21 May 2018 Toward neuro-inspired computing using a small network of micro-ring resonators on an integrated photonic chip
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Abstract
We present in this work numerical simulations of the performance of an on-chip photonic reservoir computer using nonlinear microring resonator as neurons. We present dynamical properties of the nonlinear node and the reservoir computer, and we analyse the performance of the reservoir on a typical nonlinear Boolean task : the delayed XOR task. We study the performance for various designs (number of nodes, and length of the synapses in the reservoir), and with respect to the properties of the optical injection of the data (optical detuning and power). From this work, we find that such a reservoir has state-of-the art level of performance on this particular task - that is a bit error rate of 2.5 10-4 - at 20 Gb/s, with very good power efficiency (total injected power lower than 1.0 mW).
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Florian Denis-le Coarer, Florian Denis-le Coarer, Damien Rontani, Damien Rontani, Andrew Katumba, Andrew Katumba, Matthias Freiberger, Matthias Freiberger, Joni Dambre, Joni Dambre, Peter Bienstman, Peter Bienstman, Marc Sciamanna, Marc Sciamanna, } "Toward neuro-inspired computing using a small network of micro-ring resonators on an integrated photonic chip", Proc. SPIE 10689, Neuro-inspired Photonic Computing, 1068908 (21 May 2018); doi: 10.1117/12.2306780; https://doi.org/10.1117/12.2306780
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