Terahertz pulse shaping using diffractive surfaces

Abstract

Recent advances in deep learning have been providing non-intuitive solutions to various inverse problems in optics. At the intersection of machine learning and optics, diffractive networks merge wave-optics with deep learning to design task-specific elements to all-optically perform various tasks such as object classification and machine vision. Here, we present a diffractive network, which is used to shape an arbitrary broadband pulse into a desired optical waveform, forming a compact and passive pulse engineering system. We demonstrate the synthesis of various different pulses by designing diffractive layers that collectively engineer the temporal waveform of an input terahertz pulse. Our results demonstrate direct pulse shaping in terahertz spectrum, where the amplitude and phase of the input wavelengths are independently controlled through a passive diffractive device, without the need for an external pump. Furthermore, a physical transfer learning approach is presented to illustrate pulse-width tunability by replacing part of an existing network with newly trained diffractive layers, demonstrating its modularity. This learning-based diffractive pulse engineering framework can find broad applications in e.g., communications, ultra-fast imaging and spectroscopy.

Roadmap of Terahertz Imaging 2021

“…Deserving of mention is single-pixel near-field imaging, which enables spatially resolved sub-wavelength patterns while recording the correlated intensity on a single-element detector [224], as well as the evolution of incoherent imaging using photonic-integrated devices-optical phased arrays [225]. One can predict the rise of metasurface uses in THz pulse shaping or in novel dispersion-engineering tools [226] as it was done already in flat optics components at visible light [227].…”

Photonic Matrix Computing: From Fundamentals to Applications

“…Among these three methods, MPLC was the first to be implemented in optical computing [12], and the initially programmable MVM was finished with spatial optical elements [9]. The MPLC matrix core is the only one that can currently support super-largescale matrix operation, which makes it valuable in pulse shaping [13], mode processing [14][15][16], and machine learning [5,[17][18][19]. In this review, we firstly survey recent researches and progress in optical MVMs and photonic artificial intelligence hardware.…”

Deep learning enhanced terahertz imaging of silkworm eggs development

“…One of the most advantages of THz video imaging lies in quickly obtaining sample images, laying a solid foundation for the subsequent THz image processing. Although recent advances in deep learning have been providing various versatile solutions for optics (Fan et al, 2020;Norris et al, 2020;Varadarajan et al, 2020), inspiring the intersection of deep learning and THz technology (Veli et al, 2021), the intelligent THz imaging technology and its applications are still in their infancy, and further explorations are highly demanded.…”