Artificial Synapse with Mnemonic Functionality using GSST-based Photonic Integrated Memory
2021 ◽
Vol 35
(11)
◽
pp. 1447-1449
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Here we present a multi-level discrete-state nonvolatile photonic memory based on an ultra-compact (<4μm) hybrid phase change material GSST-silicon Mach Zehnder modulator, with low insertion losses (3dB), to serve as node in a photonic neural network. Emulating an opportunely trained 100 × 100 fully connected multilayered perceptron neural network with this weighting functionality embedded as photonic memory, shows up to 92% inference accuracy and robustness towards noise when performing predictions of unseen data.
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2021 ◽
Vol 1914
(1)
◽
pp. 012036
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