All-optical deep feed forward network based on nonlinear microresonators for telecom applications (Conference Presentation)

Mattia Mancinelli

doi:10.1117/12.2546546

20 March 2020 All-optical deep feed forward network based on nonlinear microresonators for telecom applications (Conference Presentation)

Mattia Mancinelli

Author Affiliations +

Proceedings Volume 11284, Smart Photonic and Optoelectronic Integrated Circuits XXII; 112840A (2020) https://doi.org/10.1117/12.2546546
Event: SPIE OPTO, 2020, San Francisco, California, United States

Abstract

Recently, there have been a renewed interest on brain-inspired (neuromorphic) computing schemes that are directly implemented on a physical platform. In fact, such optical or electrical platforms allow performing important computational tasks at a speed much higher than the software-based counterparts. Here we propose to use neuromorphic silicon photonics to recover data integrity directly in the optical domain outperforming the electronic performances. We demonstrate a silicon photonic Feed Forward Network that can be trained to solve several tasks directly in the optical domain: linear and non-linear distortion recovering, demodulation of complex modulated data and error correction.

Conference Presentation

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Mattia Mancinelli "All-optical deep feed forward network based on nonlinear microresonators for telecom applications (Conference Presentation)", Proc. SPIE 11284, Smart Photonic and Optoelectronic Integrated Circuits XXII, 112840A (20 March 2020); https://doi.org/10.1117/12.2546546

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KEYWORDS

Microresonators

Nonlinear optics

Data processing

Neurons

Signal processing

Computer architecture

Data corrections

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