We analyze a theoretical and experimental reservoir computing architecture based on an add-drop silicon micror- ing resonator. We test it with different datasets, including the recognition of flowers from the IRIS dataset.The information is transferred to the ring by means of a high power (>10 mW) pump signal which generates non- linearities affecting a low-power continuous wave signal acting as a probe. The experimental setup was also simulated employing a time domain model [1] of the non-linear response of the ring to assess the physical limit of the pump power
Study of microring nonlinearities in silicon photonics for neuromorphic computing / Salpietro, Salvatore; Novarese, Marco; Rimoldi, Cristina; Gioannini, Mariangela. - 13371:(2025), pp. 1-7. (Intervento presentato al convegno SPIE Photonics West - OPTO tenutosi a San Francisco (USA) nel 25-30 January 2025) [10.1117/12.3040062].
Study of microring nonlinearities in silicon photonics for neuromorphic computing
Salpietro, Salvatore;Novarese, Marco;Rimoldi, Cristina;Gioannini, Mariangela
2025
Abstract
We analyze a theoretical and experimental reservoir computing architecture based on an add-drop silicon micror- ing resonator. We test it with different datasets, including the recognition of flowers from the IRIS dataset.The information is transferred to the ring by means of a high power (>10 mW) pump signal which generates non- linearities affecting a low-power continuous wave signal acting as a probe. The experimental setup was also simulated employing a time domain model [1] of the non-linear response of the ring to assess the physical limit of the pump powerFile | Dimensione | Formato | |
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https://hdl.handle.net/11583/2998718