Large-scale multi-beamshape phase retrieval dataset based on Zernike coefficients for PBF-LB/M systems

This simulated dataset containing six beam shapes is used for training and testing in our paper "Deep learning based phase retrieval with complex beam shapes for beam shape correction". In this dataset, there are 6 sub-datasets stored in 6 folders named by corresponding beam shapes. For ea...

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Bibliographic Details
Main Author: Shengyuan Yan (22248700) (author)
Other Authors: Richard Off (20818631) (author), Anil Bora Yayak (22468386) (author), Katrin Wudy (20818637) (author), Anoush Aghajani-Talesh (20818640) (author), Markus Birg (20818643) (author), Jonas Grünewald (20818646) (author), Mike Holenderski (22365142) (author), Nirvana Meratnia (20818652) (author)
Published: 2025
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Summary:This simulated dataset containing six beam shapes is used for training and testing in our paper "Deep learning based phase retrieval with complex beam shapes for beam shape correction". In this dataset, there are 6 sub-datasets stored in 6 folders named by corresponding beam shapes. For each beam shape, the trainging set has 10000 pairs of PBF-LB/M system's beam shape samples. Each paired sample contains 7 intensity images of the aberrated beam shape from the 3 pre-Fourier planes and 1 Fourier plane to the 3 post-Fourier planes paired by the Zernike coefficients used to aberrate the beam shape.<p></p>