通过深度学习从多个光束强度图像中检索 X 射线透镜图形误差。

IF 2.5 3区 物理与天体物理
Journal of Synchrotron Radiation Pub Date : 2024-09-01 Epub Date: 2024-07-23 DOI:10.1107/S1600577524004958
Manuel Sanchez Del Rio, Rafael Celestre, Juan Reyes-Herrera
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引用次数: 0

摘要

该论文探讨了用 X 射线透镜聚焦同步加速器光束时的相位问题。研究证明了仅利用传播光束在若干距离上的强度来检索透镜系统表面误差的可行性。通过使用随机误差进行几千次模拟训练的神经网络,可以准确预测包含所有像差的透镜误差曲线。它证明了只用几幅强度图像就能对 X 射线透镜或其他光学系统引起的像差进行常规测量的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
X-ray lens figure errors retrieved by deep learning from several beam intensity images.

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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来源期刊
Journal of Synchrotron Radiation
Journal of Synchrotron Radiation INSTRUMENTS & INSTRUMENTATIONOPTICS&-OPTICS
CiteScore
5.60
自引率
12.00%
发文量
289
审稿时长
1 months
期刊介绍: Synchrotron radiation research is rapidly expanding with many new sources of radiation being created globally. Synchrotron radiation plays a leading role in pure science and in emerging technologies. The Journal of Synchrotron Radiation provides comprehensive coverage of the entire field of synchrotron radiation and free-electron laser research including instrumentation, theory, computing and scientific applications in areas such as biology, nanoscience and materials science. Rapid publication ensures an up-to-date information resource for scientists and engineers in the field.
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