Machine Learning Approach to the Topological Optimization of Metasurfaces

• We present our work on using machine learning for the topological optimization of metasurfaces. First, we show that deep neural networks can be used to predict the scattering properties of metasurfaces. Subsequently, we demonstrate the inverse design of free-form metasurfaces using a modified CGAN machine learning method that balances the accuracy of desired optical properties with experimental feasibility. Our method allows constraints imposed by the nanofabrication to be integrated in the optimization.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Language Technology (hsv//eng)

NATURVETENSKAP  -- Matematik -- Beräkningsmatematik (hsv//swe)

NATURAL SCIENCES  -- Mathematics -- Computational Mathematics (hsv//eng)

NATURVETENSKAP  -- Fysik -- Annan fysik (hsv//swe)

NATURAL SCIENCES  -- Physical Sciences -- Other Physics Topics (hsv//eng)

NATURVETENSKAP  -- Fysik -- Den kondenserade materiens fysik (hsv//swe)

NATURAL SCIENCES  -- Physical Sciences -- Condensed Matter Physics (hsv//eng)

Publikations- och innehållstyp

kon (ämneskategori)

ref (ämneskategori)