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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 Quantitative phase imaging (QPI) recovers the exact wavefront of light from intensity measurements. Topographical and optical density maps of translucent microscopic bodies can be extracted from these quantified phase shifts. We demonstrate quantitative phase imaging at the tip of a coherent fiber bundle using chromatic aberrations inherent in a silicon nitride hyperboloid metalens. Our method leverages spectral multiplexing to recover phase from multiple defocus planes in a single capture using a color camera. Our 0.5 mm aperture metalens shows robust quantitative phase imaging capability with a$${28}^{\circ}$$ ${28}^{\circ }$field of view and 0.$${2}{\pi}$$ $2\pi$phase resolution ( ~ 0.$${1}{\lambda}$$ $1\lambda$in air) for experiments with an endoscopic fiber bundle. Since the spectral functionality is encoded directly in the imaging lens, the metalens acts both as a focusing element and a spectral filter. The use of a simple computational backend will enable real-time operation. Key limitations in the adoption of phase imaging methods for endoscopy such as multiple acquisition, interferometric alignment or mechanical scanning are completely mitigated in the reported metalens based QPI. 

Abstract Endoscopes are an important component for the development of minimally invasive surgeries. Their size is one of the most critical aspects, because smaller and less rigid endoscopes enable higher agility, facilitate larger accessibility, and induce less stress on the surrounding tissue. In all existing endoscopes, the size of the optics poses a major limitation in miniaturization of the imaging system. Not only is making small optics difficult, but their performance also degrades with downscaling. Meta-optics have recently emerged as a promising candidate to drastically miniaturize optics while achieving similar functionalities with significantly reduced size. Herein, we report an inverse-designed meta-optic, which combined with a coherent fiber bundle enables a 33% reduction in the rigid tip length over traditional gradient-index (GRIN) lenses. We use the meta-optic fiber endoscope (MOFIE) to demonstrate real-time video capture in full visible color, the spatial resolution of which is primarily limited by the fiber itself. Our work shows the potential of meta-optics for integration and miniaturization of biomedical devices towards minimally invasive surgery. 

Abstract 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. We devise a fully differentiable learning framework that learns a metasurface physical structure in conjunction with a neural feature-based image reconstruction algorithm. Experimentally validating the proposed method, we achieve an order of magnitude lower reconstruction error than existing approaches. As such, we present a high-quality, nano-optic imager that combines the widest field-of-view for full-color metasurface operation while simultaneously achieving the largest demonstrated aperture of 0.5 mm at an f-number of 2. 

Sub-wavelength diffractive meta-optics have emerged as a versatile platform to manipulate light fields at will, due to their ultra-small form factor and flexible multifunctionalities. However, miniaturization and multimodality are typically compromised by a reduction in imaging performance; thus, meta-optics often yield lower resolution and stronger aberration compared to traditional refractive optics. Concurrently, computational approaches have become popular to improve the image quality of traditional cameras and exceed limitations posed by refractive lenses. This in turn often comes at the expense of higher power and latency, and such systems are typically limited by the availability of certain refractive optics. Limitations in both fields have thus sparked cross-disciplinary efforts to not only overcome these roadblocks but also to go beyond and provide synergistic meta-optical–digital solutions that surpass the potential of the individual components. For instance, an application-specific meta-optical frontend can preprocess the light field of a scene and focus it onto the sensor with a desired encoding, which can either ease the computational load on the digital backend or can intentionally alleviate certain meta-optical aberrations. In this review, we introduce the fundamentals, summarize the development of meta-optical computational imaging, focus on latest advancements that redefine the current state of the art, and give a perspective on research directions that leverage the full potential of sub-wavelength photonic platforms in imaging and sensing applications. The current advancement of meta-optics and recent investments by foundries and technology partners have the potential to provide synergistic future solutions for highly efficient, compact, and low-power imaging systems. 

Metasurfaces have recently risen to prominence in optical research, providing unique functionalities that can be used for imaging, beam forming, holography, polarimetry, and many more, while keeping device dimensions small. Despite the fact that a vast range of basic metasurface designs has already been thoroughly studied in the literature, the number of metasurfacerelated papers is still growing at a rapid pace, as metasurface research is now spreading to adjacent fields, including computational imaging, augmented and virtual reality, automotive, display, biosensing, nonlinear, quantum and topological optics, optical computing, and more. At the same time, the ability of metasurfaces to perform optical functions in much more compact optical systems has triggered strong and constantly growing interest from various industries that greatly benefit from the availability of miniaturized, highly functional, and efficient optical components that can be integrated in optoelectronic systems at low cost. This creates a truly unique opportunity for the field of metasurfaces to make both a scientific and an industrial impact. The goal of this Roadmap is to mark this “golden age” of metasurface research and define future directions to encourage scientists and engineers to drive research and development in the field of metasurfaces toward both scientific excellence and broad industrial adoption.