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19 April 2023 Versatile DMDs as input information platform and trainable weights in optical neural networks
Anas Skalli, Xavier Porte, Daniel Brunner
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Proceedings Volume PC12435, Emerging Digital Micromirror Device Based Systems and Applications XV; PC1243502 (2023) https://doi.org/10.1117/12.2650029
Event: SPIE OPTO, 2023, San Francisco, California, United States
Abstract
Digital micromirror devices are versatile, high performance photonic components that combine high configurability with a large number of programmable parameters and high bandwidth. These are essential features in photonic neural networks. A DMD's mirrors can optically encode information to be injected into a photonics neural network, or they can even provide configurable connections between photonic neurons of the neural network itself. Their easy programmability makes them highly attractive, as through this feature DMDs act as the interface between the analogue world of the photonic neural network, and the digital world of programming languages as well as information processing. I will introduce several of such DMD-based operations in photonic AI will sketch future possibilities for the development of the field.
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Anas Skalli, Xavier Porte, and Daniel Brunner "Versatile DMDs as input information platform and trainable weights in optical neural networks", Proc. SPIE PC12435, Emerging Digital Micromirror Device Based Systems and Applications XV, PC1243502 (19 April 2023); https://doi.org/10.1117/12.2650029
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KEYWORDS
Neural networks
Digital micromirror devices
Artificial intelligence
Computer programming
Computer programming languages
Data processing
Interfaces
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