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1 August 2021 Pulse shaping using diffractive optical networks designed by deep learning
Muhammed Veli, Deniz Mengu, Nezih T. Yardimci, Yi Luo, Jingxi Li, Yair Rivenson, Mona Jarrahi, Aydogan Ozcan
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Proceedings Volume 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021; 118041V (2021) https://doi.org/10.1117/12.2594472
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States
Abstract
We utilize diffractive optical networks to design small footprint, passive pulse engineering platforms, where an input terahertz pulse is shaped into a desired output waveform as it diffracts through spatially-engineered transmissive surfaces. Using 3D-printed diffractive networks designed by deep learning, various terahertz pulses with different temporal widths are experimentally synthesized by controlling the amplitude and phase of the input pulse over a wide range of frequencies. Pulse width tunability was also demonstrated by changing the layer-to-layer distance of a 3D-printed diffractive network or by physically replacing 1-2 layers of an existing network with newly trained and fabricated diffractive layers.
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Muhammed Veli, Deniz Mengu, Nezih T. Yardimci, Yi Luo, Jingxi Li, Yair Rivenson, Mona Jarrahi, and Aydogan Ozcan "Pulse shaping using diffractive optical networks designed by deep learning", Proc. SPIE 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021, 118041V (1 August 2021); https://doi.org/10.1117/12.2594472
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KEYWORDS
Optical networks
Pulse shaping
Inverse optics
Optical design
Networks
Network architectures
Spectroscopy
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