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Abstract Silicon is a common material of choice for semiconductor optics in the infrared spectral range, due to its low cost, well-developed high-volume manufacturing methods, high refractive index, and transparency. It is, however, typically ill-suited for applications in the visible range, due to its large absorption coefficient, especially for green and blue light. Counterintuitively, we demonstrate how ultra-thin crystalline meta-optics enable full-color imaging in the visible range. For this purpose, we employ an inverse design approach, which maximizes the volume under the broadband modulation transfer function of the meta-optics. Beyond that, we demonstrate polarization-multiplexed functionality in the visible. This is particularly important as polarization optics require high index materials, a characteristic often difficult to obtain in the visible. 

Abstract Metalenses, with their ultrathin thicknesses and their ease for achieving ultra small diameters, offer a promising alternative to refractive lenses in miniaturized imaging systems, such as endoscopes, potentially enabling applications in tightly confined spaces. However, traditional metalenses suffer from strong chromatic aberrations, limiting their utility in multi-color imaging. To address this limitation, here we present an inverse-designed polychromatic metalens with a diameter of 680 μm, focal length of 400 μm, and low dispersion across 3 distinct wavelengths at 643 nm, 532 nm, and 444 nm. The metalens collimates and steers light emitted from a scanning fiber tip, generating scanning beams across a 70° field-of-view to provide illumination for a scan-based imaging. The metalens provides a close-to-diffraction-limited 0.5° angular resolution, only restricted by the effective aperture of the system. The average relative efficiency among three design wavelengths is around 32% for on-axis angle and 13% averaged across the entire field-of-view. This work holds promise for the application of metalenses in endoscopes and other miniaturized imaging systems. 

Harnessing commonsense knowledge poses a significant challenge for machine comprehension systems. This paper primarily focuses on incorporating a specific subset of commonsense knowledge, namely, script knowledge. Script knowledge is about sequences of actions that are typically performed by individuals in everyday life. Our experiments were centered around the MCScript dataset, which was the basis of the SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge. As a baseline, we utilized our Three-Way Attentive Networks (TriANs) framework to model the interactions among passages, questions, and answers. Building upon the TriAN, we proposed to: (1) integrate a pre-trained language model to capture script knowledge; (2) introduce multi-layer attention to facilitate multi-hop reasoning; and (3) incorporate positional embeddings to enhance the model’s capacity for event-ordering reasoning. In this paper, we present our proposed methods and prove their efficacy in improving script knowledge integration and reasoning. 

A broad range of imaging and sensing technologies in the infrared require large field-of-view (FoV) operation. To achieve this, traditional refractive systems often employ multiple elements to compensate for aberrations, which leads to excess size, weight, and cost. For many applications, including night vision eye-wear, air-borne surveillance, and autonomous navigation for unmanned aerial vehicles, size and weight are highly constrained. Sub-wavelength diffractive optics, also known as meta-optics, can dramatically reduce the size, weight, and cost of these imaging systems, as meta-optics are significantly thinner and lighter than traditional refractive lenses. Here, we demonstrate 80° FoV thermal imaging in the long-wavelength infrared regime (8–12 µm) using an all-silicon meta-optic with an entrance aperture and lens focal length of 1 cm.