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|a 10.1107/S1600577524004958
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|a eng
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|a Sanchez Del Rio, Manuel
|e verfasserin
|4 aut
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|a X-ray lens figure errors retrieved by deep learning from several beam intensity images
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|c 2024
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 05.09.2024
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a open access.
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|a The phase problem in the context of focusing synchrotron beams with X-ray lenses is addressed. The feasibility of retrieving the surface error of a lens system by using only the intensity of the propagated beam at several distances is demonstrated. A neural network, trained with a few thousand simulations using random errors, can predict accurately the lens error profile that accounts for all aberrations. It demonstrates the feasibility of routinely measuring the aberrations induced by an X-ray lens, or another optical system, using only a few intensity images
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|a Journal Article
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|a compound refractive lens
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|a machine learning
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|a modeling
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|a neural network
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| 650 |
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|a simulation
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| 700 |
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|a Celestre, Rafael
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Reyes-Herrera, Juan
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Journal of synchrotron radiation
|d 1994
|g 31(2024), Pt 5 vom: 01. Sept., Seite 1001-1009
|w (DE-627)NLM09824129X
|x 1600-5775
|7 nnas
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| 773 |
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|g volume:31
|g year:2024
|g number:Pt 5
|g day:01
|g month:09
|g pages:1001-1009
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|u http://dx.doi.org/10.1107/S1600577524004958
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