@article{Mario Miscuglio_Jiawei Meng_Armin Mehrabian_Volker J. Sorger_Omer Yesiliurt_Ludmila J. Prokopeva_Alexander V. Kildishev_Yifei Zhang_Juejun Hu_2020, title={Artificial Synapse with Mnemonic Functionality using GSST-based Photonic Integrated Memory}, volume={35}, url={https://journals.riverpublishers.com/index.php/ACES/article/view/7649}, abstractNote={<p>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.</p>}, number={11}, journal={The Applied Computational Electromagnetics Society Journal (ACES)}, author={Mario Miscuglio and Jiawei Meng and Armin Mehrabian and Volker J. Sorger and Omer Yesiliurt and Ludmila J. Prokopeva and Alexander V. Kildishev and Yifei Zhang and Juejun Hu}, year={2020}, month={Nov.}, pages={1447–1448} }