1,720,982 research outputs found
Photonic reservoir computing for nonlinear equalization of 64-QAM signals with a Kramers-Kronig receiver
Get PDFPhotonic reservoir computing is a promising processing solution for the equalization of fiber optic communication signals. We simulate the nonlinear equalization of 64 Quadrature-Amplitude Modulated signals using a fully passive space multiplexed reservoir. The system deploys direct detection using the recently proposed Kramers-Kronig receiver. (C) 2022 The Author(s
Experimental results on nonlinear distortion compensation using photonic reservoir computing with a single set of weights for different wavelengths
Get PDFPhotonics-based computing approaches in combination with wavelength division multiplexing offer a potential solution to modern data and bandwidth needs. This paper experimentally takes an important step towards wavelength division multiplexing in an integrated waveguide-based photonic reservoir computing platform by using a single set of readout weights for up to at least 3 ITU-T channels to efficiently scale the data bandwidth when processing a nonlinear signal equalization task on a 28 Gbps modulated on-off keying signal. Using multiple-wavelength training, we obtain bit error rates well below that of the 1.5 x 10(-2) forward error correction limit at high fiber input powers of 18 dBm, which result in high nonlinear distortion. The results of the reservoir chip are compared to a tapped delay line filter and clearly show that the system performs nonlinear equalization. This was achieved using only limited post processing which in future work can be implemented in optical hardware as well
Photonic reservoir computing for wavelength multiplexed nonlinear fiber distortion mitigation
No full textWe seek to improve nonlinear fiber distortion mitigation for wavelength multiplexed telecommunications in terms of both processing speed and energy efficiency. We propose a photonic reservoir computing hardware implementation maximizing the chip footprint to processing power ratio by employing a single readout for all wavelengths
Machine learning issues and opportunities in ultrafast particle classiication for label-free microflow cymetry
No full textCombining a passive spatial photonic reservoir computer with a semiconductor laser increases its nonlinear computational capacity
Get PDFPhotonic reservoir computing has been used to efficiently solve difficult and timeconsuming problems. The physical implementations of such reservoirs offer low power consumption and fast processing speed due to their photonic nature. In this paper, we investigate the computational capacity of a passive spatially distributed reservoir computing system. It consists of a network of waveguides connected via optical splitters and combiners. A limitation of its reservoir is that it is fully linear and that the nonlinearity - which is often required for solving computing tasks - is only introduced in the output layer. To address this issue, we investigate the incorporation of an additional active nonlinear component into the system. Our approach involves the integration of a single semiconductor laser in an external optical delay line within the architecture. Based on numerical simulations, we show that the architecture with this semiconductor laser has a nonlinear computational capacity that is significantly increased as compared to the original passive architecture, which can be beneficial to solving difficult computational tasks
Photonic Reservoir Computing for Nonlinear Equalization of 64-QAM Signals with a Kramers-Kronig Receiver
No full textParts of this work were performed in the context of the EU projects ITN Postdigital (GA860360), Nebula (871658) and Neoteric (GA871330)
Wavelength dimension in waveguide-based photonic reservoir computing
Get PDFExisting work on coherent photonic reservoir computing (PRC) mostly concentrates on single-wavelength solutions. In this paper, we discuss the opportunities and challenges related to exploiting the wavelength dimension in integrated photonic reservoir computing systems. Different strategies are presented to be able to process several wavelengths in parallel using the same readout. Additionally, we present multiwavelength training techniques that allow to increase the stable operating wavelength range by at least a factor of two. It is shown that a single-readout photonic reservoir system can perform with approximate to 0% BER on several WDM channels in parallel for bit-level tasks and nonlinear signal equalization. This even when taking manufacturing deviations and laser wavelength drift into account. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreemen
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