Fig. 1: Neural nano-optics end-to-end design.

Our learned, ultrathin meta-optic as shown in (a) is 500 μm in thickness and diameter, allowing for the design of a miniature camera. The manufactured optic is shown in (b). A zoom-in is shown in (c) and nanopost dimensions are shown in (d). Our end-to-end imaging pipeline shown in e is composed of the proposed efficient metasurface image formation model and the feature-based deconvolution algorithm. From the optimizable phase profile, our differentiable model produces spatially varying PSFs, which are then patch-wise convolved with the input image to form the sensor measurement. The sensor reading is then deconvolved using our algorithm to produce the final image. The illustrations above “Meta-Optic” and “Sensor” in (e) were created by the authors using Adobe Illustrator.