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26 February 2020 Neuromorphic computing through photonic integrated circuits
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Abstract
The identification of neuromorphic computing as a highly promising alternative computing system has been emerged from its potential to increase rapidly the computational efficiency that is currently restricted by Moore’s law end. First electronic neuromorphic chips like IBM’s TrueNorth and Intel’s Loihi revealed a tremendous performance improvement in terms of computational speed and density; however, they are still operating in MHz rates. To this end, neuromorphic photonic integrated circuits can further increase the computational speed and density, having a large portfolio of components with GHz-bandwidth and low-energy. Herein, we present an all-optical sigmoid activation function as well as a single-λ linear neuron. The all-optical sigmoid activation function comprises a Semiconductor Optical Amplifier-Mach-Zehnder Interferometer (SOA-MZI) configured in differentially-biased scheme followed by an SOA. Its thresholding capabilities have been experimentally demonstrated with 100psec optical pulses. Then, we introduce an all-optical phase-encoded weighting scheme and we experimentally demonstrate its linear algebra operational credentials by the means of a typical IQ modulator operated at 10Gbaud/s.
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© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
G. Mourgias-Alexandris, A. Totovic, N. Passalis, G. Dabos, A. Tefas, and N. Pleros "Neuromorphic computing through photonic integrated circuits", Proc. SPIE 11284, Smart Photonic and Optoelectronic Integrated Circuits XXII, 1128403 (26 February 2020); https://doi.org/10.1117/12.2543781
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