Katumba, AndrewFreiberger, MatthiasLaporte, FlorisLugnan, AlessioSackesyn, StijnMa, ChonghuaiDambre, JoniBienstman, Peter2022-11-302022-11-302018Katumba, A., Freiberger, M., Laporte, F., Lugnan, A., Sackesyn, S., Ma, C., ... & Bienstman, P. (2018). Neuromorphic computing based on silicon photonics and reservoir computing. IEEE Journal of Selected Topics in Quantum Electronics, 24(6), 1-10.https://ieeexplore.ieee.org/abstract/document/8331848/https://nru.uncst.go.ug/handle/123456789/5584We present our latest progress using new neuromorphic paradigms for optical information processing in silicon photonics. We show how passive reservoir computing chips can be used to perform a variety of tasks (bit level tasks, nonlinear dispersion compensation, ...) at high speeds and low power consumption. In addition, we present a spatial analog of reservoir computing based on pillar scatterers and a cavity, that can be used to speed up classification of biological cells.enSilicon photonicsNeuromorphic computingReservoir computingArticle