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Topological encoding method for data-driven photonics inverse design
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DOI：10.1364/OE.387504.png)
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Abstract
En 中文
Data-driven approaches have been proposed as effective strategies for the inverse design and optimization of photonic structures in recent years. In order to assist data-driven methods for the design of topology of photonic devices, we propose a topological encoding method that transforms photonic structures represented by binary images to a continuous sparse representation. This sparse representation can be utilized for dimensionality reduction and dataset generation, enabling effective analysis and optimization of photonic topologies with data-driven approaches. As a proof of principle, we leverage our encoding method for the design of two dimensional non-paraxial diffractive optical elements with various diffraction intensity distributions. We proved that our encoding method is able to assist machine-learning-based inverse design approaches for accurate and global optimization. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Keywords:
OPTIMIZATION
NANOPHOTONICS
METASURFACE
Journal
IF:
3.3
Papers:
6.1W
Citations:
14.3W