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

T. Wang, C. Jiang, Q. Fang, X. Guo, Y. Zhang, C. Jin, S. Xiang

Nonlinear photonic sources including semiconductor lasers have recently been utilized as ideal computation elements for information processing. They supply energy-efficient way and rich dynamics for classification and recognition tasks. In this work, we propose and numerically study the dynamics of complex photonic systems including high-$\beta$ laser element with delayed feedback and functional current modulation, and employ nonlinear laser dynamics of near-threshold region for the application in reservoir computing. The results indicate a perfect (100$\%$) recognition accuracy for the pattern recognition task, and an accuracy of about 98$\%$ for the Mackey-Glass chaotic sequences prediction. Therefore, the system shows an improvement of performance with low-power consumption, in particular, the error rate is an order of magnitude smaller in comparison with previous works.

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