Terahertz pulse shaping using diffractive networks

Muhammed Veli; Deniz Mengu; Nezih T. Yardimci; Yi Luo; Jingxi Li; Yair Rivenson; Mona Jarrahi; Aydogan Ozcan

doi:10.1117/12.2579808

5 March 2021 Terahertz pulse shaping using diffractive networks

Muhammed Veli, Deniz Mengu, Nezih T. Yardimci, Yi Luo, Jingxi Li, Yair Rivenson, Mona Jarrahi, Aydogan Ozcan

Proceedings Volume 11703, AI and Optical Data Sciences II; 117031G (2021) https://doi.org/10.1117/12.2579808
Event: SPIE OPTO, 2021, Online Only

Abstract

We present a diffractive network, trained for pulse engineering to shape input pulses into desired optical waveforms. The synthesis of square-pulses with various widths was experimentally demonstrated with 3D-fabricated passive diffractive layers that control both the amplitude and phase profile of the input terahertz pulse across a wide range of frequencies. Pulse-width tunability was also demonstrated by altering the layer-to-layer distances of a diffractive network. Furthermore, the modularity of this framework was demonstrated by replacing part of an already-trained network with newly-trained layers to tune the width of the output terahertz pulse, presenting a Lego-like physical transfer learning approach.

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Muhammed Veli, Deniz Mengu, Nezih T. Yardimci, Yi Luo, Jingxi Li, Yair Rivenson, Mona Jarrahi, and Aydogan Ozcan "Terahertz pulse shaping using diffractive networks", Proc. SPIE 11703, AI and Optical Data Sciences II, 117031G (5 March 2021); https://doi.org/10.1117/12.2579808

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KEYWORDS

Pulse shaping

Networks

Imaging spectroscopy

Machine vision

Neural networks

Optical spectroscopy

Optical spectroscopy imaging

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