Comprehensive Performance Analysis of a VCSEL-Based Photonic Reservoir Computer

Optical neural networks offer radically new avenues for ultrafast, energy-efficient hardware machine learning and artificial intelligence. Reservoir Computing (RC), given its high performance cheap training has attracted considerable attention photonic network implementations, principally based on semiconductor lasers (SLs). Among SLs, Vertical Cavity Surface Emitting Lasers (VCSELs) possess unique attributes, e.g. speed, low power, rich dynamics, reduced cost, ease to integrate in array architectures, making them valuable candidates future networks. This work provides a comprehensive analysis of telecom-wavelength GHz-rate VCSEL RC system, revealing the impact key system parameters across different processing tasks.