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We demonstrate an all-optical low-power 2R regenerator of 10-Gb/s non-return-to-zero data based on a 10- -diameter electrically pumped microdisk laser, which is heterogeneously integrated onto the silicon-on-insulator platform and processed in a CMOS pilot line. The scheme results in BER improvement 8and works for submilliwatt-level input signals. The laser operates in the continuous-wave...
We present a complex network of interconnected optical structures for information processing. This network is an implementation of reservoir computing, a novel method in the field of machine learning. Reservoir computing can be used for example in classification problems such as speech and image recognition, or for the generation of arbitrary patterns, tasks which are usually very hard to generalize...
In this paper, we demonstrate excitability in a silicon-on-insulator microring. Neglecting the fast light dynamics simplifies the calculation of the excitability onset. Excitable microrings will be useful as a basic building block in all-optical neural networks.
In this paper we propose an optically pumped nanophotonic III-V semiconductor optical amplifier heterogeneously integrated on a silicon-on-insulator waveguide circuit through wafer bonding technology. 10µm long adiabatic tapers allow a full power transfer from the silicon waveguide layer to the III-V membrane. Low-power consumption is expected, given the high optical confinement in the 100nm thick...
Despite ever increasing computational power, recognition and classification problems remain challenging to solve. Recently advances have been made by the introduction of the new concept of reservoir computing. This is a methodology coming from the field of machine learning and neural networks and has been successfully used in several pattern classification problems, like speech and image recognition...
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