Multi-wavelength laser sources on silicon photonics can enable large spectral coverage for DWDM optical I/O links and leverage the scalability of a CMOS compatible process simultaneously. In this work, we report a laser array of four four-wavelength distributed feedback lasers that produce in total sixteen wavelength channels simultaneously with a wavelength spacing of 200 GHz and output power of 17 dBm per laser. We show integrated III-V/Si hybrid lasers on the same die with wafer-level bonded epitaxial III-V layer that spans a spectral coverage of 17 nm through the 16 wavelength channels. We also measured the relative intensity noise (RIN) of all sixteen wavelength channels to be under -135 dB/Hz and the Lorentzian linewidth to be less than 300 kHz.
Multi-wavelength laser sources have gained significant interest for future high-bandwidth density DWDM optical links, enabling improved energy efficiency and bandwidth scaling. In this work, we present an integrated III-V/Si hybrid four-wavelength DFB laser with 200 GHz wavelength spacing and <10 dBm output power per wavelength. The wavelength spacing and total output power variations are <±25 GHz and <1 dB, respectively, for an ambient temperature change of 30°C. We also measured the relative intensity noise (RIN) and Lorentzian linewidth of the laser to be <-135 dB/Hz and <300 kHz, respectively.
Reservoir computing has emerged as a lightweight, high-speed machine learning paradigm. We introduce a new optoelectronic reservoir computer for image recognition, in which input data is first pre-processed offline using two convolutional neural network layers with randomly initialized weights, generating a series of random feature maps. These random feature maps are then multiplied by a random mask matrix to generate input nodes, which are then passed to the reservoir computer. Using the MNIST dataset in simulation, we achieve performance in line with state-of-the-art convolutional neural networks (1% error), while potentially offering order-of-magnitude improvement in training speeds.
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