrated photonic architecture for delay-based reservoir computing. Optics Express, 2023, 31 (7), pp.11610. ⟨10.1364/OE.484052⟩. ⟨hal-04047354⟩
26 Consultations
19 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More