Data enhanced iterative few-sample learning algorithm-based inverse design of 2D programmable chiral metamaterials

Data enhanced iterative few-sample learning algorithm-based inverse design of 2D programmable chiral metamaterials

A data enhanced iterative few-sample (DEIFS) algorithm is proposed to achieve the accurate and efficient inverse design of multi-shaped 2D chiral metamaterials. Specifically, three categories of 2D diffractive chiral structures with different geometrical parameters, including widths, separation spac...

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Bibliographic Details
Main Authors: Zhao Zeyu, You Jie, Zhang Jun, Du Shiyin, Tao Zilong, Tang Yuhua, Jiang Tian
Format: Article
Language:English
Published: De Gruyter 2022-09-01
Series:Nanophotonics
Subjects:
deep learning
few-sample
inverse design
programmable metamaterial
Online Access:https://doi.org/10.1515/nanoph-2022-0310
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https://doi.org/10.1515/nanoph-2022-0310

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