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Nonlinear photonic sources including semiconductor lasers have recently beenutilized as ideal computation elements for information processing. They supplyenergy-efficient way and rich dynamics for classification and recognitiontasks. In this work, we propose and numerically study the dynamics of complexphotonic systems including high-$\beta$ laser element with delayed feedback andfunctional current modulation, and employ nonlinear laser dynamics ofnear-threshold region for the application in time-delayed reservoir computing.The results indicate a perfect (100$\%$) recognition accuracy for the patternrecognition task, and an accuracy of about 98$\%$ for the Mackey-Glass chaoticsequences prediction. Therefore, the system shows an improvement of performancewith low-power consumption, in particular, the error rate is an order ofmagnitude smaller in comparison with previous works. Furthermore, by changingthe DC pump, we are able to modify the amount of spontaneous emission photonsof the system, this then allow us to explore how the laser noise impact theperformance of the reservoir computing system. Through manipulating thesevariables, we show a deeper understanding on the proposed system, which ishelpful for the practical applications of reservoir computing.

Reservoir computing and task performing through using high-$\beta$ lasers with delayed optical feedback