We present subwavelength imaging of amplitude- and phase-encoded objects based on a solid-immersion diffractive processor designed through deep learning. Subwavelength features from the objects are resolved by the collaboration between a jointly-optimized diffractive encoder and decoder pair. We experimentally demonstrated the subwavelength-imaging performance of solid immersion diffractive processors using terahertz radiation and achieved all-optical reconstruction of subwavelength phase features of objects (with linewidths of ~λ/3.4, where λ is the wavelength) by transforming them into magnified intensity images at the output field-of-view. Solid-immersion diffractive processors would provide cost-effective and compact solutions for applications in bioimaging, sensing, and material inspection, among others.
We present a universal polarization transformer composed of diffractive layers and linear polarizer arrays, capable of all-optically synthesizing a large set of complex-valued polarization scattering matrices between the polarization states at different positions within its input and output fields-of-view. We numerically demonstrated that our deep learning-based design could synthesize 10,000 different spatially-encoded polarization scattering matrices within a single diffractive volume. Using wire-grid polarizers and 3D-printed diffractive layers, we also demonstrated an experimental proof-of-concept by achieving an all-optical polarization permutation operation with 16. Our innovative framework can inspire new devices with versatile polarization control capabilities in various fields.
We present a diffractive terahertz sensor using a single-pixel detector to rapidly sense hidden defects within a target sample volume. Leveraging multiple spatially-engineered diffractive layers optimized via deep learning, this diffractive sensor can all-optically process the sample scattered waves and generate an output spectrum encoding information for indicating the presence/absence of hidden defects. We experimentally validated this framework using a single-pixel terahertz time-domain spectroscopy set-up and 3D-printed diffractive layers, successfully detecting unknown hidden defects within silicon samples. By circumventing raster scanning and digital image formation/reconstruction, this framework holds vast potential for various applications requiring high-throughput, non-destructive defect detection.
We present a diffractive camera that performs class-specific imaging of target objects, while all-optically and instantaneously erasing the objects from other classes during light propagation through thin diffractive layers, maximizing privacy preservation. We experimentally validated this class-specific camera design by 3D-printing the resulting diffractive layers (optimized through deep learning) and selectively imaging MNIST handwritten digits using the assembled camera system under terahertz radiation. The presented object class-specific camera is passive and does not require external computing power, providing a data-efficient solution to task-specific and privacy-aware modern imaging applications.
Band structures engineering of periodic optical structures enables the control of light propagation and localization. Although photons trapped inside 2D lattices can be described within the first Brillouin zone in reciprocal space, the wavevectors of scattered photons outside the lattice are limited by the 3D light cone, which depicts the free-photon dispersion in the surroundings. Because plasmonic nanoparticle lattices show unique dual properties of light trapping and strong scattering, this material platform is promising for investigations of radiative losses. This talk describes how light-cone surface lattice resonance (SLRs) from plasmonic nanoparticle lattices allow the observation of radiated electromagnetic fields. We theoretically predicted the angular distributions of the radiated fields, and experimentally probed the light-cone SLR modes by in-plane lasing emission. These results provide a nanolaser design strategy to achieve tunable lasing colors by lattice rotation.
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