Publications by authors named "Luocheng Huang"

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.

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Wide field of view and light weight optics are critical for advanced eyewear, with applications in augmented/virtual reality and night vision. Conventional refractive lenses are often stacked to correct aberrations at a wide field of view, leading to limited performance and increased size and weight. In particular, simultaneously achieving a wide field of view and large aperture for light collection is desirable but challenging to realize in a compact form-factor.

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Light's ability to perform massive linear operations in parallel has recently inspired numerous demonstrations of optics-assisted artificial neural networks (ANN). However, a clear system-level advantage of optics over purely digital ANN has not yet been established. While linear operations can indeed be optically performed very efficiently, the lack of nonlinearity and signal regeneration require high-power, low-latency signal transduction between optics and electronics.

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Subwavelength diffractive optics known as meta-optics have demonstrated the potential to significantly miniaturize imaging systems. However, despite impressive demonstrations, most meta-optical imaging systems suffer from strong chromatic aberrations, limiting their utilities. Here, we employ inverse-design to create broadband meta-optics operating in the long-wave infrared (LWIR) regime (8-12 μm).

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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.

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Nano-optic imagers that modulate light at sub-wavelength scales could enable new applications in diverse domains ranging from robotics to medicine. Although metasurface optics offer a path to such ultra-small imagers, existing methods have achieved image quality far worse than bulky refractive alternatives, fundamentally limited by aberrations at large apertures and low f-numbers. In this work, we close this performance gap by introducing a neural nano-optics imager.

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A compact near-eye visor (NEV) system that can guide light from a display to the eye could transform augmented reality (AR) technology. Unfortunately, existing implementations of such an NEV either suffer from small field of view or chromatic aberrations. See-through quality and bulkiness further make the overall performance of the visors unsuitable for a seamless user experience.

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