Fully (implemented, scalable, and parallel) recurrent photonic neural networks in multimode semiconductor lasers

Anas Skalli; Xavier Porte; Nasibeh Haghighi; James Lott; Stephan Reitzenstein; Daniel Brunner

doi:10.1117/12.2650070

17 March 2023 Fully (implemented, scalable, and parallel) recurrent photonic neural networks in multimode semiconductor lasers

Anas Skalli, Xavier Porte, Nasibeh Haghighi, James Lott, Stephan Reitzenstein, Daniel Brunner

Author Affiliations +

Proceedings Volume PC12438, AI and Optical Data Sciences IV; PC124380G (2023) https://doi.org/10.1117/12.2650070
Event: SPIE OPTO, 2023, San Francisco, California, United States

Abstract

Photonic neural networks are a highly promising computational system for AI-inspired future information processing. We have recently demonstrated the first fully implemented, photonic neural network realized in multimode semicondcutor lasers. The numerous laser modes acts as the systems neurons, which carrier diffusion and intra-cavity diffraction creating recurrent connections. I will discuss our recent result, where we push the realtime data-rate of the neural network towards GHz levels and use such systems to address highly relevant photonic-technology applications.

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Citation Download Citation

Anas Skalli, Xavier Porte, Nasibeh Haghighi, James Lott, Stephan Reitzenstein, and Daniel Brunner "Fully (implemented, scalable, and parallel) recurrent photonic neural networks in multimode semiconductor lasers", Proc. SPIE PC12438, AI and Optical Data Sciences IV, PC124380G (17 March 2023); https://doi.org/10.1117/12.2650070

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