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DFlat is a forward and inverse design framework for flat optics. Although specially geared for the design of metasurface optics, it may be used for any end-to-end imaging and sensing task.
This repository hosts a simple demonstration of a deep learning approach for the inverse design of patch antennas. The goal is to explore energy-efficient designs and to significantly reduce simulation cost compared to conventional methods.
MATLAB implementation of the Huygens-Fresnel principle for the calculation of the scattering farfield pattern produced from the illumination of a finite-aperture rectangular metasurface.
(Tensorflow Version) D-Flat is a forward and inverse design framework for flat optics. Although specially geared for the design of metasurface optics, it may be used for any end-to-end imaging and sensing task.
Meta_SCMT is a software to inverse design large-area dielectric metasurface. The key factor that differentiates the Meta_SCMT from current Local Periodic Approximation(LPA) based methods is that Meta_SCMT can achieve fullwave-level accuracy with much less computational resource.
SmartGlass (SG) is a python implementation of a diffractive optical neural network. Currently, it supports training an all-optical classifier (e.g. classify hand-written digits MNIST dataset). Besides, the framework can also be used to design optics based on a task like focusing and beam steering. However, custom object functions should be defin…