All-optical reservoir computing system based on polarization dynamics

Reservoir computing (RC) is a simplified recurrent neural network, can be implemented by using a nonlinear system with delay feedback, called as delay-based RC. Various nonlinear nodes and feedback loop structures are proposed. Most works are based on the dynamical responses in intensity of the nonlinear systems. There are also a photoelectric RC system based on wavelength dynamics and an all-optical RC based on the phase dynamics of a semiconductor laser with optical feedback, as well as so-called polarization dynamics of a vertical cavity surface emitting laser (VCSEL). However, these VCSEL-RCs actually are based on the intensity dynamics of two mutually orthogonal polarization modes, or polarization-resolved intensity dynamics. The RC based on rich dynamical responses in polarization has not yet been seen. A semiconductor optical amplifier (SOA) fiber ring laser can produce rich dynamical states in polarization, is used in optical chaotic secure communication and distributed optical fiber sensing. To further expand the application of polarization dynamics of the SOA fiber ring laser and open up a new direction for the research of optical RC neural network, an all-optical RC system based on polarization dynamics of the ring laser is proposed. The ring laser is used as the reservoir, and the SOA as the nonlinear node. After the input signal is masked according to a synchronization scheme, it is injected into the reservoir by intensity modulation for a continuous wave generated by a super-luminescent light emitting diode (SLED). The dynamical response in polarization of the ring laser is detected by a polarizer and a photodetector. The influences of the SOA operation current, output power of the SLED and attenuation of a variable optical attenuator (VOA) in the fiber loop on the polarization dynamic characteristic, mainly refers to the output degree of polarization, of the laser are analyzed experimentally. The fading memory abilities and nonlinear responses of the RC system based on the polarization dynamic response and intensity dynamic response are compared in experiment. The influences of output power of the SLED and attenuation of the VOA on fading memory ability, consistency and separation of the RC system based on the two kinds of dynamic responses are investigated experimentally. Thus the range of the VOA attenuation is determined. The network performance of the polarization dynamics RC system is evaluated by processing the Santa Fe time series prediction task and the multi-waveform recognition task. The prediction error can be as low as 0.0058 for the time series prediction task, and the accuracy can be as high as 100% for the recognition task under the appropriate system parameters and only 30 virtual nodes. The experimental results show that the polarization dynamics RC system has good prediction performance and classification ability, which are comparable to the existing intensity dynamics RC system based on the ring laser. The system can be expected to process two tasks in parallel when the polarization dynamics and intensity dynamics are used at the same time.