TY - JOUR

T1 - Forecasting the chaotic dynamics of external cavity semiconductor lasers

AU - Kai, Chao

AU - Li, Pu

AU - Yang, Yi

AU - Wang, Bingjie

AU - Shore, K. Alan

AU - Wang, Yuncai

PY - 2023/3/1

Y1 - 2023/3/1

N2 - Chaotic time series prediction has been paid intense attention in recent years due to its important applications. Herein, we present a single-node photonic reservoir computing approach to forecasting the chaotic behavior of external cavity semiconductor lasers using only observed data. In the reservoir, we employ a semiconductor laser with delay as the sole nonlinear physical node. By investigating the effect of the reservoir meta-parameters on the prediction performance, we numerically demonstrate that there exists an optimal meta-parameter space for forecasting optical-feedback-induced chaos. Simulation results demonstrate that using our method, the upcoming chaotic time series can be continuously predicted for a time period in excess of 2 ns with a normalized mean squared error lower than 0.1. This proposed method only utilizes simple nonlinear semiconductor lasers and thus offers a hardware-friendly approach for complex chaos prediction. In addition, this work may provide a roadmap for the meta-parameter selection of a delay-based photonic reservoir to obtain optimal prediction performance.

AB - Chaotic time series prediction has been paid intense attention in recent years due to its important applications. Herein, we present a single-node photonic reservoir computing approach to forecasting the chaotic behavior of external cavity semiconductor lasers using only observed data. In the reservoir, we employ a semiconductor laser with delay as the sole nonlinear physical node. By investigating the effect of the reservoir meta-parameters on the prediction performance, we numerically demonstrate that there exists an optimal meta-parameter space for forecasting optical-feedback-induced chaos. Simulation results demonstrate that using our method, the upcoming chaotic time series can be continuously predicted for a time period in excess of 2 ns with a normalized mean squared error lower than 0.1. This proposed method only utilizes simple nonlinear semiconductor lasers and thus offers a hardware-friendly approach for complex chaos prediction. In addition, this work may provide a roadmap for the meta-parameter selection of a delay-based photonic reservoir to obtain optimal prediction performance.

KW - Chaos

KW - Electric fields

KW - Numerical simulation

KW - Optical devices

KW - Power spectra

KW - Semiconductor lasers

U2 - 10.1364/OL.480874

DO - 10.1364/OL.480874

M3 - Article

VL - 48

SP - 1236

EP - 1239

JO - Optics Letters

JF - Optics Letters

SN - 0146-9592

IS - 5

ER -