Polarization Multiplexing Reservoir Computing Based on a VCSEL With Polarized Optical Feedback

We propose to realize the parallel tasks processing by reservoir computing (RC) using two polarization-resolved modes in a single vertical-cavity surface-emitting laser (VCSEL). Two feedback cases, parallelly-polarized optical feedback (PPOF) and orthogonally-polarized optical feedback, are considered in the VCSEL. A time series prediction task and a waveform recognition task are employed to examine the parallel tasks processing performance in two polarization-resolved modes of the VCSEL-based RC system. Through numerical simulations, the dependences of parallel tasks processing performance of the VCSEL-based RC system on the feedback strength, injection strength are analyzed carefully and compared for the two feedback cases. Besides, the effects of injection current, frequency detuning, spontaneous emission noise, and the number of virtual nodes are also examined. It is found that, for both feedback cases, good performance of parallel tasks processing in two polarization modes of the VCSEL-based RC system could be obtained in broad parameter regions, and in these regions a better performance is achieved for the PPOF case. This proposed polarization multiplexing RC based on VCSEL permits parallel tasks processing in two polarization modes in a single VCSEL, and hence is interesting and valuable for low power consumption neuromorphic photonics systems.