Untrained physics-driven aberration retrieval network

In the field of coherent diffraction imaging, phase retrieval is essential for correcting the aberration of an optic system. For estimating aberration from intensity, conventional methods rely on neural networks whose performance is limited by training datasets. In this Letter, we propose an untrain...

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Veröffentlicht in:	Optics letters 2024-08, Vol.49 (16), p.4545
Hauptverfasser:	Li, Shuo, Wang, Bin, Wang, Xiaofei
Format:	Artikel
Sprache:	eng
Schlagworte:	Aberration Light diffraction Luminous intensity Neural networks Phase retrieval Underpotential deposition
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