Science Alert December 4, 2021
Although metasurface optics offer a path to ultra-small imagers, existing methods have achieved image quality far worse than bulky refractive alternatives because of aberrations at large apertures and low f-numbers. A team of researchers in the US (Princeton University, Washington University) has introduced a neural nano-optics imager. They devised a fully differentiable learning framework that learns a metasurface physical structure in conjunction with a neural feature-based image reconstruction algorithm achieving an order of magnitude lower reconstruction error than existing approaches. They experimentally validated the results. The nano-optic imager combines the widest field-of-view for full-color metasurface operation while simultaneously achieving the largest demonstrated aperture of 0.5 mm at a f-number of 2. Nano-optic imagers that modulate light at sub-wavelength scales could enable new applications in diverse domains ranging from robotics to medicine…read more. Open Access TECHNICAL ARTICLE
Existing micro-sized camera (left) versus the new model (right). Credit: Princeton University