Dataset 'Advancing Machine Learning Optimization of Chiral Photonic Metasurface: Comparative Study of Neural Network and Genetic Algorithm Approaches'
Dataset 'Advancing Machine Learning Optimization of Chiral Photonic Metasurface: Comparative Study of Neural Network and Genetic Algorithm Approaches'
This dataset contains the shapes and spectra generated through the use of the chiral metasurface machine-learning optimization framework in the article "Advancing Machine Learning Optimization of Chiral Photonic Metasurface: Comparative Study of Neural Network and Genetic Algorithm Approaches". A preprint of the article is available on arXiv via external link [ arXiv:2512.13656, https://arxiv.org/abs/2512.13656 or https://doi.org/10.48550/arXiv.2512.13656 ]. Also, see accepted manuscript https://doi.org/10.1002/apxr.202500223 (Advanced Physics Research).
- Justus Liebig University Giessen Germany
- Zhejiang Ocean University China (People's Republic of)
- University of Namur Belgium
artificial intelligence optics design, machine learning, chiral photonics, dielectric metamaterials, stochastic evolutionary algorithm
artificial intelligence optics design, machine learning, chiral photonics, dielectric metamaterials, stochastic evolutionary algorithm
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