Performance Enhancement of Reservoir Computing based on Fabry-Pérot Laser as All-Optical Reconfigurable Nonlinear Node

The paper explores the performance enhancement of a photonic reservoir computer through the reconfigurability of all-optical nonlinear node based on Fabry-Pérot laser diode. By benchmarking various tasks with differing computational demands, we demonstrate how reconfigurability offers flexible computational capabilities, enabling the reservoir computer to adapt to specific tasks while striking an optimal balance between nonlinear transformation and linear memory. We achieve the state-of-the-art results using a basic delay-line reservoir computer concept with a small number of virtual nodes (∼30 nodes).