A major challenge for nanophotonics engineers is the wide range of optical responses that metamaterials and other nanoplasmonic structures can generate. In the past few years, machine learning has emerged as a powerful tool for sifting through this vast ...
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Nanowerk Nanotechnology Spotlight


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Applying machine learning to nanophotonic design efforts

A major challenge for nanophotonics engineers is the wide range of optical responses that metamaterials and other nanoplasmonic structures can generate. In the past few years, machine learning has emerged as a powerful tool for sifting through this vast universe of possible design parameters to aid the design of nanophotonic devices tailored for specific applications. A novel approach uses a type of neural network called a mixture density network to solve the non-uniqueness problem of machine learning algorithms, while also improving accuracy.